Sample records for adjusted effect estimates
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Balancing Score Adjusted Targeted Minimum Loss-based Estimation
Lendle, Samuel David; Fireman, Bruce; van der Laan, Mark J.
2015-01-01
Adjusting for a balancing score is sufficient for bias reduction when estimating causal effects including the average treatment effect and effect among the treated. Estimators that adjust for the propensity score in a nonparametric way, such as matching on an estimate of the propensity score, can be consistent when the estimated propensity score is not consistent for the true propensity score but converges to some other balancing score. We call this property the balancing score property, and discuss a class of estimators that have this property. We introduce a targeted minimum loss-based estimator (TMLE) for a treatment-specific mean with the balancing score property that is additionally locally efficient and doubly robust. We investigate the new estimator’s performance relative to other estimators, including another TMLE, a propensity score matching estimator, an inverse probability of treatment weighted estimator, and a regression-based estimator in simulation studies. PMID:26561539
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Empirical likelihood inference in randomized clinical trials.
Zhang, Biao
2017-01-01
In individually randomized controlled trials, in addition to the primary outcome, information is often available on a number of covariates prior to randomization. This information is frequently utilized to undertake adjustment for baseline characteristics in order to increase precision of the estimation of average treatment effects; such adjustment is usually performed via covariate adjustment in outcome regression models. Although the use of covariate adjustment is widely seen as desirable for making treatment effect estimates more precise and the corresponding hypothesis tests more powerful, there are considerable concerns that objective inference in randomized clinical trials can potentially be compromised. In this paper, we study an empirical likelihood approach to covariate adjustment and propose two unbiased estimating functions that automatically decouple evaluation of average treatment effects from regression modeling of covariate-outcome relationships. The resulting empirical likelihood estimator of the average treatment effect is as efficient as the existing efficient adjusted estimators 1 when separate treatment-specific working regression models are correctly specified, yet are at least as efficient as the existing efficient adjusted estimators 1 for any given treatment-specific working regression models whether or not they coincide with the true treatment-specific covariate-outcome relationships. We present a simulation study to compare the finite sample performance of various methods along with some results on analysis of a data set from an HIV clinical trial. The simulation results indicate that the proposed empirical likelihood approach is more efficient and powerful than its competitors when the working covariate-outcome relationships by treatment status are misspecified.
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An evaluation of bias in propensity score-adjusted non-linear regression models.
Wan, Fei; Mitra, Nandita
2018-03-01
Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.
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Pfeiffer, R M; Riedl, R
2015-08-15
We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.
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Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong
2017-12-28
Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.
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Estimating restricted mean treatment effects with stacked survival models
Wey, Andrew; Vock, David M.; Connett, John; Rudser, Kyle
2016-01-01
The difference in restricted mean survival times between two groups is a clinically relevant summary measure. With observational data, there may be imbalances in confounding variables between the two groups. One approach to account for such imbalances is estimating a covariate-adjusted restricted mean difference by modeling the covariate-adjusted survival distribution, and then marginalizing over the covariate distribution. Since the estimator for the restricted mean difference is defined by the estimator for the covariate-adjusted survival distribution, it is natural to expect that a better estimator of the covariate-adjusted survival distribution is associated with a better estimator of the restricted mean difference. We therefore propose estimating restricted mean differences with stacked survival models. Stacked survival models estimate a weighted average of several survival models by minimizing predicted error. By including a range of parametric, semi-parametric, and non-parametric models, stacked survival models can robustly estimate a covariate-adjusted survival distribution and, therefore, the restricted mean treatment effect in a wide range of scenarios. We demonstrate through a simulation study that better performance of the covariate-adjusted survival distribution often leads to better mean-squared error of the restricted mean difference although there are notable exceptions. In addition, we demonstrate that the proposed estimator can perform nearly as well as Cox regression when the proportional hazards assumption is satisfied and significantly better when proportional hazards is violated. Finally, the proposed estimator is illustrated with data from the United Network for Organ Sharing to evaluate post-lung transplant survival between large and small-volume centers. PMID:26934835
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Estimating regression to the mean and true effects of an intervention in a four-wave panel study.
Gmel, Gerhard; Wicki, Matthias; Rehm, Jürgen; Heeb, Jean-Luc
2008-01-01
First, to analyse whether a taxation-related decrease in spirit prices had a similar effect on spirit consumption for low-, medium- and high-level drinkers. Secondly, as the relationship between baseline values and post-intervention changes is confounded with regression to the mean (RTM) effects, to apply different approaches for estimating the RTM effect and true change. Consumption of spirits and total alcohol consumption were analysed in a four-wave panel study (one pre-intervention and three post-intervention measurements) of 889 alcohol consumers sampled from the general population of Switzerland. Two correlational methods, one method quantitatively estimating the RTM effect and one growth curve approach based on hierarchical linear models (HLM), were used to estimate RTM effects among low-, medium- and high-level drinkers. Adjusted for RTM effects, high-level drinkers increased consumption more than lighter drinkers in the short term, but this was not a persisting effect. Changes in taxation affected mainly light and moderate drinkers in the long term. All methods concurred that RTM effects were present to a considerable degree, and methods quantifying the RTM effect or adjusting for it yielded similar estimates. Intervention studies have to consider RTM effects both in the study design and in the evaluation methods. Observed changes can be adjusted for RTM effects and true change can be estimated. The recommended method, particularly if the aim is to estimate change not only for the sample as a whole, but for groups of drinkers with different baseline consumption levels, is growth curve modelling. If reliability of measurement instruments cannot be increased, the incorporation of more than one pre-intervention measurement point may be a valuable adjustment of the study design.
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Balentine, Courtney J; Vanness, David J; Schneider, David F
2018-01-01
We evaluated whether diagnostic thyroidectomy for indeterminate thyroid nodules would be more cost-effective than genetic testing after including the costs of long-term surveillance. We used a Markov decision model to estimate the cost-effectiveness of thyroid lobectomy versus genetic testing (Afirma®) for evaluation of indeterminate (Bethesda 3-4) thyroid nodules. The base case was a 40-year-old woman with a 1-cm indeterminate nodule. Probabilities and estimates of utilities were obtained from the literature. Cost estimates were based on Medicare reimbursements with a 3% discount rate for costs and quality-adjusted life-years. During a 5-year period after the diagnosis of indeterminate thyroid nodules, lobectomy was less costly and more effective than Afirma® (lobectomy: $6,100; 4.50 quality-adjusted life- years vs Afirma®: $9,400; 4.47 quality-adjusted life-years). Only in 253 of 10,000 simulations (2.5%) did Afirma® show a net benefit at a cost-effectiveness threshold of $100,000 per quality- adjusted life-years. There was only a 0.3% probability of Afirma® being cost saving and a 14.9% probability of improving quality-adjusted life-years. Our base case estimate suggests that diagnostic lobectomy dominates genetic testing as a strategy for ruling out malignancy of indeterminate thyroid nodules. These results, however, were highly sensitive to estimates of utilities after lobectomy and living under surveillance after Afirma®. Published by Elsevier Inc.
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Linden, Ariel
2017-08-01
When a randomized controlled trial is not feasible, health researchers typically use observational data and rely on statistical methods to adjust for confounding when estimating treatment effects. These methods generally fall into 3 categories: (1) estimators based on a model for the outcome using conventional regression adjustment; (2) weighted estimators based on the propensity score (ie, a model for the treatment assignment); and (3) "doubly robust" (DR) estimators that model both the outcome and propensity score within the same framework. In this paper, we introduce a new DR estimator that utilizes marginal mean weighting through stratification (MMWS) as the basis for weighted adjustment. This estimator may prove more accurate than treatment effect estimators because MMWS has been shown to be more accurate than other models when the propensity score is misspecified. We therefore compare the performance of this new estimator to other commonly used treatment effects estimators. Monte Carlo simulation is used to compare the DR-MMWS estimator to regression adjustment, 2 weighted estimators based on the propensity score and 2 other DR methods. To assess performance under varied conditions, we vary the level of misspecification of the propensity score model as well as misspecify the outcome model. Overall, DR estimators generally outperform methods that model one or the other components (eg, propensity score or outcome). The DR-MMWS estimator outperforms all other estimators when both the propensity score and outcome models are misspecified and performs equally as well as other DR estimators when only the propensity score is misspecified. Health researchers should consider using DR-MMWS as the principal evaluation strategy in observational studies, as this estimator appears to outperform other estimators in its class. © 2017 John Wiley & Sons, Ltd.
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Assessment of simulated aerosol effective radiative forcings in the terrestrial spectrum
NASA Astrophysics Data System (ADS)
Heyn, Irene; Block, Karoline; Mülmenstädt, Johannes; Gryspeerdt, Edward; Kühne, Philipp; Salzmann, Marc; Quaas, Johannes
2017-01-01
In its fifth assessment report (AR5), the Intergovernmental Panel on Climate Change provides a best estimate of the effective radiative forcing (ERF) due to anthropogenic aerosol at -0.9 W m-2. This value is considerably weaker than the estimate of -1.2 W m-2 in AR4. A part of the difference can be explained by an offset of +0.2 W m-2 which AR5 added to all published estimates that only considered the solar spectrum, in order to account for adjustments in the terrestrial spectrum. We find that, in the CMIP5 multimodel median, the ERF in the terrestrial spectrum is small, unless microphysical effects on ice- and mixed-phase clouds are parameterized. In the latter case it is large but accompanied by a very strong ERF in the solar spectrum. The total adjustments can be separated into microphysical adjustments (aerosol "effects") and thermodynamic adjustments. Using a kernel technique, we quantify the latter and find that the rapid thermodynamic adjustments of water vapor and temperature profiles are small. Observation-based constraints on these model results are urgently needed.
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A novel measure of effect size for mediation analysis.
Lachowicz, Mark J; Preacher, Kristopher J; Kelley, Ken
2018-06-01
Mediation analysis has become one of the most popular statistical methods in the social sciences. However, many currently available effect size measures for mediation have limitations that restrict their use to specific mediation models. In this article, we develop a measure of effect size that addresses these limitations. We show how modification of a currently existing effect size measure results in a novel effect size measure with many desirable properties. We also derive an expression for the bias of the sample estimator for the proposed effect size measure and propose an adjusted version of the estimator. We present a Monte Carlo simulation study conducted to examine the finite sampling properties of the adjusted and unadjusted estimators, which shows that the adjusted estimator is effective at recovering the true value it estimates. Finally, we demonstrate the use of the effect size measure with an empirical example. We provide freely available software so that researchers can immediately implement the methods we discuss. Our developments here extend the existing literature on effect sizes and mediation by developing a potentially useful method of communicating the magnitude of mediation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Grosse, Scott D; Chaugule, Shraddha S; Hay, Joel W
2015-01-01
Estimates of preference-weighted health outcomes or health state utilities are needed to assess improvements in health in terms of quality-adjusted life-years. Gains in quality-adjusted life-years are used to assess the cost–effectiveness of prophylactic use of clotting factor compared with on-demand treatment among people with hemophilia, a congenital bleeding disorder. Published estimates of health utilities for people with hemophilia vary, contributing to uncertainty in the estimates of cost–effectiveness of prophylaxis. Challenges in estimating utility weights for the purpose of evaluating hemophilia treatment include selection bias in observational data, difficulty in adjusting for predictors of health-related quality of life and lack of preference-based data comparing adults with lifetime or primary prophylaxis versus no prophylaxis living within the same country and healthcare system. PMID:25585817
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Wang, Tingting; Li, Hongkai; Su, Ping; Yu, Yuanyuan; Sun, Xiaoru; Liu, Yi; Yuan, Zhongshang; Xue, Fuzhong
2017-11-20
In observational studies, epidemiologists often attempt to estimate the total effect of an exposure on an outcome of interest. However, when the underlying diagram is unknown and limited knowledge is available, dissecting bias performances is essential to estimating the total effect of an exposure on an outcome when mistakenly adjusting for mediators under logistic regression. Through simulation, we focused on six causal diagrams concerning different roles of mediators. Sensitivity analysis was conducted to assess the bias performances of varying across exposure-mediator effects and mediator-outcome effects when adjusting for the mediator. Based on the causal relationships in the real world, we compared the biases of varying across the effects of exposure-mediator with those of varying across the effects of mediator-outcome when adjusting for the mediator. The magnitude of the bias was defined by the difference between the estimated effect (using logistic regression) and the total effect of the exposure on the outcome. In four scenarios (a single mediator, two series mediators, two independent parallel mediators or two correlated parallel mediators), the biases of varying across the effects of exposure-mediator were greater than those of varying across the effects of mediator-outcome when adjusting for the mediator. In contrast, in two other scenarios (a single mediator or two independent parallel mediators in the presence of unobserved confounders), the biases of varying across the effects of exposure-mediator were less than those of varying across the effects of mediator-outcome when adjusting for the mediator. The biases were more sensitive to the variation of effects of exposure-mediator than the effects of mediator-outcome when adjusting for the mediator in the absence of unobserved confounders, while the biases were more sensitive to the variation of effects of mediator-outcome than those of exposure-mediator in the presence of an unobserved confounder. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Revisiting the Table 2 fallacy: A motivating example examining preeclampsia and preterm birth.
Bandoli, Gretchen; Palmsten, Kristin; Chambers, Christina D; Jelliffe-Pawlowski, Laura L; Baer, Rebecca J; Thompson, Caroline A
2018-05-21
A "Table Fallacy," as coined by Westreich and Greenland, reports multiple adjusted effect estimates from a single model. This practice, which remains common in published literature, can be problematic when different types of effect estimates are presented together in a single table. The purpose of this paper is to quantitatively illustrate this potential for misinterpretation with an example estimating the effects of preeclampsia on preterm birth. We analysed a retrospective population-based cohort of 2 963 888 singleton births in California between 2007 and 2012. We performed a modified Poisson regression to calculate the total effect of preeclampsia on the risk of PTB, adjusting for previous preterm birth. pregnancy alcohol abuse, maternal education, and maternal socio-demographic factors (Model 1). In subsequent models, we report the total effects of previous preterm birth, alcohol abuse, and education on the risk of PTB, comparing and contrasting the controlled direct effects, total effects, and confounded effect estimates, resulting from Model 1. The effect estimate for previous preterm birth (a controlled direct effect in Model 1) increased 10% when estimated as a total effect. The risk ratio for alcohol abuse, biased due to an uncontrolled confounder in Model 1, was reduced by 23% when adjusted for drug abuse. The risk ratio for maternal education, solely a predictor of the outcome, was essentially unchanged. Reporting multiple effect estimates from a single model may lead to misinterpretation and lack of reproducibility. This example highlights the need for careful consideration of the types of effects estimated in statistical models. © 2018 John Wiley & Sons Ltd.
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Liu, Tianyi; Nie, Xiaolu; Wu, Zehao; Zhang, Ying; Feng, Guoshuang; Cai, Siyu; Lv, Yaqi; Peng, Xiaoxia
2017-12-29
Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis. We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders. Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding. The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind of bias into consideration when drawing conclusion based on summary estimation of meta-analyses.
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A bias-adjusted evidence synthesis of RCT and observational data: the case of total hip replacement.
Schnell-Inderst, Petra; Iglesias, Cynthia P; Arvandi, Marjan; Ciani, Oriana; Matteucci Gothe, Raffaella; Peters, Jaime; Blom, Ashley W; Taylor, Rod S; Siebert, Uwe
2017-02-01
Evaluation of clinical effectiveness of medical devices differs in some aspects from the evaluation of pharmaceuticals. One of the main challenges identified is lack of robust evidence and a will to make use of experimental and observational studies (OSs) in quantitative evidence synthesis accounting for internal and external biases. Using a case study of total hip replacement to compare the risk of revision of cemented and uncemented implant fixation modalities, we pooled treatment effect estimates from OS and RCTs, and simplified existing methods for bias-adjusted evidence synthesis to enhance practical application. We performed an elicitation exercise using methodological and clinical experts to determine the strength of beliefs about the magnitude of internal and external bias affecting estimates of treatment effect. We incorporated the bias-adjusted treatment effects into a generalized evidence synthesis, calculating both frequentist and Bayesian statistical models. We estimated relative risks as summary effect estimates with 95% confidence/credibility intervals to capture uncertainty. When we compared alternative approaches to synthesizing evidence, we found that the pooled effect size strongly depended on the inclusion of observational data as well as on the use bias-adjusted estimates. We demonstrated the feasibility of using observational studies in meta-analyses to complement RCTs and incorporate evidence from a wider spectrum of clinically relevant studies and healthcare settings. To ensure internal validity, OS data require sufficient correction for confounding and selection bias, either through study design and primary analysis, or by applying post-hoc bias adjustments to the results. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.
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Caetano, Raul; Mills, Britain A; Harris, T Robert
2012-01-01
This study was conducted to examine discrepancies in alcohol consumption estimates between a self-reported standard quantity-frequency measure and an adjusted version based on respondents' typically used container size. Using a multistage cluster sample design, 5,224 Hispanic individuals 18 years of age and older were selected from the household population in five metropolitan areas of the United States: Miami, New York, Philadelphia, Houston, and Los Angeles. The survey-weighted response rate was 76%. Personal interviews lasting an average of 1 hour were conducted in respondents' homes in either English or Spanish. The overall effect of container adjustment was to increase estimates of ethanol consumption by 68% for women (range across Hispanic groups: 17%-99%) and 30% for men (range: 14%-42%). With the exception of female Cuban American, Mexican American, and South/Central American beer drinkers and male Cuban American wine drinkers, all percentage differences between unadjusted and container-adjusted estimates were positive. Second, container adjustments produced the largest change for volume of distilled spirits, followed by wine and beer. Container size adjustments generally produced larger percentage increases in consumption estimates for the higher volume drinkers, especially the upper tertile of female drinkers. Self-reported alcohol consumption based on standard drinks underreports consumption when compared with reports based on the amount of alcohol poured into commonly used containers.
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Zou, W; Ouyang, H
2016-02-01
We propose a multiple estimation adjustment (MEA) method to correct effect overestimation due to selection bias from a hypothesis-generating study (HGS) in pharmacogenetics. MEA uses a hierarchical Bayesian approach to model individual effect estimates from maximal likelihood estimation (MLE) in a region jointly and shrinks them toward the regional effect. Unlike many methods that model a fixed selection scheme, MEA capitalizes on local multiplicity independent of selection. We compared mean square errors (MSEs) in simulated HGSs from naive MLE, MEA and a conditional likelihood adjustment (CLA) method that model threshold selection bias. We observed that MEA effectively reduced MSE from MLE on null effects with or without selection, and had a clear advantage over CLA on extreme MLE estimates from null effects under lenient threshold selection in small samples, which are common among 'top' associations from a pharmacogenetics HGS.
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Keogh, Ruth H; Daniel, Rhian M; VanderWeele, Tyler J; Vansteelandt, Stijn
2018-05-01
Estimation of causal effects of time-varying exposures using longitudinal data is a common problem in epidemiology. When there are time-varying confounders, which may include past outcomes, affected by prior exposure, standard regression methods can lead to bias. Methods such as inverse probability weighted estimation of marginal structural models have been developed to address this problem. However, in this paper we show how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates. We refer to the resulting estimation approach as sequential conditional mean models (SCMMs), which can be fitted using generalized estimating equations. We outline this approach and describe how including propensity score adjustment is advantageous. We compare the causal effects being estimated using SCMMs and marginal structural models, and we compare the two approaches using simulations. SCMMs enable more precise inferences, with greater robustness against model misspecification via propensity score adjustment, and easily accommodate continuous exposures and interactions. A new test for direct effects of past exposures on a subsequent outcome is described.
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Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States
ERIC Educational Resources Information Center
Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.
2007-01-01
Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…
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Latimer, Nicholas R; Abrams, Keith R; Amonkar, Mayur M; Stapelkamp, Ceilidh; Swann, R Suzanne
2015-07-01
Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48-1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, "treatment group" (assumes treatment effect could continue until death) and "on-treatment observed" (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE "treatment group" and "on-treatment observed" analyses performed similarly well. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching-a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Treatment switching is common in oncology trials, and the implications of this for the interpretation of the clinical effectiveness and cost-effectiveness of the novel treatment are important to consider. If patients who switch treatments benefit from the experimental treatment and a standard intention-to-treat analysis is conducted, the overall survival advantage associated with the new treatment could be underestimated. The present study applied established statistical methods to adjust for treatment switching in a trial that compared dabrafenib and dacarbazine for metastatic melanoma. The results showed that this led to a substantially increased estimate of the overall survival treatment effect associated with dabrafenib. ©AlphaMed Press.
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Abrams, Keith R.; Amonkar, Mayur M.; Stapelkamp, Ceilidh; Swann, R. Suzanne
2015-01-01
Background. Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48–1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Materials and Methods. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, “treatment group” (assumes treatment effect could continue until death) and “on-treatment observed” (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. Results. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE “treatment group” and “on-treatment observed” analyses performed similarly well. Conclusion. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching—a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Implications for Practice: Treatment switching is common in oncology trials, and the implications of this for the interpretation of the clinical effectiveness and cost-effectiveness of the novel treatment are important to consider. If patients who switch treatments benefit from the experimental treatment and a standard intention-to-treat analysis is conducted, the overall survival advantage associated with the new treatment could be underestimated. The present study applied established statistical methods to adjust for treatment switching in a trial that compared dabrafenib and dacarbazine for metastatic melanoma. The results showed that this led to a substantially increased estimate of the overall survival treatment effect associated with dabrafenib. PMID:26040620
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Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data
Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.
2014-01-01
In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438
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Crump, Kenny S; Van Landingham, Cynthia; Moolgavkar, Suresh H; McClellan, Roger
2015-01-01
The International Agency for Research on Cancer (IARC) in 2012 upgraded its hazard characterization of diesel engine exhaust (DEE) to “carcinogenic to humans.” The Diesel Exhaust in Miners Study (DEMS) cohort and nested case-control studies of lung cancer mortality in eight U.S. nonmetal mines were influential in IARC’s determination. We conducted a reanalysis of the DEMS case-control data to evaluate its suitability for quantitative risk assessment (QRA). Our reanalysis used conditional logistic regression and adjusted for cigarette smoking in a manner similar to the original DEMS analysis. However, we included additional estimates of DEE exposure and adjustment for radon exposure. In addition to applying three DEE exposure estimates developed by DEMS, we applied six alternative estimates. Without adjusting for radon, our results were similar to those in the original DEMS analysis: all but one of the nine DEE exposure estimates showed evidence of an association between DEE exposure and lung cancer mortality, with trend slopes differing only by about a factor of two. When exposure to radon was adjusted, the evidence for a DEE effect was greatly diminished, but was still present in some analyses that utilized the three original DEMS DEE exposure estimates. A DEE effect was not observed when the six alternative DEE exposure estimates were utilized and radon was adjusted. No consistent evidence of a DEE effect was found among miners who worked only underground. This article highlights some issues that should be addressed in any use of the DEMS data in developing a QRA for DEE. PMID:25857246
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Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan
2014-01-01
Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880
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Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne
2016-11-03
Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.
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Adjustment for reporting bias in network meta-analysis of antidepressant trials
2012-01-01
Background Network meta-analysis (NMA), a generalization of conventional MA, allows for assessing the relative effectiveness of multiple interventions. Reporting bias is a major threat to the validity of MA and NMA. Numerous methods are available to assess the robustness of MA results to reporting bias. We aimed to extend such methods to NMA. Methods We introduced 2 adjustment models for Bayesian NMA. First, we extended a meta-regression model that allows the effect size to depend on its standard error. Second, we used a selection model that estimates the propensity of trial results being published and in which trials with lower propensity are weighted up in the NMA model. Both models rely on the assumption that biases are exchangeable across the network. We applied the models to 2 networks of placebo-controlled trials of 12 antidepressants, with 74 trials in the US Food and Drug Administration (FDA) database but only 51 with published results. NMA and adjustment models were used to estimate the effects of the 12 drugs relative to placebo, the 66 effect sizes for all possible pair-wise comparisons between drugs, probabilities of being the best drug and ranking of drugs. We compared the results from the 2 adjustment models applied to published data and NMAs of published data and NMAs of FDA data, considered as representing the totality of the data. Results Both adjustment models showed reduced estimated effects for the 12 drugs relative to the placebo as compared with NMA of published data. Pair-wise effect sizes between drugs, probabilities of being the best drug and ranking of drugs were modified. Estimated drug effects relative to the placebo from both adjustment models were corrected (i.e., similar to those from NMA of FDA data) for some drugs but not others, which resulted in differences in pair-wise effect sizes between drugs and ranking. Conclusions In this case study, adjustment models showed that NMA of published data was not robust to reporting bias and provided estimates closer to that of NMA of FDA data, although not optimal. The validity of such methods depends on the number of trials in the network and the assumption that conventional MAs in the network share a common mean bias mechanism. PMID:23016799
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Uncertainty-based Estimation of the Secure Range for ISO New England Dynamic Interchange Adjustment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Etingov, Pavel V.; Makarov, Yuri V.; Wu, Di
2014-04-14
The paper proposes an approach to estimate the secure range for dynamic interchange adjustment, which assists system operators in scheduling the interchange with neighboring control areas. Uncertainties associated with various sources are incorporated. The proposed method is implemented in the dynamic interchange adjustment (DINA) tool developed by Pacific Northwest National Laboratory (PNNL) for ISO New England. Simulation results are used to validate the effectiveness of the proposed method.
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Mills, Britain A.; Harris, T. Robert
2012-01-01
Objective: This study was conducted to examine discrepancies in alcohol consumption estimates between a self-reported standard quantity—frequency measure and an adjusted version based on respondents’ typically used container size. Method: Using a multistage cluster sample design, 5,224 Hispanic individuals 18 years of age and older were selected from the household population in five metropolitan areas of the United States: Miami, New York, Philadelphia, Houston, and Los Angeles. The survey-weighted response rate was 76%. Personal interviews lasting an average of 1 hour were conducted in respondents’ homes in either English or Spanish. Results: The overall effect of container adjustment was to increase estimates of ethanol consumption by 68% for women (range across Hispanic groups: 17%–99%) and 30% for men (range: 14%–42%). With the exception of female Cuban American, Mexican American, and South/Central American beer drinkers and male Cuban American wine drinkers, all percentage differences between unadjusted and container-adjusted estimates were positive. Second, container adjustments produced the largest change for volume of distilled spirits, followed by wine and beer. Container size adjustments generally produced larger percentage increases in consumption estimates for the higher volume drinkers, especially the upper tertile of female drinkers. Conclusions: Self-reported alcohol consumption based on standard drinks underreports consumption when compared with reports based on the amount of alcohol poured into commonly used containers. PMID:22152669
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Moreno, Santiago G; Sutton, Alex J; Ades, A E; Cooper, Nicola J; Abrams, Keith R
2011-11-01
To extend, apply, and evaluate a regression-based approach to adjusting meta-analysis for publication and related biases. The approach uses related meta-analyses to improve estimation by borrowing strength on the degree of bias. The proposed adjustment approach is described. Adjustments are applied both independently and by borrowing strength across journal-extracted data on the effectiveness of 12 antidepressant drugs from placebo-controlled trials. The methods are also applied to Food and Drug Administration (FDA) data obtained on the same 12 drugs. Results are compared, viewing the FDA observed data as gold standard. Estimates adjusted for publication biases made independently for each drug were very uncertain using both the journal and FDA data. Adjusted estimates were much more precise when borrowing strength across meta-analyses. Reassuringly, adjustments in this way made to the journal data agreed closely with the observed estimates from the FDA data, while the adjusted FDA results changed only minimally from those observed from the FDA data. The method worked well in the case study considered and therefore further evaluation is encouraged. It is suggested that this approach may be especially useful when adjusting several meta-analyses on similar interventions and outcomes, particularly when there are small numbers of studies. Copyright © 2011 Elsevier Inc. All rights reserved.
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Estimation of health effects of prenatal methylmercury exposure using structural equation models.
Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe; Weihe, Pal
2002-10-14
Observational studies in epidemiology always involve concerns regarding validity, especially measurement error, confounding, missing data, and other problems that may affect the study outcomes. Widely used standard statistical techniques, such as multiple regression analysis, may to some extent adjust for these shortcomings. However, structural equations may incorporate most of these considerations, thereby providing overall adjusted estimations of associations. This approach was used in a large epidemiological data set from a prospective study of developmental methyl-mercury toxicity. Structural equation models were developed for assessment of the association between biomarkers of prenatal mercury exposure and neuropsychological test scores in 7 year old children. Eleven neurobehavioral outcomes were grouped into motor function and verbally mediated function. Adjustment for local dependence and item bias was necessary for a satisfactory fit of the model, but had little impact on the estimated mercury effects. The mercury effect on the two latent neurobehavioral functions was similar to the strongest effects seen for individual test scores of motor function and verbal skills. Adjustment for contaminant exposure to poly chlorinated biphenyls (PCBs) changed the estimates only marginally, but the mercury effect could be reduced to non-significance by assuming a large measurement error for the PCB biomarker. The structural equation analysis allows correction for measurement error in exposure variables, incorporation of multiple outcomes and incomplete cases. This approach therefore deserves to be applied more frequently in the analysis of complex epidemiological data sets.
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NASA Astrophysics Data System (ADS)
Karbalaee, Negar; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan
2017-04-01
This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the Integrated Multisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained.
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Mogasale, Vittal; Maskery, Brian; Ochiai, R Leon; Lee, Jung Seok; Mogasale, Vijayalaxmi V; Ramani, Enusa; Kim, Young Eun; Park, Jin Kyung; Wierzba, Thomas F
2014-10-01
No access to safe water is an important risk factor for typhoid fever, yet risk-level heterogeneity is unaccounted for in previous global burden estimates. Since WHO has recommended risk-based use of typhoid polysaccharide vaccine, we revisited the burden of typhoid fever in low-income and middle-income countries (LMICs) after adjusting for water-related risk. We estimated the typhoid disease burden from studies done in LMICs based on blood-culture-confirmed incidence rates applied to the 2010 population, after correcting for operational issues related to surveillance, limitations of diagnostic tests, and water-related risk. We derived incidence estimates, correction factors, and mortality estimates from systematic literature reviews. We did scenario analyses for risk factors, diagnostic sensitivity, and case fatality rates, accounting for the uncertainty in these estimates and we compared them with previous disease burden estimates. The estimated number of typhoid fever cases in LMICs in 2010 after adjusting for water-related risk was 11·9 million (95% CI 9·9-14·7) cases with 129 000 (75 000-208 000) deaths. By comparison, the estimated risk-unadjusted burden was 20·6 million (17·5-24·2) cases and 223 000 (131 000-344 000) deaths. Scenario analyses indicated that the risk-factor adjustment and updated diagnostic test correction factor derived from systematic literature reviews were the drivers of differences between the current estimate and past estimates. The risk-adjusted typhoid fever burden estimate was more conservative than previous estimates. However, by distinguishing the risk differences, it will allow assessment of the effect at the population level and will facilitate cost-effectiveness calculations for risk-based vaccination strategies for future typhoid conjugate vaccine. Copyright © 2014 Mogasale et al. Open Access article distributed under the terms of CC BY-NC-SA. Published by .. All rights reserved.
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Alonso, Jordi; Vilagut, Gemma; Chatterji, Somnath; Heeringa, Steven; Schoenbaum, Michael; Üstün, T. Bedirhan; Rojas-Farreras, Sonia; Angermeyer, Matthias; Bromet, Evelyn; Bruffaerts, Ronny; de Girolamo, Giovanni; Gureje, Oye; Haro, Josep Maria; Karam, Aimee N.; Kovess, Viviane; Levinson, Daphna; Liu, Zhaorui; Mora, Maria Elena Medina; Ormel, J.; Posada-Villa, Jose; Uda, Hidenori; Kessler, Ronald C.
2010-01-01
Background The methodology commonly used to estimate disease burden, featuring ratings of severity of individual conditions, has been criticized for ignoring comorbidity. A methodology that addresses this problem is proposed and illustrated here with data from the WHO World Mental Health Surveys. Although the analysis is based on self-reports about one’s own conditions in a community survey, the logic applies equally well to analysis of hypothetical vignettes describing comorbid condition profiles. Methods Face-to-face interviews in 13 countries (six developing, nine developed; n = 31,067; response rate = 69.6%) assessed 10 classes of chronic physical and 9 of mental conditions. A visual analog scale (VAS) was used to assess overall perceived health. Multiple regression analysis with interactions for comorbidity was used to estimate associations of conditions with VAS. Simulation was used to estimate condition-specific effects. Results The best-fitting model included condition main effects and interactions of types by numbers of conditions. Neurological conditions, insomnia, and major depression were rated most severe. Adjustment for comorbidity reduced condition-specific estimates with substantial between-condition variation (.24–.70 ratios of condition-specific estimates with and without adjustment for comorbidity). The societal-level burden rankings were quite different from the individual-level rankings, with the highest societal-level rankings associated with conditions having high prevalence rather than high individual-level severity. Conclusions Plausible estimates of disorder-specific effects on VAS can be obtained using methods that adjust for comorbidity. These adjustments substantially influence condition-specific ratings. PMID:20553636
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Mayer, M L; Rozier, R G
2000-08-01
This analysis questions the appropriateness of inflation adjustment in analyses of provider behavior by comparing results from estimations using adjusted financial variables with those from estimations using unadjusted financial variables. Using Medicaid claims from 1984-1991, we explored the effects of Medicaid reimbursement increases on dentists' participation. Using results from inflation adjusted analyses, we would conclude that a 23% nominal increase in Medicaid reimbursement rates yields no increase in the number of Medicaid children seen by dentists. In contrast, estimations based on unadjusted reimbursement rates suggest that this same 23% nominal increase in reimbursement leads to an expected 16-person (15.4%) increase in the number of Medicaid patients seen per provider per year. These analyses demonstrate that results are sensitive to adjustment for inflation. While adjusting for inflation is a generally accepted practice in health services research, doing so without evidence that providers respond to adjusted reimbursement may be unjustified. More research is needed to determine the appropriateness of inflation adjustment in analyses of provider behavior, and the circumstances under which it should or should not be done.
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Cost-effectiveness of aortic valve replacement in the elderly: an introductory study.
Wu, YingXing; Jin, Ruyun; Gao, Guangqiang; Grunkemeier, Gary L; Starr, Albert
2007-03-01
With increased life expectancy and improved technology, valve replacement is being offered to increasing numbers of elderly patients with satisfactory clinical results. By using standard econometric techniques, we estimated the relative cost-effectiveness of aortic valve replacement by drawing on a large prospective database at our institution. By using aortic valve replacement as an example, this introductory report paves the way to more definitive studies of these issues in the future. From 1961 to 2003, 4617 adult patients underwent aortic valve replacement at our service. These patients were provided with a prospective lifetime follow-up. As of 2005, these patients had accumulated 31,671 patient-years of follow-up (maximum 41 years) and had returned 22,396 yearly questionnaires. A statistical model was used to estimate the future life years of patients who are currently alive. In the absence of direct estimates of utility, quality-adjusted life years were estimated from New York Heart Association class. The cost-effectiveness ratio was calculated by the patient's age at surgery. The overall cost-effectiveness ratio was approximately 13,528 dollars per quality-adjusted life year gained. The cost-effectiveness ratio increased according to age at surgery, up to 19,826 dollars per quality-adjusted life year for octogenarians and 27,182 dollars per quality-adjusted life year for nonagenarians. Given the limited scope of this introductory study, aortic valve replacement is cost-effective for all age groups and is very cost-effective for all but the most elderly according to standard econometric rules of thumb.
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Johnson, Brent A
2009-10-01
We consider estimation and variable selection in the partial linear model for censored data. The partial linear model for censored data is a direct extension of the accelerated failure time model, the latter of which is a very important alternative model to the proportional hazards model. We extend rank-based lasso-type estimators to a model that may contain nonlinear effects. Variable selection in such partial linear model has direct application to high-dimensional survival analyses that attempt to adjust for clinical predictors. In the microarray setting, previous methods can adjust for other clinical predictors by assuming that clinical and gene expression data enter the model linearly in the same fashion. Here, we select important variables after adjusting for prognostic clinical variables but the clinical effects are assumed nonlinear. Our estimator is based on stratification and can be extended naturally to account for multiple nonlinear effects. We illustrate the utility of our method through simulation studies and application to the Wisconsin prognostic breast cancer data set.
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Causal Methods for Observational Research: A Primer.
Almasi-Hashiani, Amir; Nedjat, Saharnaz; Mansournia, Mohammad Ali
2018-04-01
The goal of many observational studies is to estimate the causal effect of an exposure on an outcome after adjustment for confounders, but there are still some serious errors in adjusting confounders in clinical journals. Standard regression modeling (e.g., ordinary logistic regression) fails to estimate the average effect of exposure in total population in the presence of interaction between exposure and covariates, and also cannot adjust for time-varying confounding appropriately. Moreover, stepwise algorithms of the selection of confounders based on P values may miss important confounders and lead to bias in effect estimates. Causal methods overcome these limitations. We illustrate three causal methods including inverse-probability-of-treatment-weighting (IPTW) and parametric g-formula, with an emphasis on a clever combination of these 2 methods: targeted maximum likelihood estimation (TMLE) which enjoys a double-robust property against bias. © 2018 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Tang, Yongqiang
2017-12-01
Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.
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Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.
Nixon, R M; Thompson, S G
2003-09-15
Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.
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Lee, Paul H
2017-06-01
Some confounders are nonlinearly associated with dependent variables, but they are often adjusted using a linear term. The purpose of this study was to examine the error of mis-specifying the nonlinear confounding effect. We carried out a simulation study to investigate the effect of adjusting for a nonlinear confounder in the estimation of a causal relationship between the exposure and outcome in 3 ways: using a linear term, binning into 5 equal-size categories, or using a restricted cubic spline of the confounder. Continuous, binary, and survival outcomes were simulated. We examined the confounder across varying measurement error. In addition, we performed a real data analysis examining the 3 strategies to handle the nonlinear effects of accelerometer-measured physical activity in the National Health and Nutrition Examination Survey 2003-2006 data. The mis-specification of a nonlinear confounder had little impact on causal effect estimation for continuous outcomes. For binary and survival outcomes, this mis-specification introduced bias, which could be eliminated using spline adjustment only when there is small measurement error of the confounder. Real data analysis showed that the associations between high blood pressure, high cholesterol, and diabetes and mortality adjusted for physical activity with restricted cubic spline were about 3% to 11% larger than their counterparts adjusted with a linear term. For continuous outcomes, confounders with nonlinear effects can be adjusting with a linear term. Spline adjustment should be used for binary and survival outcomes on confounders with small measurement error.
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Overcoming bias in estimating the volume-outcome relationship.
Tsai, Alexander C; Votruba, Mark; Bridges, John F P; Cebul, Randall D
2006-02-01
To examine the effect of hospital volume on 30-day mortality for patients with congestive heart failure (CHF) using administrative and clinical data in conventional regression and instrumental variables (IV) estimation models. The primary data consisted of longitudinal information on comorbid conditions, vital signs, clinical status, and laboratory test results for 21,555 Medicare-insured patients aged 65 years and older hospitalized for CHF in northeast Ohio in 1991-1997. The patient was the primary unit of analysis. We fit a linear probability model to the data to assess the effects of hospital volume on patient mortality within 30 days of admission. Both administrative and clinical data elements were included for risk adjustment. Linear distances between patients and hospitals were used to construct the instrument, which was then used to assess the endogeneity of hospital volume. When only administrative data elements were included in the risk adjustment model, the estimated volume-outcome effect was statistically significant (p=.029) but small in magnitude. The estimate was markedly attenuated in magnitude and statistical significance when clinical data were added to the model as risk adjusters (p=.39). IV estimation shifted the estimate in a direction consistent with selective referral, but we were unable to reject the consistency of the linear probability estimates. Use of only administrative data for volume-outcomes research may generate spurious findings. The IV analysis further suggests that conventional estimates of the volume-outcome relationship may be contaminated by selective referral effects. Taken together, our results suggest that efforts to concentrate hospital-based CHF care in high-volume hospitals may not reduce mortality among elderly patients.
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Vrabel, Joseph; Teeple, Andrew; Kress, Wade H.
2009-01-01
With increasing demands for reliable water supplies and availability estimates, groundwater flow models often are developed to enhance understanding of surface-water and groundwater systems. Specific hydraulic variables must be known or calibrated for the groundwater-flow model to accurately simulate current or future conditions. Surface geophysical surveys, along with selected test-hole information, can provide an integrated framework for quantifying hydrogeologic conditions within a defined area. In 2004, the U.S. Geological Survey, in cooperation with the North Platte Natural Resources District, performed a surface geophysical survey using a capacitively coupled resistivity technique to map the lithology within the top 8 meters of the near-surface for 110 kilometers of the Interstate and Tri-State Canals in western Nebraska and eastern Wyoming. Assuming that leakage between the surface-water and groundwater systems is affected primarily by the sediment directly underlying the canal bed, leakage potential was estimated from the simple vertical mean of inverse-model resistivity values for depth levels with geometrically increasing layer thickness with depth which resulted in mean-resistivity values biased towards the surface. This method generally produced reliable results, but an improved analysis method was needed to account for situations where confining units, composed of less permeable material, underlie units with greater permeability. In this report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, the authors use geostatistical analysis to develop the minimum-unadjusted method to compute a relative leakage potential based on the minimum resistivity value in a vertical column of the resistivity model. The minimum-unadjusted method considers the effects of homogeneous confining units. The minimum-adjusted method also is developed to incorporate the effect of local lithologic heterogeneity on water transmission. Seven sites with differing geologic contexts were selected following review of the capacitively coupled resistivity data collected in 2004. A reevaluation of these sites using the mean, minimum-unadjusted, and minimum-adjusted methods was performed to compare the different approaches for estimating leakage potential. Five of the seven sites contained underlying confining units, for which the minimum-unadjusted and minimum-adjusted methods accounted for the confining-unit effect. Estimates of overall leakage potential were lower for the minimum-unadjusted and minimum-adjusted methods than those estimated by the mean method. For most sites, the local heterogeneity adjustment procedure of the minimum-adjusted method resulted in slightly larger overall leakage-potential estimates. In contrast to the mean method, the two minimum-based methods allowed the least permeable areas to control the overall vertical permeability of the subsurface. The minimum-adjusted method refined leakage-potential estimation by additionally including local lithologic heterogeneity effects.
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Panel Estimates of Male-Female Earnings Functions.
ERIC Educational Resources Information Center
Kim, Moon-Kak; Polachek, Solomon W.
1994-01-01
Application of single and simultaneous equation fixed-effects and random-effects shows that earnings appreciation with experience and depreciation with labor market interruptions are comparable for men and women. Adjusting for heterogeneity reduces the wage gap to 20%; adjusting for endogeneity reduces it nearly to zero. (SK)
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A clinical economics workstation for risk-adjusted health care cost management.
Eisenstein, E. L.; Hales, J. W.
1995-01-01
This paper describes a healthcare cost accounting system which is under development at Duke University Medical Center. Our approach differs from current practice in that this system will dynamically adjust its resource usage estimates to compensate for variations in patient risk levels. This adjustment is made possible by introducing a new cost accounting concept, Risk-Adjusted Quantity (RQ). RQ divides case-level resource usage variances into their risk-based component (resource consumption differences attributable to differences in patient risk levels) and their non-risk-based component (resource consumption differences which cannot be attributed to differences in patient risk levels). Because patient risk level is a factor in estimating resource usage, this system is able to simultaneously address the financial and quality dimensions of case cost management. In effect, cost-effectiveness analysis is incorporated into health care cost management. PMID:8563361
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Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles
Lane, Kevin J; Levy, Jonathan I; Scammell, Madeleine Kangsen; Patton, Allison P; Durant, John L; Mwamburi, Mkaya; Zamore, Wig; Brugge, Doug
2015-01-01
Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time. PMID:25827314
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Krol, Marieke; Brouwer, Werner B F; Severens, Johan L; Kaper, Janneke; Evers, Silvia M A A
2012-12-01
Productivity costs related to paid work are commonly calculated in economic evaluations of health technologies by multiplying the relevant number of work days lost with a wage rate estimate. It has been argued that actual productivity costs may either be lower or higher than current estimates due to compensation mechanisms and/or multiplier effects (related to team dependency and problems with finding good substitutes in cases of absenteeism). Empirical evidence on such mechanisms and their impact on productivity costs is scarce, however. This study aims to increase knowledge on how diminished productivity is compensated within firms. Moreover, it aims to explore how compensation and multiplier effects potentially affect productivity cost estimates. Absenteeism and compensation mechanisms were measured in a randomized trial among Dutch citizens examining the cost-effectiveness of reimbursement for smoking cessation treatment. Multiplier effects were extracted from published literature. Productivity costs were calculated applying the Friction Cost Approach. Regular estimates were subsequently adjusted for (i) compensation during regular working hours, (ii) job dependent multipliers and (iii) both compensation and multiplier effects. A total of 187 respondents included in the trial were useful for inclusion in this study, based on being in paid employment, having experienced absenteeism in the preceding six months and completing the questionnaire on absenteeism and compensation mechanisms. Over half of these respondents stated that their absenteeism was compensated during normal working hours by themselves or colleagues. Only counting productivity costs not compensated in regular working hours reduced the traditional estimate by 57%. Correcting for multiplier effects increased regular estimates by a quarter. Combining both impacts decreased traditional estimates by 29%. To conclude, large amounts of lost production are compensated in normal hours. Productivity costs estimates are strongly influenced by adjustment for compensation mechanisms and multiplier effects. The validity of such adjustments needs further examination, however. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Zhang, Ke; Jiang, Bin; Shi, Peng
2017-02-01
In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H ∞ and H 2 with pole placement, multiconstrained design is given to calculate the gain of DFEO. Finally, simulation results are presented to illustrate the feasibility and effectiveness of the proposed DFEO design with AP.
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Cost-effectiveness of biological treatment sequences for fistulising Crohn’s disease across Europe
Baji, Petra; Gulácsi, László; Brodszky, Valentin; Végh, Zsuzsanna; Danese, Silvio; Irving, Peter M; Peyrin-Biroulet, Laurent; Schreiber, Stefan; Rencz, Fanni; Lakatos, Péter L; Péntek, Márta
2017-01-01
Background In clinical practice, treatment sequences of biologicals are applied for active fistulising Crohn’s disease, however underlying health economic analyses are lacking. Objective The purpose of this study was to analyse the cost-effectiveness of different biological sequences including infliximab, biosimilar-infliximab, adalimumab and vedolizumab in nine European countries. Methods A Markov model was developed to compare treatment sequences of one, two and three biologicals from the payer’s perspective on a five-year time horizon. Data on effectiveness and health state utilities were obtained from the literature. Country-specific costs were considered. Calculations were performed with both official list prices and estimated real prices of biologicals. Results Biosimilar-infliximab is the most cost-effective treatment against standard care across the countries (with list prices: €34684–€72551/quality adjusted life year; with estimated real prices: €24364–€56086/quality adjusted life year). The most cost-effective two-agent sequence, except for Germany, is the biosimilar-infliximab–adalimumab therapy compared with single biosimilar-infliximab (with list prices: €58533–€133831/quality adjusted life year; with estimated prices: €45513–€105875/quality adjusted life year). The cost-effectiveness of the biosimilar-infliximab–adalimumab–vedolizumab three-agent sequence compared wit biosimilar-infliximab –adalimumab is €87214–€152901/quality adjusted life year. Conclusions The suggested first-choice biological treatment is biosimilar-infliximab. In case of treatment failure, switching to adalimumab then to vedolizumab provides meaningful additional health gains but at increased costs. Inter-country differences in cost-effectiveness are remarkable due to significant differences in costs. PMID:29511561
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Assessing mediation using marginal structural models in the presence of confounding and moderation
Coffman, Donna L.; Zhong, Wei
2012-01-01
This paper presents marginal structural models (MSMs) with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW can be used to take confounding into account, but IPW has several advantages. Regression adjustment of even one confounder of the mediator and outcome that has been influenced by treatment results in biased estimates of the direct effect (i.e., the effect of treatment on the outcome that does not go through the mediator). One advantage of IPW is that it can properly adjust for this type of confounding, assuming there are no unmeasured confounders. Further, we illustrate that IPW estimation provides unbiased estimates of all effects when there is a baseline moderator variable that interacts with the treatment, when there is a baseline moderator variable that interacts with the mediator, and when the treatment interacts with the mediator. IPW estimation also provides unbiased estimates of all effects in the presence of non-randomized treatments. In addition, for testing mediation we propose a test of the null hypothesis of no mediation. Finally, we illustrate this approach with an empirical data set in which the mediator is continuous, as is often the case in psychological research. PMID:22905648
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Assessing mediation using marginal structural models in the presence of confounding and moderation.
Coffman, Donna L; Zhong, Wei
2012-12-01
This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW can be used to take confounding into account, but IPW has several advantages. Regression adjustment of even one confounder of the mediator and outcome that has been influenced by treatment results in biased estimates of the direct effect (i.e., the effect of treatment on the outcome that does not go through the mediator). One advantage of IPW is that it can properly adjust for this type of confounding, assuming there are no unmeasured confounders. Further, we illustrate that IPW estimation provides unbiased estimates of all effects when there is a baseline moderator variable that interacts with the treatment, when there is a baseline moderator variable that interacts with the mediator, and when the treatment interacts with the mediator. IPW estimation also provides unbiased estimates of all effects in the presence of nonrandomized treatments. In addition, for testing mediation we propose a test of the null hypothesis of no mediation. Finally, we illustrate this approach with an empirical data set in which the mediator is continuous, as is often the case in psychological research. PsycINFO Database Record (c) 2013 APA, all rights reserved.
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Killewald, Alexandra; García-Manglano, Javier
2016-11-01
Prior research on parenthood effects has typically used single-sex models and estimated average effects. By contrast, we estimate population-level variability in partners' changes in housework hours, paid work hours, occupation traits, and wages after becoming parents, and we explore whether one partner's adjustment offsets or supplements the other's. We find tradeoffs between spouses on paid work adjustments to parenthood, but complementarity in adjustments to housework hours, occupation traits, and wages. The effect of parenthood on wives' behaviors is larger and more variable than on husbands' behaviors in every domain. The modest variation between husbands in work responses to parenthood explains little of the variation in the motherhood penalty, while variation in wives' own behaviors plays a larger role. We refer to this pattern as tethered autonomy: variation across American couples in work responses to parenthood is shaped primarily by variation in wives' adjustments, while husbands' work acts largely as a fixed point. Copyright © 2016 Elsevier Inc. All rights reserved.
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Fenwick, Elisabeth; Marshall, Deborah A; Blackhouse, Gordon; Vidaillet, Humberto; Slee, April; Shemanski, Lynn; Levy, Adrian R
2008-01-01
Losses to follow-up and administrative censoring can cloud the interpretation of trial-based economic evaluations. A number of investigators have examined the impact of different levels of adjustment for censoring, including nonadjustment, adjustment of effects only, and adjustment for both costs and effects. Nevertheless, there is a lack of research on the impact of censoring on decision-making. The objective of this study was to estimate the impact of adjustment for censoring on the interpretation of cost-effectiveness results and expected value of perfect information (EVPI), using a trial-based analysis that compared rate- and rhythm-control treatments for persons with atrial fibrillation. Three different levels of adjustment for censoring were examined: no censoring of cost and effects, censoring of effects only, and censoring of both costs and effects. In each case, bootstrapping was used to estimate the uncertainty incosts and effects, and the EVPI was calculated to determine the potential worth of further research. Censoring did not impact the adoption decision. Nevertheless, this was not the case for the decision uncertainty or the EVPI. For a threshold of $50,000 per life-year, the EVPI varied between $626,000 (partial censoring) to $117 million (full censoring) for the eligible US population. The level of adjustment for censoring in trial-based cost-effectiveness analyses can impact on the decisions to fund a new technology and to devote resources for further research. Only when censoring is taken into account for both costs and effects are these decisions appropriately addressed.
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Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.; Phuyal, Khem P.; Ji, Lei
2013-01-01
In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVIsat_adjust) based on RVI was developed. A 10-year (2000–2009) NDVIsat_adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CPnon_sat_adjust, CPsat_adjust) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CPsat_adjust and the NASS average corn yield data (r = 0.78, 113 samples) is stronger than the relationship between CPnon_sat_adjust and the NASS average corn yield data (r = 0.67, 113 samples), indicating that the new CPsat_adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.
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Sobel, Michael E; Lindquist, Martin A
2014-07-01
Functional magnetic resonance imaging (fMRI) has facilitated major advances in understanding human brain function. Neuroscientists are interested in using fMRI to study the effects of external stimuli on brain activity and causal relationships among brain regions, but have not stated what is meant by causation or defined the effects they purport to estimate. Building on Rubin's causal model, we construct a framework for causal inference using blood oxygenation level dependent (BOLD) fMRI time series data. In the usual statistical literature on causal inference, potential outcomes, assumed to be measured without systematic error, are used to define unit and average causal effects. However, in general the potential BOLD responses are measured with stimulus dependent systematic error. Thus we define unit and average causal effects that are free of systematic error. In contrast to the usual case of a randomized experiment where adjustment for intermediate outcomes leads to biased estimates of treatment effects (Rosenbaum, 1984), here the failure to adjust for task dependent systematic error leads to biased estimates. We therefore adjust for systematic error using measured "noise covariates" , using a linear mixed model to estimate the effects and the systematic error. Our results are important for neuroscientists, who typically do not adjust for systematic error. They should also prove useful to researchers in other areas where responses are measured with error and in fields where large amounts of data are collected on relatively few subjects. To illustrate our approach, we re-analyze data from a social evaluative threat task, comparing the findings with results that ignore systematic error.
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Selmer, Randi; Haglund, Bengt; Furu, Kari; Andersen, Morten; Nørgaard, Mette; Zoëga, Helga; Kieler, Helle
2016-10-01
Compare analyses of a pooled data set on the individual level with aggregate meta-analysis in a multi-database study. We reanalysed data on 2.3 million births in a Nordic register based cohort study. We compared estimated odds ratios (OR) for the effect of selective serotonin reuptake inhibitors (SSRI) and venlafaxine use in pregnancy on any cardiovascular birth defect and the rare outcome right ventricular outflow tract obstructions (RVOTO). Common covariates included maternal age, calendar year, birth order, maternal diabetes, and co-medication. Additional covariates were added in analyses with country-optimized adjustment. Country adjusted OR (95%CI) for any cardiovascular birth defect in the individual-based pooled analysis was 1.27 (1.17-1.39), 1.17 (1.07-1.27) adjusted for common covariates and 1.15 (1.05-1.26) adjusted for all covariates. In fixed effects meta-analyses pooled OR was 1.29 (1.19-1.41) based on crude country specific ORs, 1.19 (1.09-1.29) adjusted for common covariates, and 1.16 (1.06-1.27) for country-optimized adjustment. In a random effects model the adjusted OR was 1.07 (0.87-1.32). For RVOTO, OR was 1.48 (1.15-1.89) adjusted for all covariates in the pooled data set, and 1.53 (1.19-1.96) after country-optimized adjustment. Country-specific adjusted analyses at the substance level were not possible for RVOTO. Results of fixed effects meta-analysis and individual-based analyses of a pooled dataset were similar in this study on the association of SSRI/venlafaxine and cardiovascular birth defects. Country-optimized adjustment attenuated the estimates more than adjustment for common covariates only. When data are sparse pooled data on the individual level are needed for adjusted analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Neighbors, Charles J; Barnett, Nancy P; Rohsenow, Damaris J; Colby, Suzanne M; Monti, Peter M
2010-05-01
Brief interventions in the emergency department targeting risk-taking youth show promise to reduce alcohol-related injury. This study models the cost-effectiveness of a motivational interviewing-based intervention relative to brief advice to stop alcohol-related risk behaviors (standard care). Average cost-effectiveness ratios were compared between conditions. In addition, a cost-utility analysis examined the incremental cost of motivational interviewing per quality-adjusted life year gained. Microcosting methods were used to estimate marginal costs of motivational interviewing and standard care as well as two methods of patient screening: standard emergency-department staff questioning and proactive outreach by counseling staff. Average cost-effectiveness ratios were computed for drinking and driving, injuries, vehicular citations, and negative social consequences. Using estimates of the marginal effect of motivational interviewing in reducing drinking and driving, estimates of traffic fatality risk from drinking-and-driving youth, and national life tables, the societal costs per quality-adjusted life year saved by motivational interviewing relative to standard care were also estimated. Alcohol-attributable traffic fatality risks were estimated using national databases. Intervention costs per participant were $81 for standard care, $170 for motivational interviewing with standard screening, and $173 for motivational interviewing with proactive screening. The cost-effectiveness ratios for motivational interviewing were more favorable than standard care across all study outcomes and better for men than women. The societal cost per quality-adjusted life year of motivational interviewing was $8,795. Sensitivity analyses indicated that results were robust in terms of variability in parameter estimates. This brief intervention represents a good societal investment compared with other commonly adopted medical interventions.
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Kennedy, Jeffrey R.; Paretti, Nicholas V.
2014-01-01
Flooding in urban areas routinely causes severe damage to property and often results in loss of life. To investigate the effect of urbanization on the magnitude and frequency of flood peaks, a flood frequency analysis was carried out using data from urbanized streamgaging stations in Phoenix and Tucson, Arizona. Flood peaks at each station were predicted using the log-Pearson Type III distribution, fitted using the expected moments algorithm and the multiple Grubbs-Beck low outlier test. The station estimates were then compared to flood peaks estimated by rural-regression equations for Arizona, and to flood peaks adjusted for urbanization using a previously developed procedure for adjusting U.S. Geological Survey rural regression peak discharges in an urban setting. Only smaller, more common flood peaks at the 50-, 20-, 10-, and 4-percent annual exceedance probabilities (AEPs) demonstrate any increase in magnitude as a result of urbanization; the 1-, 0.5-, and 0.2-percent AEP flood estimates are predicted without bias by the rural-regression equations. Percent imperviousness was determined not to account for the difference in estimated flood peaks between stations, either when adjusting the rural-regression equations or when deriving urban-regression equations to predict flood peaks directly from basin characteristics. Comparison with urban adjustment equations indicates that flood peaks are systematically overestimated if the rural-regression-estimated flood peaks are adjusted upward to account for urbanization. At nearly every streamgaging station in the analysis, adjusted rural-regression estimates were greater than the estimates derived using station data. One likely reason for the lack of increase in flood peaks with urbanization is the presence of significant stormwater retention and detention structures within the watershed used in the study.
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42 CFR 412.525 - Adjustments to the Federal prospective payment.
Code of Federal Regulations, 2010 CFR
2010-10-01
... its estimated costs for a patient exceed the adjusted LTC-MS-DRG payment plus a fixed-loss amount. For...-DRG relative weights that are in effect at the start of the applicable long-term care hospital...
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Time variation of effective climate sensitivity in GCMs
NASA Astrophysics Data System (ADS)
Williams, K. D.; Ingram, W. J.; Gregory, J. M.
2009-04-01
Effective climate sensitivity is often assumed to be constant (if uncertain), but some previous studies of General Circulation Model (GCM) simulations have found it varying as the simulation progresses. This complicates the fitting of simple models to such simulations, as well as having implications for the estimation of climate sensitivity from observations. This study examines the evolution of the feedbacks determining the climate sensitivity in GCMs submitted to the Coupled Model Intercomparison Project. Apparent centennial-timescale variations of effective climate sensitivity during stabilisation to a forcing can be considered an artefact of using conventional forcings which only allow for instantaneous effects and stratospheric adjustment. If the forcing is adjusted for processes occurring on timescales which are short compared to the climate stabilisation timescale then there is little centennial timescale evolution of effective climate sensitivity in any of the GCMs. We suggest that much of the apparent variation in effective climate sensitivity identified in previous studies is actually due to the comparatively fast forcing adjustment. Persistent differences are found in the strength of the feedbacks between the coupled atmosphere - ocean (AO) versions and their atmosphere - mixed-layer ocean (AML) counterparts, (the latter are often assumed to give the equilibrium climate sensitivity of the AOGCM). The AML model can typically only estimate the equilibrium climate sensitivity of the parallel AO version to within about 0.5K. The adjustment to the forcing to account for comparatively fast processes varies in magnitude and sign between GCMs, as well as differing between AO and AML versions of the same model. There is evidence from one AOGCM that the forcing adjustment may take a couple of decades, with implications for observationally based estimates of equilibrium climate sensitivity. We suggest that at least some of the spread in 21st century global temperature predictions between GCMs is due to differing adjustment processes, hence work to understand these differences should be a priority.
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Austin, Peter C; Manca, Andrea; Zwarenstein, Merrick; Juurlink, David N; Stanbrook, Matthew B
2010-02-01
Statisticians have criticized the use of significance testing to compare the distribution of baseline covariates between treatment groups in randomized controlled trials (RCTs). Furthermore, some have advocated for the use of regression adjustment to estimate the effect of treatment after adjusting for potential imbalances in prognostically important baseline covariates between treatment groups. We examined 114 RCTs published in the New England Journal of Medicine, the Journal of the American Medical Association, The Lancet, and the British Medical Journal between January 1, 2007 and June 30, 2007. Significance testing was used to compare baseline characteristics between treatment arms in 38% of the studies. The practice was very rare in British journals and more common in the U.S. journals. In 29% of the studies, the primary outcome was continuous, whereas in 65% of the studies, the primary outcome was either dichotomous or time-to-event in nature. Adjustment for baseline covariates was reported when estimating the treatment effect in 34% of the studies. Our findings suggest the need for greater editorial consistency across journals in the reporting of RCTs. Furthermore, there is a need for greater debate about the relative merits of unadjusted vs. adjusted estimates of treatment effect. Copyright 2010 Elsevier Inc. All rights reserved.
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Coherent Power Analysis in Multi-Level Studies Using Design Parameters from Surveys
ERIC Educational Resources Information Center
Rhoads, Christopher
2016-01-01
Current practice for conducting power analyses in hierarchical trials using survey based ICC and effect size estimates may be misestimating power because ICCs are not being adjusted to account for treatment effect heterogeneity. Results presented in Table 1 show that the necessary adjustments can be quite large or quite small. Furthermore, power…
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Berger, Lawrence M; Bruch, Sarah K; Johnson, Elizabeth I; James, Sigrid; Rubin, David
2009-01-01
This study used data on 2,453 children aged 4-17 from the National Survey of Child and Adolescent Well-Being and 5 analytic methods that adjust for selection factors to estimate the impact of out-of-home placement on children's cognitive skills and behavior problems. Methods included ordinary least squares (OLS) regressions and residualized change, simple change, difference-in-difference, and fixed effects models. Models were estimated using the full sample and a matched sample generated by propensity scoring. Although results from the unmatched OLS and residualized change models suggested that out-of-home placement is associated with increased child behavior problems, estimates from models that more rigorously adjust for selection bias indicated that placement has little effect on children's cognitive skills or behavior problems.
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Treatment strategies for pelvic organ prolapse: a cost-effectiveness analysis.
Hullfish, Kathie L; Trowbridge, Elisa R; Stukenborg, George J
2011-05-01
To compare the relative cost effectiveness of treatment decision alternatives for post-hysterectomy pelvic organ prolapse (POP). A Markov decision analysis model was used to assess and compare the relative cost effectiveness of expectant management, use of a pessary, and surgery for obtaining months of quality-adjusted life over 1 year. Sensitivity analysis was conducted to determine whether the results depended on specific estimates of patient utilities for pessary use, probabilities for complications and other events, and estimated costs. Only two treatment alternatives were found to be efficient choices: initial pessary use and vaginal reconstructive surgery (VRS). Pessary use (including patients that eventually transitioned to surgery) achieved 10.4 quality-adjusted months, at a cost of $10,000 per patient, while VRS obtained 11.4 quality-adjusted months, at $15,000 per patient. Sensitivity analysis demonstrated that these baseline results depended on several key estimates in the model. This analysis indicates that pessary use and VRS are the most cost-effective treatment alternatives for treating post-hysterectomy vaginal prolapse. Additional research is needed to standardize POP outcomes and complications, so that healthcare providers can best utilize cost information in balancing the risks and benefits of their treatment decisions.
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Combining Study Outcome Measures Using Dominance Adjusted Weights
ERIC Educational Resources Information Center
Makambi, Kepher H.; Lu, Wenxin
2013-01-01
Weighting of studies in meta-analysis is usually implemented by using the estimated inverse variances of treatment effect estimates. However, there is a possibility of one study dominating other studies in the estimation process by taking on a weight that is above some upper limit. We implement an estimator of the heterogeneity variance that takes…
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Acute health impacts of airborne particles estimated from satellite remote sensing.
Wang, Zhaoxi; Liu, Yang; Hu, Mu; Pan, Xiaochuan; Shi, Jing; Chen, Feng; He, Kebin; Koutrakis, Petros; Christiani, David C
2013-01-01
Satellite-based remote sensing provides a unique opportunity to monitor air quality from space at global, continental, national and regional scales. Most current research focused on developing empirical models using ground measurements of the ambient particulate. However, the application of satellite-based exposure assessment in environmental health is still limited, especially for acute effects, because the development of satellite PM(2.5) model depends on the availability of ground measurements. We tested the hypothesis that MODIS AOD (aerosol optical depth) exposure estimates, obtained from NASA satellites, are directly associated with daily health outcomes. Three independent healthcare databases were used: unscheduled outpatient visits, hospital admissions, and mortality collected in Beijing metropolitan area, China during 2006. We use generalized linear models to compare the short-term effects of air pollution assessed by ground monitoring (PM(10)) with adjustment of absolute humidity (AH) and AH-calibrated AOD. Across all databases we found that both AH-calibrated AOD and PM(10) (adjusted by AH) were consistently associated with elevated daily events on the current day and/or lag days for cardiovascular diseases, ischemic heart diseases, and COPD. The relative risks estimated by AH-calibrated AOD and PM(10) (adjusted by AH) were similar. Additionally, compared to ground PM(10), we found that AH-calibrated AOD had narrower confidence intervals for all models and was more robust in estimating the current day and lag day effects. Our preliminary findings suggested that, with proper adjustment of meteorological factors, satellite AOD can be used directly to estimate the acute health impacts of ambient particles without prior calibrating to the sparse ground monitoring networks. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Extension of Kaplan-Meier methods in observational studies with time-varying treatment.
Xu, Stanley; Shetterly, Susan; Powers, David; Raebel, Marsha A; Tsai, Thomas T; Ho, P Michael; Magid, David
2012-01-01
Inverse probability of treatment weighted Kaplan-Meier estimates have been developed to compare two treatments in the presence of confounders in observational studies. Recently, stabilized weights were developed to reduce the influence of extreme inverse probability of treatment-weighted weights in estimating treatment effects. The objective of this research was to use adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests to examine the effect of a treatment that varies over time in an observational study. We proposed stabilized weight adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests when the treatment was time-varying over the follow-up period. We applied these new methods in examining the effect of an anti-platelet agent, clopidogrel, on subsequent events, including bleeding, myocardial infarction, and death after a drug-eluting stent was implanted into a coronary artery. In this population, clopidogrel use may change over time based on a patient's behavior (e.g., nonadherence) and physicians' recommendations (e.g., end of duration of therapy). Consequently, clopidogrel use was treated as a time-varying variable. We demonstrate that 1) the sample sizes at three chosen time points are almost identical in the original and weighted datasets; and 2) the covariates between patients on and off clopidogrel were well balanced after stabilized weights were applied to the original samples. The stabilized weight-adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests are useful in presenting and comparing survival functions for time-varying treatments in observational studies while adjusting for known confounders. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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Bykov, Katsiaryna; Yoshida, Kazuki; Weisskopf, Marc G; Gagne, Joshua J
2017-03-01
Both statins and higher serum cholesterol have been reported to reduce to risk of Parkinson Disease (PD). Given the importance of adjusting for cholesterol levels when evaluating the effect of statins, we assessed whether the protective effect of statins would remain when adjustment for cholesterol is performed. We conducted a systematic review of epidemiologic studies that reported quantitative estimates of the association between statins and incident PD and were published through February 2016. Random-effects meta-analysis was used to assess the effect of statins on PD separately among the studies that adjusted for either cholesterol or hyperlipidemia and studies that did not. Ten eligible studies that evaluated the use of statins and incident PD were identified. Among the six studies that did not adjust for cholesterol, a protective effect of statins was observed (relative risk 0.75; 95% confidence intervals (CI) 0.60 to 0.92). Excluding studies with possible bias because of reverse causation or stratifying on study design did not affect the results. No protective effect was observed among the four studies that adjusted for either cholesterol of hyperlipidemia (relative risk 0.91; 95%CI 0.68 to 1.22). The effect estimate for studies that adjusted for cholesterol was 1.04 (95%CI 0.68 to 1.59) when a study with immortal time bias was excluded. The apparent protective effect of statins on risk of PD is at least partially explained by confounding by statin indication. Immortal time bias and healthy user effects also could have contributed to biased results. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Bayesian effect estimation accounting for adjustment uncertainty.
Wang, Chi; Parmigiani, Giovanni; Dominici, Francesca
2012-09-01
Model-based estimation of the effect of an exposure on an outcome is generally sensitive to the choice of which confounding factors are included in the model. We propose a new approach, which we call Bayesian adjustment for confounding (BAC), to estimate the effect of an exposure of interest on the outcome, while accounting for the uncertainty in the choice of confounders. Our approach is based on specifying two models: (1) the outcome as a function of the exposure and the potential confounders (the outcome model); and (2) the exposure as a function of the potential confounders (the exposure model). We consider Bayesian variable selection on both models and link the two by introducing a dependence parameter, ω, denoting the prior odds of including a predictor in the outcome model, given that the same predictor is in the exposure model. In the absence of dependence (ω= 1), BAC reduces to traditional Bayesian model averaging (BMA). In simulation studies, we show that BAC, with ω > 1, estimates the exposure effect with smaller bias than traditional BMA, and improved coverage. We, then, compare BAC, a recent approach of Crainiceanu, Dominici, and Parmigiani (2008, Biometrika 95, 635-651), and traditional BMA in a time series data set of hospital admissions, air pollution levels, and weather variables in Nassau, NY for the period 1999-2005. Using each approach, we estimate the short-term effects of on emergency admissions for cardiovascular diseases, accounting for confounding. This application illustrates the potentially significant pitfalls of misusing variable selection methods in the context of adjustment uncertainty. © 2012, The International Biometric Society.
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Beckmann, Kerri; Duffy, Stephen W; Lynch, John; Hiller, Janet; Farshid, Gelareh; Roder, David
2015-09-01
To estimate over-diagnosis due to population-based mammography screening using a lead time adjustment approach, with lead time measures based on symptomatic cancers only. Women aged 40-84 in 1989-2009 in South Australia eligible for mammography screening. Numbers of observed and expected breast cancer cases were compared, after adjustment for lead time. Lead time effects were modelled using age-specific estimates of lead time (derived from interval cancer rates and predicted background incidence, using maximum likelihood methods) and screening sensitivity, projected background breast cancer incidence rates (in the absence of screening), and proportions screened, by age and calendar year. Lead time estimates were 12, 26, 43 and 53 months, for women aged 40-49, 50-59, 60-69 and 70-79 respectively. Background incidence rates were estimated to have increased by 0.9% and 1.2% per year for invasive and all breast cancer. Over-diagnosis among women aged 40-84 was estimated at 7.9% (0.1-12.0%) for invasive cases and 12.0% (5.7-15.4%) when including ductal carcinoma in-situ (DCIS). We estimated 8% over-diagnosis for invasive breast cancer and 12% inclusive of DCIS cancers due to mammography screening among women aged 40-84. These estimates may overstate the extent of over-diagnosis if the increasing prevalence of breast cancer risk factors has led to higher background incidence than projected. © The Author(s) 2015.
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[Effect of social desirability on dietary intake estimated from a food questionnaire].
Barros, Renata; Moreira, Pedro; Oliveira, Bruno
2005-01-01
Self-report of dietary intake could be biased by social thus affecting risk estimates in epidemiological studies. The objective of study was to assess the effect of social desirability on dietary intake from a food frequency questionnaire (FFQ). A convenience sample of 483 Portuguese university students was recruited. Subjects were invited to complete a two-part self-administered questionnaire: the first part included the Marlowe-Crowne Social Desirability Scale (M-CSDS), a physical activity questionnaire and self-reported height and weight; the second part, included a semi-quantitative FFQ validated for Portuguese adults, that should be returned after fulfillment. All subjects completed the first part of the questionnaire and 40.4% returned the FFQ fairly completed. In multiple regression analysis, after adjustment for energy and confounders, social desirability produced a significant positive effect in the estimates of dietary fibre, vitamin C, vitamin E, magnesium and potassium, in both genders. In multiple regression, after adjustment for energy and confounders, social desirability had a significant positive effect in the estimates of vegetable consumption, for both genders, and a negative effect in white bread and beer, for women. Social desirability affected nutritional and food intake estimated from a food frequency questionnaire.
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Estimating Teacher Effectiveness from Two-Year Changes in Students' Test Scores
ERIC Educational Resources Information Center
Leigh, Andrew
2010-01-01
Using a dataset covering over 10,000 Australian school teachers and over 90,000 pupils, I estimate how effective teachers are in raising students' test scores. Since the exams are biennial, it is necessary to take account of the teacher's work in the intervening year. Even adjusting for measurement error, the teacher fixed effects are widely…
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The Effect of State Regulatory Stringency on Nursing Home Quality
Mukamel, Dana B; Weimer, David L; Harrington, Charlene; Spector, William D; Ladd, Heather; Li, Yue
2012-01-01
Objective To test the hypothesis that more stringent quality regulations contribute to better quality nursing home care and to assess their cost-effectiveness. Data Sources/Setting Primary and secondary data from all states and U.S. nursing homes between 2005 and 2006. Study Design We estimated seven models, regressing quality measures on the Harrington Regulation Stringency Index and control variables. To account for endogeneity between regulation and quality, we used instrumental variables techniques. Quality was measured by staffing hours by type per case-mix adjusted day, hotel expenditures, and risk-adjusted decline in activities of daily living, high-risk pressure sores, and urinary incontinence. Data Collection All states' licensing and certification offices were surveyed to obtain data about deficiencies. Secondary data included the Minimum Data Set, Medicare Cost Reports, and the Economic Freedom Index. Principal Findings Regulatory stringency was significantly associated with better quality for four of the seven measures studied. The cost-effectiveness for the activities-of-daily-living measure was estimated at about 72,000 in 2011/ Quality Adjusted Life Year. Conclusions Quality regulations lead to better quality in nursing homes along some dimensions, but not all. Our estimates of cost-effectiveness suggest that increased regulatory stringency is in the ballpark of other acceptable cost-effective practices. PMID:22946859
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The performance of different propensity score methods for estimating marginal hazard ratios.
Austin, Peter C
2013-07-20
Propensity score methods are increasingly being used to reduce or minimize the effects of confounding when estimating the effects of treatments, exposures, or interventions when using observational or non-randomized data. Under the assumption of no unmeasured confounders, previous research has shown that propensity score methods allow for unbiased estimation of linear treatment effects (e.g., differences in means or proportions). However, in biomedical research, time-to-event outcomes occur frequently. There is a paucity of research into the performance of different propensity score methods for estimating the effect of treatment on time-to-event outcomes. Furthermore, propensity score methods allow for the estimation of marginal or population-average treatment effects. We conducted an extensive series of Monte Carlo simulations to examine the performance of propensity score matching (1:1 greedy nearest-neighbor matching within propensity score calipers), stratification on the propensity score, inverse probability of treatment weighting (IPTW) using the propensity score, and covariate adjustment using the propensity score to estimate marginal hazard ratios. We found that both propensity score matching and IPTW using the propensity score allow for the estimation of marginal hazard ratios with minimal bias. Of these two approaches, IPTW using the propensity score resulted in estimates with lower mean squared error when estimating the effect of treatment in the treated. Stratification on the propensity score and covariate adjustment using the propensity score result in biased estimation of both marginal and conditional hazard ratios. Applied researchers are encouraged to use propensity score matching and IPTW using the propensity score when estimating the relative effect of treatment on time-to-event outcomes. Copyright © 2012 John Wiley & Sons, Ltd.
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ERIC Educational Resources Information Center
Steiner, Peter M.; Cook, Thomas D.; Shadish, William R.
2011-01-01
The effect of unreliability of measurement on propensity score (PS) adjusted treatment effects has not been previously studied. The authors report on a study simulating different degrees of unreliability in the multiple covariates that were used to estimate the PS. The simulation uses the same data as two prior studies. Shadish, Clark, and Steiner…
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Effective fiber for lactating dairy cows: a physically adjusted NDF (paNDF) system
USDA-ARS?s Scientific Manuscript database
Multiplying dietary NDF by particle size (PS) has been used as an estimate of physically effective fiber (peNDF). Our objectives were to: 1) compare the use of peNDF as dietary NDF × PS vs. use of individual NDF and PS descriptors in a physically adjusted NDF (paNDF) system when used with other fact...
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Latimer, Nicholas R; Abrams, K R; Lambert, P C; Crowther, M J; Wailoo, A J; Morden, J P; Akehurst, R L; Campbell, M J
2017-04-01
Estimates of the overall survival benefit of new cancer treatments are often confounded by treatment switching in randomised controlled trials (RCTs) - whereby patients randomised to the control group are permitted to switch onto the experimental treatment upon disease progression. In health technology assessment, estimates of the unconfounded overall survival benefit associated with the new treatment are needed. Several switching adjustment methods have been advocated in the literature, some of which have been used in health technology assessment. However, it is unclear which methods are likely to produce least bias in realistic RCT-based scenarios. We simulated RCTs in which switching, associated with patient prognosis, was permitted. Treatment effect size and time dependency, switching proportions and disease severity were varied across scenarios. We assessed the performance of alternative adjustment methods based upon bias, coverage and mean squared error, related to the estimation of true restricted mean survival in the absence of switching in the control group. We found that when the treatment effect was not time-dependent, rank preserving structural failure time models (RPSFTM) and iterative parameter estimation methods produced low levels of bias. However, in the presence of a time-dependent treatment effect, these methods produced higher levels of bias, similar to those produced by an inverse probability of censoring weights method. The inverse probability of censoring weights and structural nested models produced high levels of bias when switching proportions exceeded 85%. A simplified two-stage Weibull method produced low bias across all scenarios and provided the treatment switching mechanism is suitable, represents an appropriate adjustment method.
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Björ, Ove; Damber, Lena; Jonsson, Håkan; Nilsson, Tohr
2015-07-01
Iron-ore miners are exposed to extremely dusty and physically arduous work environments. The demanding activities of mining select healthier workers with longer work histories (ie, the Healthy Worker Survivor Effect (HWSE)), and could have a reversing effect on the exposure-response association. The objective of this study was to evaluate an iron-ore mining cohort to determine whether the effect of respirable dust was confounded by the presence of an HWSE. When an HWSE exists, standard modelling methods, such as Cox regression analysis, produce biased results. We compared results from g-estimation of accelerated failure-time modelling adjusted for HWSE with corresponding unadjusted Cox regression modelling results. For all-cause mortality when adjusting for the HWSE, cumulative exposure from respirable dust was associated with a 6% decrease of life expectancy if exposed ≥15 years, compared with never being exposed. Respirable dust continued to be associated with mortality after censoring outcomes known to be associated with dust when adjusting for the HWSE. In contrast, results based on Cox regression analysis did not support that an association was present. The adjustment for the HWSE made a difference when estimating the risk of mortality from respirable dust. The results of this study, therefore, support the recommendation that standard methods of analysis should be complemented with structural modelling analysis techniques, such as g-estimation of accelerated failure-time modelling, to adjust for the HWSE. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Methods of adjusting the stable estimates of fertility for the effects of mortality decline.
Abou-Gamrah, H
1976-03-01
Summary The paper shows how stable population methods, based on the age structure and the rate of increase, may be used to estimate the demographic measures of a quasi-stable population. After a discussion of known methods for adjusting the stable estimates to allow for the effects of mortality decline two new methods are presented, the application of which requires less information. The first method does not need any supplementary information, and the second method requires an estimate of the difference between the last two five-year intercensal rates of increase, i.e. five times the annual change of the rate of increase during the last ten years. For these new methods we do not need to know the onset year of mortality decline as in the Coale-Demeny method, or a long series of rates of increase as in Zachariah's method.
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The economic effect of Planet Health on preventing bulimia nervosa.
Wang, Li Yan; Nichols, Lauren P; Austin, S Bryn
2011-08-01
To assess the economic effect of the school-based obesity prevention program Planet Health on preventing disordered weight control behaviors and to determine the cost-effectiveness of the intervention in terms of its combined effect on prevention of obesity and disordered weight control behaviors. On the basis of the intervention's short-term effect on disordered weight control behaviors prevention, we projected the number of girls who were prevented from developing bulimia nervosa by age 17 years. We further estimated medical costs saved and quality-adjusted life years gained by the intervention over 10 years. As a final step, we compared the intervention costs with the combined intervention benefits from both obesity prevention (reported previously) and prevention of disordered weight control behaviors to determine the overall cost-effectiveness of the intervention. Middle schools. A sample of 254 intervention girls aged 10 to 14 years. The Planet Health program was implemented during the school years from 1995 to 1997 and was designed to promote healthful nutrition and physical activity among youth. Intervention costs, medical costs saved, quality-adjusted life years gained, and cost-effectiveness ratio. An estimated 1 case of bulimia nervosa would have been prevented. As a result, an estimated $33 999 in medical costs and 0.7 quality-adjusted life years would be saved. At an intervention cost of $46 803, the combined prevention of obesity and disordered weight control behaviors would yield a net savings of $14 238 and a gain of 4.8 quality-adjusted life years. Primary prevention programs, such as Planet Health, warrant careful consideration by policy makers and program planners. The findings of this study provide additional argument for integrated prevention of obesity and eating disorders.
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Adjustment to time of use pricing: Persistence of habits or change
NASA Astrophysics Data System (ADS)
Rebello, Derrick Michael
1999-11-01
Generally the dynamics related to residential electricity consumption under TOU rates have not been analyzed completely. A habit persistence model is proposed to account for the dynamics that may be present as a result of recurring habits or lack of information about the effects of shifting load across TOU periods. In addition, the presence of attrition bias necessitated a two-step estimation approach. The decision to remain in the program modeled in the first-step, while demand for electricity was estimated in the second-step. Results show that own-price effects and habit persistence have the most significant effect the model. The habit effects, which while small in absolute terms, are significant. Elasticity estimates show that electricity consumption is inelastic during all periods of the day. Estimates of the long-run elasticities were nearly identical to short-run estimates, showing little or no adjustment across time. Cross-price elasticities indicate a willingness to substitute consumption across periods implying that TOU goods are weak substitutes. The most significant substitution occurs during the period of 5:00 PM to 9:00 PM, when most individuals are likely to be home and active.
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Turner, Nikki; Pierse, Nevil; Bissielo, Ange; Huang, Q Sue; Baker, Michael G; Widdowson, Marc-Alain; Kelly, Heath
2014-06-17
Few studies report the effectiveness of trivalent inactivated influenza vaccine (TIV) in preventing hospitalisation for influenza-confirmed respiratory infections. Using a prospective surveillance platform, this study reports the first such estimate from a well-defined ethnically diverse population in New Zealand (NZ). A case test-negative design was used to estimate propensity adjusted vaccine effectiveness. Patients with a severe acute respiratory infection (SARI), defined as a patient of any age requiring hospitalisation with a history of a fever or a measured temperature ≥38°C and cough and onset within the past 7 days, admitted to public hospitals in South and Central Auckland were eligible for inclusion in the study. Cases were SARI patients who tested positive for influenza, while non-cases (controls) were SARI patients who tested negative. Results were adjusted for the propensity to be vaccinated and the timing of the influenza season. The propensity and season adjusted vaccine effectiveness (VE) was estimated as 39% (95% CI 16;56). The VE point estimate against influenza A (H1N1) was lower than for influenza B or influenza A (H3N2) but confidence intervals were wide and overlapping. Estimated VE was 59% (95% CI 26;77) in patients aged 45-64 years but only 8% (-78;53) in those aged 65 years and above. Prospective surveillance for SARI has been successfully established in NZ. This study for the first year, the 2012 influenza season, has shown low to moderate protection by TIV against influenza positive hospitalisation. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Karnon, Jonathan; Caffrey, Orla; Pham, Clarabelle; Grieve, Richard; Ben-Tovim, David; Hakendorf, Paul; Crotty, Maria
2013-06-01
Cost-effectiveness analysis is well established for pharmaceuticals and medical technologies but not for evaluating variations in clinical practice. This paper describes a novel methodology--risk adjusted cost-effectiveness (RAC-E)--that facilitates the comparative evaluation of applied clinical practice processes. In this application, risk adjustment is undertaken with a multivariate matching algorithm that balances the baseline characteristics of patients attending different settings (e.g., hospitals). Linked, routinely collected data are used to analyse patient-level costs and outcomes over a 2-year period, as well as to extrapolate costs and survival over patient lifetimes. The study reports the relative cost-effectiveness of alternative forms of clinical practice, including a full representation of the statistical uncertainty around the mean estimates. The methodology is illustrated by a case study that evaluates the relative cost-effectiveness of services for patients presenting with acute chest pain across the four main public hospitals in South Australia. The evaluation finds that services provided at two hospitals were dominated, and of the remaining services, the more effective hospital gained life years at a low mean additional cost and had an 80% probability of being the most cost-effective hospital at realistic cost-effectiveness thresholds. Potential determinants of the estimated variation in costs and effects were identified, although more detailed analyses to identify specific areas of variation in clinical practice are required to inform improvements at the less cost-effective institutions. Copyright © 2012 John Wiley & Sons, Ltd.
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Potter, Gail E; Smieszek, Timo; Sailer, Kerstin
2015-09-01
Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0-5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models.
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Potter, Gail E.; Smieszek, Timo; Sailer, Kerstin
2015-01-01
Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0–5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models. PMID:26634122
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Chu, Rong; Walter, Stephen D.; Guyatt, Gordon; Devereaux, P. J.; Walsh, Michael; Thorlund, Kristian; Thabane, Lehana
2012-01-01
Background Chance imbalance in baseline prognosis of a randomized controlled trial can lead to over or underestimation of treatment effects, particularly in trials with small sample sizes. Our study aimed to (1) evaluate the probability of imbalance in a binary prognostic factor (PF) between two treatment arms, (2) investigate the impact of prognostic imbalance on the estimation of a treatment effect, and (3) examine the effect of sample size (n) in relation to the first two objectives. Methods We simulated data from parallel-group trials evaluating a binary outcome by varying the risk of the outcome, effect of the treatment, power and prevalence of the PF, and n. Logistic regression models with and without adjustment for the PF were compared in terms of bias, standard error, coverage of confidence interval and statistical power. Results For a PF with a prevalence of 0.5, the probability of a difference in the frequency of the PF≥5% reaches 0.42 with 125/arm. Ignoring a strong PF (relative risk = 5) leads to underestimating the strength of a moderate treatment effect, and the underestimate is independent of n when n is >50/arm. Adjusting for such PF increases statistical power. If the PF is weak (RR = 2), adjustment makes little difference in statistical inference. Conditional on a 5% imbalance of a powerful PF, adjustment reduces the likelihood of large bias. If an absolute measure of imbalance ≥5% is deemed important, including 1000 patients/arm provides sufficient protection against such an imbalance. Two thousand patients/arm may provide an adequate control against large random deviations in treatment effect estimation in the presence of a powerful PF. Conclusions The probability of prognostic imbalance in small trials can be substantial. Covariate adjustment improves estimation accuracy and statistical power, and hence should be performed when strong PFs are observed. PMID:22629322
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Røislien, Jo; Clausen, Thomas; Gran, Jon Michael; Bukten, Anne
2014-05-17
The reduction of crime is an important outcome of opioid maintenance treatment (OMT). Criminal intensity and treatment regimes vary among OMT patients, but this is rarely adjusted for in statistical analyses, which tend to focus on cohort incidence rates and rate ratios. The purpose of this work was to estimate the relationship between treatment and criminal convictions among OMT patients, adjusting for individual covariate information and timing of events, fitting time-to-event regression models of increasing complexity. National criminal records were cross linked with treatment data on 3221 patients starting OMT in Norway 1997-2003. In addition to calculating cohort incidence rates, criminal convictions was modelled as a recurrent event dependent variable, and treatment a time-dependent covariate, in Cox proportional hazards, Aalen's additive hazards, and semi-parametric additive hazards regression models. Both fixed and dynamic covariates were included. During OMT, the number of days with criminal convictions for the cohort as a whole was 61% lower than when not in treatment. OMT was associated with reduced number of days with criminal convictions in all time-to-event regression models, but the hazard ratio (95% CI) was strongly attenuated when adjusting for covariates; from 0.40 (0.35, 0.45) in a univariate model to 0.79 (0.72, 0.87) in a fully adjusted model. The hazard was lower for females and decreasing with older age, while increasing with high numbers of criminal convictions prior to application to OMT (all p < 0.001). The strongest predictors were level of criminal activity prior to entering into OMT, and having a recent criminal conviction (both p < 0.001). The effect of several predictors was significantly time-varying with their effects diminishing over time. Analyzing complex observational data regarding to fixed factors only overlooks important temporal information, and naïve cohort level incidence rates might result in biased estimates of the effect of interventions. Applying time-to-event regression models, properly adjusting for individual covariate information and timing of various events, allows for more precise and reliable effect estimates, as well as painting a more nuanced picture that can aid health care professionals and policy makers.
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Three estimates of the association between linear growth failure and cognitive ability.
Cheung, Y B; Lam, K F
2009-09-01
To compare three estimators of association between growth stunting as measured by height-for-age Z-score and cognitive ability in children, and to examine the extent statistical adjustment for covariates is useful for removing confounding due to socio-economic status. Three estimators, namely random-effects, within- and between-cluster estimators, for panel data were used to estimate the association in a survey of 1105 pairs of siblings who were assessed for anthropometry and cognition. Furthermore, a 'combined' model was formulated to simultaneously provide the within- and between-cluster estimates. Random-effects and between-cluster estimators showed strong association between linear growth and cognitive ability, even after adjustment for a range of socio-economic variables. In contrast, the within-cluster estimator showed a much more modest association: For every increase of one Z-score in linear growth, cognitive ability increased by about 0.08 standard deviation (P < 0.001). The combined model verified that the between-cluster estimate was significantly larger than the within-cluster estimate (P = 0.004). Residual confounding by socio-economic situations may explain a substantial proportion of the observed association between linear growth and cognition in studies that attempt to control the confounding by means of multivariable regression analysis. The within-cluster estimator provides more convincing and modest results about the strength of association.
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Valenciano, Marta; Kissling, Esther; Cohen, Jean-Marie; Oroszi, Beatrix; Barret, Anne-Sophie; Rizzo, Caterina; Nunes, Baltazar; Pitigoi, Daniela; Larrauri Cámara, Amparro; Mosnier, Anne; Horvath, Judith K.; O'Donnell, Joan; Bella, Antonino; Guiomar, Raquel; Lupulescu, Emilia; Savulescu, Camelia; Ciancio, Bruno C.; Kramarz, Piotr; Moren, Alain
2011-01-01
Background A multicentre case-control study based on sentinel practitioner surveillance networks from seven European countries was undertaken to estimate the effectiveness of 2009–2010 pandemic and seasonal influenza vaccines against medically attended influenza-like illness (ILI) laboratory-confirmed as pandemic influenza A (H1N1) (pH1N1). Methods and Findings Sentinel practitioners swabbed ILI patients using systematic sampling. We included in the study patients meeting the European ILI case definition with onset of symptoms >14 days after the start of national pandemic vaccination campaigns. We compared pH1N1 cases to influenza laboratory-negative controls. A valid vaccination corresponded to >14 days between receiving a dose of vaccine and symptom onset. We estimated pooled vaccine effectiveness (VE) as 1 minus the odds ratio with the study site as a fixed effect. Using logistic regression, we adjusted VE for potential confounding factors (age group, sex, month of onset, chronic diseases and related hospitalizations, smoking history, seasonal influenza vaccinations, practitioner visits in previous year). We conducted a complete case analysis excluding individuals with missing values and a multiple multivariate imputation to estimate missing values. The multivariate imputation (n = 2902) adjusted pandemic VE (PIVE) estimates were 71.9% (95% confidence interval [CI] 45.6–85.5) overall; 78.4% (95% CI 54.4–89.8) in patients <65 years; and 72.9% (95% CI 39.8–87.8) in individuals without chronic disease. The complete case (n = 1,502) adjusted PIVE were 66.0% (95% CI 23.9–84.8), 71.3% (95% CI 29.1–88.4), and 70.2% (95% CI 19.4–89.0), respectively. The adjusted PIVE was 66.0% (95% CI −69.9 to 93.2) if vaccinated 8–14 days before ILI onset. The adjusted 2009–2010 seasonal influenza VE was 9.9% (95% CI −65.2 to 50.9). Conclusions Our results suggest good protection of the pandemic monovalent vaccine against medically attended pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine. However, the late availability of the pandemic vaccine and subsequent limited coverage with this vaccine hampered our ability to study vaccine benefits during the outbreak period. Future studies should include estimation of the effectiveness of the new trivalent vaccine in the upcoming 2010–2011 season, when vaccination will occur before the influenza season starts. Please see later in the article for the Editors' Summary PMID:21379316
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Inverse probability weighting for covariate adjustment in randomized studies
Li, Xiaochun; Li, Lingling
2013-01-01
SUMMARY Covariate adjustment in randomized clinical trials has the potential benefit of precision gain. It also has the potential pitfall of reduced objectivity as it opens the possibility of selecting “favorable” model that yields strong treatment benefit estimate. Although there is a large volume of statistical literature targeting on the first aspect, realistic solutions to enforce objective inference and improve precision are rare. As a typical randomized trial needs to accommodate many implementation issues beyond statistical considerations, maintaining the objectivity is at least as important as precision gain if not more, particularly from the perspective of the regulatory agencies. In this article, we propose a two-stage estimation procedure based on inverse probability weighting to achieve better precision without compromising objectivity. The procedure is designed in a way such that the covariate adjustment is performed before seeing the outcome, effectively reducing the possibility of selecting a “favorable” model that yields a strong intervention effect. Both theoretical and numerical properties of the estimation procedure are presented. Application of the proposed method to a real data example is presented. PMID:24038458
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Thomas, H L; Andrews, N; Green, H K; Boddington, N L; Zhao, H; Reynolds, A; McMenamin, J; Pebody, R G
2014-01-01
Methods for estimating vaccine effectiveness (VE) against severe influenza are not well established. We used the screening method to estimate VE against influenza resulting in intensive care unit (ICU) admission in England and Scotland in 2011/2012. We extracted data on confirmed influenza ICU cases from severe influenza surveillance systems, and obtained their 2011/2012 trivalent influenza vaccine (TIV) status from primary care. We compared case vaccine uptake with population vaccine uptake obtained from routine monitoring systems, adjusting for age group, specific risk group, region and week. Of 60 influenza ICU cases reported, vaccination status was available for 56 (93%). Adjusted VE against ICU admission for those aged ≥ 65 years was -10% [95% confidence interval (CI) -207 to 60], consistent with evidence of poor protection from the 2011/2012 TIV in 2011/2012. Adjusted VE for those aged <65 years in risk groups was -296% (95% CI -930 to -52), suggesting significant residual confounding using the screening method in those subject to selective vaccination.
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Inverse probability weighting for covariate adjustment in randomized studies.
Shen, Changyu; Li, Xiaochun; Li, Lingling
2014-02-20
Covariate adjustment in randomized clinical trials has the potential benefit of precision gain. It also has the potential pitfall of reduced objectivity as it opens the possibility of selecting a 'favorable' model that yields strong treatment benefit estimate. Although there is a large volume of statistical literature targeting on the first aspect, realistic solutions to enforce objective inference and improve precision are rare. As a typical randomized trial needs to accommodate many implementation issues beyond statistical considerations, maintaining the objectivity is at least as important as precision gain if not more, particularly from the perspective of the regulatory agencies. In this article, we propose a two-stage estimation procedure based on inverse probability weighting to achieve better precision without compromising objectivity. The procedure is designed in a way such that the covariate adjustment is performed before seeing the outcome, effectively reducing the possibility of selecting a 'favorable' model that yields a strong intervention effect. Both theoretical and numerical properties of the estimation procedure are presented. Application of the proposed method to a real data example is presented. Copyright © 2013 John Wiley & Sons, Ltd.
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2011-01-01
Background Physicians of the Spanish Influenza Sentinel Surveillance System report and systematically swab patients attended to their practices for influenza-like illness (ILI). Within the surveillance system, some Spanish regions also participated in an observational study aiming at estimating influenza vaccine effectiveness (cycEVA study). During the season 2009-2010, we estimated pandemic influenza vaccine effectiveness using both the influenza surveillance data and the cycEVA study. Methods We conducted two case-control studies using the test-negative design, between weeks 48/2009 and 8/2010 of the pandemic season. The surveillance-based study included all swabbed patients in the sentinel surveillance system. The cycEVA study included swabbed patients from seven Spanish regions. Cases were laboratory-confirmed pandemic influenza A(H1N1)2009. Controls were ILI patients testing negative for any type of influenza. Variables collected in both studies included demographic data, vaccination status, laboratory results, chronic conditions, and pregnancy. Additionally, cycEVA questionnaire collected data on previous influenza vaccination, smoking, functional status, hospitalisations, visits to the general practitioners, and obesity. We used logistic regression to calculate adjusted odds ratios (OR), computing pandemic influenza vaccine effectiveness as (1-OR)*100. Results We included 331 cases and 995 controls in the surveillance-based study and 85 cases and 351 controls in the cycEVA study. We detected nine (2.7%) and two (2.4%) vaccine failures in the surveillance-based and cycEVA studies, respectively. Adjusting for variables collected in surveillance database and swabbing month, pandemic influenza vaccine effectiveness was 62% (95% confidence interval (CI): -5; 87). The cycEVA vaccine effectiveness was 64% (95%CI: -225; 96) when adjusting for common variables with the surveillance system and 75% (95%CI: -293; 98) adjusting for all variables collected. Conclusion Point estimates of the pandemic influenza vaccine effectiveness suggested a protective effect of the pandemic vaccine against laboratory-confirmed influenza A(H1N1)2009 in the season 2009-2010. Both studies were limited by the low vaccine coverage and the late start of the vaccination campaign. Routine influenza surveillance provides reliable estimates and could be used for influenza vaccine effectiveness studies in future seasons taken into account the surveillance system limitations. PMID:22129083
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Wang, Ching-Yun; Cullings, Harry; Song, Xiao; Kopecky, Kenneth J.
2017-01-01
SUMMARY Observational epidemiological studies often confront the problem of estimating exposure-disease relationships when the exposure is not measured exactly. In the paper, we investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a nonparametric correction (NPC) estimator using data from the subcohort, and further propose a joint nonparametric correction (JNPC) estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of JNPC and NPC is further developed. The proposed estimators are nonparametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses. PMID:29354018
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Over, Thomas M.; Saito, Riki J.; Veilleux, Andrea G.; Sharpe, Jennifer B.; Soong, David T.; Ishii, Audrey L.
2016-06-28
This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant.The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted annual maximum peak discharge records by streamgage are provided at https://doi.org/10.3133/sir20165050 for download.
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Effect of pregnancy on the genetic evaluation of dairy cattle.
Pereira, R J; Santana, M L; Bignardi, A B; Verneque, R S; El Faro, L; Albuquerque, L G
2011-09-26
We investigated the effect of stage of pregnancy on estimates of breeding values for milk yield and milk persistency in Gyr and Holstein dairy cattle in Brazil. Test-day milk yield records were analyzed using random regression models with or without the effect of pregnancy. Models were compared using residual variances, heritabilities, rank correlations of estimated breeding values of bulls and cows, and number of nonpregnant cows in the top 200 for milk yield and milk persistency. The estimates of residual variance and heritabilities obtained with the models with or without the effect of pregnancy were similar for the two breeds. Inclusion of the effect of pregnancy in genetic evaluation models for these populations did not affect the ranking of cows and sires based on their predicted breeding values for 305-day cumulative milk yield. In contrast, when we examined persistency of milk yield, lack of adjustment for the effect of pregnancy overestimated breeding values of nonpregnant cows and cows with a long days open period and underestimated breeding values of cows with a short days open period. We recommend that models include the effect of days of pregnancy for estimation of adjustment factors for the effect of pregnancy in genetic evaluations of Dairy Gyr and Holstein cattle.
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Simmons, Joseph P; LeBoeuf, Robyn A; Nelson, Leif D
2010-12-01
Increasing accuracy motivation (e.g., by providing monetary incentives for accuracy) often fails to increase adjustment away from provided anchors, a result that has led researchers to conclude that people do not effortfully adjust away from such anchors. We challenge this conclusion. First, we show that people are typically uncertain about which way to adjust from provided anchors and that this uncertainty often causes people to believe that they have initially adjusted too far away from such anchors (Studies 1a and 1b). Then, we show that although accuracy motivation fails to increase the gap between anchors and final estimates when people are uncertain about the direction of adjustment, accuracy motivation does increase anchor-estimate gaps when people are certain about the direction of adjustment, and that this is true regardless of whether the anchors are provided or self-generated (Studies 2, 3a, 3b, and 5). These results suggest that people do effortfully adjust away from provided anchors but that uncertainty about the direction of adjustment makes that adjustment harder to detect than previously assumed. This conclusion has important theoretical implications, suggesting that currently emphasized distinctions between anchor types (self-generated vs. provided) are not fundamental and that ostensibly competing theories of anchoring (selective accessibility and anchoring-and-adjustment) are complementary. PsycINFO Database Record (c) 2010 APA, all rights reserved.
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A matching framework to improve causal inference in interrupted time-series analysis.
Linden, Ariel
2018-04-01
Interrupted time-series analysis (ITSA) is a popular evaluation methodology in which a single treatment unit's outcome is studied over time and the intervention is expected to "interrupt" the level and/or trend of the outcome, subsequent to its introduction. When ITSA is implemented without a comparison group, the internal validity may be quite poor. Therefore, adding a comparable control group to serve as the counterfactual is always preferred. This paper introduces a novel matching framework, ITSAMATCH, to create a comparable control group by matching directly on covariates and then use these matches in the outcomes model. We evaluate the effect of California's Proposition 99 (passed in 1988) for reducing cigarette sales, by comparing California to other states not exposed to smoking reduction initiatives. We compare ITSAMATCH results to 2 commonly used matching approaches, synthetic controls (SYNTH), and regression adjustment; SYNTH reweights nontreated units to make them comparable to the treated unit, and regression adjusts covariates directly. Methods are compared by assessing covariate balance and treatment effects. Both ITSAMATCH and SYNTH achieved covariate balance and estimated similar treatment effects. The regression model found no treatment effect and produced inconsistent covariate adjustment. While the matching framework achieved results comparable to SYNTH, it has the advantage of being technically less complicated, while producing statistical estimates that are straightforward to interpret. Conversely, regression adjustment may "adjust away" a treatment effect. Given its advantages, ITSAMATCH should be considered as a primary approach for evaluating treatment effects in multiple-group time-series analysis. © 2017 John Wiley & Sons, Ltd.
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Cowlishaw, Sean; Suomi, Aino; Rodgers, Bryan
2016-09-01
To evaluate (1) whether gambling problems predict overall trajectories of change in family or interpersonal adjustment and (2) whether annual measures of gambling problems predict time-specific decreases in family or interpersonal adjustment, concurrently and prospectively. The Quinte Longitudinal Study (QLS) involved random-digit dialling of telephone numbers around the city of Belleville, Canada to recruit 'general population' and 'at-risk' groups (the latter oversampling people likely to develop problems). Five waves of assessment were conducted (2006-10). Latent Trajectory Modelling (LTM) estimated overall trajectories of family and interpersonal adjustment, which were predicted by gambling problems, and also estimated how time-specific problems predicted deviations from these trajectories. Southeast Ontario, Canada. Community sample of Canadian adults (n = 4121). The Problem Gambling Severity Index (PGSI) defined at-risk gambling (ARG: PGSI 1-2) and moderate-risk/problem gambling (MR/PG: PGSI 3+). Outcomes included: (1) family functioning, assessed using a seven-point rating of overall functioning; (2) social support, assessed using items from the Non-support subscale of the Personality Assessment Inventory; and (3) relationship satisfaction, measured by the Kansas Marital Satisfaction Scale. Baseline measures of ARG and MR/PG did not predict rates of change in trajectories of family or interpersonal adjustment. Rather, the annual measures of MR/PG predicted time-specific decreases in family functioning (estimate: -0.11, P < 0.01), social support (estimate: -0.28, P < 0.01) and relationship satisfaction (estimate: -0.53, P < 0.01). ARG predicted concurrent levels of family functioning (estimate: -0.07, P < 0.01). There were time-lagged effects of MR/PG on subsequent levels of family functioning (estimate: -0.12, P < 0.01) and social support (estimate: -0.24, P < 0.01). In a longitudinal study of Canadian adults, moderate-risk/problem gambling did not predict overall trajectories of family or interpersonal adjustment. Rather, the annual measures of moderate-risk/problem gambling predicted time-specific and concurrent decreases in all outcomes, and lower family functioning and social support across adjacent waves. © 2016 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.
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Galán, Iñaki; Simón, Lorena; Flores, Víctor; Ortiz, Cristina; Fernández-Cuenca, Rafael; Linares, Cristina; Boldo, Elena; Medrano, María José; Pastor-Barriuso, Roberto
2015-12-01
Recent research has assessed the impact of tobacco laws on cardiovascular and respiratory morbidity. In this study, we also examined whether the association between the implementation of the 2005 Spanish smoking ban and hospital admissions for cardiovascular and respiratory diseases varies according to the adjustment for potential confounders. Ecological time series analysis. Residents of Madrid and Barcelona cities (Spain). Data on daily emergency room admissions for acute myocardial infarction, cerebrovascular disease, chronic obstructive pulmonary disease (COPD), and asthma derived from the 2003-2006 Spanish hospital admissions registry. Changes in admission rates between 2006 and the 2003-2005 period were estimated using additive Poisson models allowing for overdispersion adjusted for secular trend in admission, seasonality, day of the week, temperature, number of flu and acute respiratory infection cases, pollution levels, tobacco consumption prevalence and, for asthma cases, pollen count. In Madrid, fully adjusted models failed to detect significant changes in hospital admission rates for any disease during the study period. In Barcelona, however, hospital admissions decreased by 10.2% (95% CI 3.8% to 16.1%) for cerebrovascular diseases and by 16.0% (95% CI 7.0% to 24.1%) for COPD. Substantial changes in effect estimates were observed on adjustment for linear or quadratic trend. Effect estimates for asthma-related admissions varied substantially when adjusting for pollen count in Madrid, and for seasonality and tobacco consumption in Barcelona. Our results confirm that the potential impact of a smoking ban must be adjusted for the underlying secular trend. In asthma-related admissions, pollen count, seasonality and tobacco consumption must be specified in the model. The substantial variability in effects detected between the two cities of Madrid and Barcelona lends strong support for a nationwide study to assess the overall effect of a smoking ban in Spain and identify the causes of the observed heterogeneity. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
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NASA Astrophysics Data System (ADS)
Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.
2015-09-01
Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.
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Design of DNA pooling to allow incorporation of covariates in rare variants analysis.
Guan, Weihua; Li, Chun
2014-01-01
Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect. For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique. Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes. Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.
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Unbiased Causal Inference from an Observational Study: Results of a Within-Study Comparison
ERIC Educational Resources Information Center
Pohl, Steffi; Steiner, Peter M.; Eisermann, Jens; Soellner, Renate; Cook, Thomas D.
2009-01-01
Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…
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Turner, Nikki; Pierse, Nevil; Bissielo, Ange; Huang, Q Sue; Baker, Michael; Widdowson, Marc-Alain; Kelly, Heath
2015-01-01
Background Few studies report the effectiveness of trivalent inactivated influenza vaccine (TIV) in preventing hospitalisation for influenza-confirmed respiratory infections. Using a prospective surveillance platform, this study reports the first such estimate from a well-defined ethnically diverse population in New Zealand (NZ). Methods A case test-negative study was used to estimate propensity adjusted vaccine effectiveness. Patients with a severe acute respiratory infection (SARI), defined as a patient of any age requiring hospitalization with a history of a fever or a measured temperature ≥38°C and cough and onset within the past 7 days, admitted to public hospitals in Central, South and East Auckland were eligible for inclusion in the study. Cases were SARI patients who tested positive for influenza, while non-cases (controls) were SARI patients who tested negative. Results were adjusted for the propensity to be vaccinated and the timing of the influenza season Results The propensity and season adjusted vaccine effectiveness (VE) was estimated as 37% (95% CI 18;51). The VE point estimate against influenza A (H1N1) was higher than for influenza B or influenza A (H3N2) but confidence intervals were wide and overlapping. Estimated VE was 51% (95% CI 28;67) in patients aged 18-64 years but only 6% (95% CI -51;42) in those aged 65 years and above. Conclusion Prospective surveillance for SARI has been successfully established in NZ . This study for the first year, the 2012 influenza season, has shown low to moderate protection by TIV against hospitalisation for laboratory-confirmed influenza. PMID:24768730
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Nuttall, David; Parkin, David; Devlin, Nancy
2015-01-01
This paper describes the development of a methodology for the case-mix adjustment of patient-reported outcome measures (PROMs) data permitting the comparison of outcomes between providers on a like-for-like basis. Statistical models that take account of provider-specific effects form the basis of the proposed case-mix adjustment methodology. Indirect standardisation provides a transparent means of case mix adjusting the PROMs data, which are updated on a monthly basis. Recently published PROMs data for patients undergoing unilateral knee replacement are used to estimate empirical models and to demonstrate the application of the proposed case-mix adjustment methodology in practice. The results are illustrative and are used to highlight a number of theoretical and empirical issues that warrant further exploration. For example, because of differences between PROMs instruments, case-mix adjustment methodologies may require instrument-specific approaches. A number of key assumptions are made in estimating the empirical models, which could be open to challenge. The covariates of post-operative health status could be expanded, and alternative econometric methods could be employed. © 2013 Crown copyright.
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Smooth individual level covariates adjustment in disease mapping.
Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise
2018-05-01
Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Robertson, David S; Prevost, A Toby; Bowden, Jack
2016-09-30
Seamless phase II/III clinical trials offer an efficient way to select an experimental treatment and perform confirmatory analysis within a single trial. However, combining the data from both stages in the final analysis can induce bias into the estimates of treatment effects. Methods for bias adjustment developed thus far have made restrictive assumptions about the design and selection rules followed. In order to address these shortcomings, we apply recent methodological advances to derive the uniformly minimum variance conditionally unbiased estimator for two-stage seamless phase II/III trials. Our framework allows for the precision of the treatment arm estimates to take arbitrary values, can be utilised for all treatments that are taken forward to phase III and is applicable when the decision to select or drop treatment arms is driven by a multiplicity-adjusted hypothesis testing procedure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
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Njai, Rashid; Siegel, Paul Z; Miller, Jacqueline W; Liao, Youlian
2011-05-01
The validity of self-reported data for mammography differ by race. We assessed the effect of racial differences in the validity of age-adjusted, self-reported mammography use estimates from the Behavioral Risk Factor Surveillance System (BRFSS) from 1995 through 2006 to determine whether misclassification (inaccurate survey question response) may have obscured actual racial disparities. We adjusted BRFSS mammography use data for age by using 2000 census estimates and for misclassification by using the following formula: (estimated prevalence - 1 + specificity) / (sensitivity + specificity - 1). We used values reported in the literature for the formula (sensitivity = 0.97 for both black and white women, specificity = 0.49 and 0.62, respectively, for black and white women). After adjustment for misclassification, the percentage of women aged 40 years or older in 1995 who reported receiving a mammogram during the previous 2 years was 54% among white women and 41% among black women, compared with 70% among both white and black women after adjustment for age only. In 2006, the percentage after adjustment for misclassification was 65% among white women and 59% among black women compared with 77% among white women and 78% among black women after adjustment for age only. Self-reported data overestimate mammography use - more so for black women than for white women. After adjustment for respondent misclassification, neither white women nor black women had attained the Healthy People 2010 objective (≥ 70%) by 2006, and a disparity between white and black women emerged.
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van der Pligt, J; van Schie, E C; Hoevenagel, R
1998-01-01
This paper addresses the effects of availability and anchoring-and-adjustment on people's beliefs and values concerning environmental issues. The first three studies focus on lay people's perceptions of the causes of large scale environmental risks, the second series of three studies deals with how people value environmental goods and how much they are prepared to pay to mitigate environmental risks. In studies 1-3 we investigate the effects of availability and anchoring-and-adjustment on estimating the contribution of various factors to large scale environmental risks. Highly complex risks such as acid rain and global warming tend to be associated with multiple causes, and our results show that estimating the role of these causes is clearly affected by availability and anchoring-and-adjustment. Both have sizeable effects and persist over time. Moreover, corrective procedures only seem to have a limited effect. Availability and anchoring-and-adjustment not only play a role in judging the possible causes of risks; they also play a role in research attempting to assess the public's willingness to pay (WTP) to protect our environment. The outcomes of WTP surveys are often used as a tool to help policy decision making. In the second part of this article we present three studies on this issue. Results provide further evidence of the impact of the two heuristics on the outcomes of WTP research. Implications for research and practice are briefly discussed.
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Estimating the effect of a rare time-dependent treatment on the recurrent event rate.
Smith, Abigail R; Zhu, Danting; Goodrich, Nathan P; Merion, Robert M; Schaubel, Douglas E
2018-05-30
In many observational studies, the objective is to estimate the effect of treatment or state-change on the recurrent event rate. If treatment is assigned after the start of follow-up, traditional methods (eg, adjustment for baseline-only covariates or fully conditional adjustment for time-dependent covariates) may give biased results. We propose a two-stage modeling approach using the method of sequential stratification to accurately estimate the effect of a time-dependent treatment on the recurrent event rate. At the first stage, we estimate the pretreatment recurrent event trajectory using a proportional rates model censored at the time of treatment. Prognostic scores are estimated from the linear predictor of this model and used to match treated patients to as yet untreated controls based on prognostic score at the time of treatment for the index patient. The final model is stratified on matched sets and compares the posttreatment recurrent event rate to the recurrent event rate of the matched controls. We demonstrate through simulation that bias due to dependent censoring is negligible, provided the treatment frequency is low, and we investigate a threshold at which correction for dependent censoring is needed. The method is applied to liver transplant (LT), where we estimate the effect of development of post-LT End Stage Renal Disease (ESRD) on rate of days hospitalized. Copyright © 2018 John Wiley & Sons, Ltd.
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Strak, Maciej; Janssen, Nicole; Beelen, Rob; Schmitz, Oliver; Karssenberg, Derek; Houthuijs, Danny; van den Brink, Carolien; Dijst, Martin; Brunekreef, Bert; Hoek, Gerard
2017-07-01
Cohorts based on administrative data have size advantages over individual cohorts in investigating air pollution risks, but often lack in-depth information on individual risk factors related to lifestyle. If there is a correlation between lifestyle and air pollution, omitted lifestyle variables may result in biased air pollution risk estimates. Correlations between lifestyle and air pollution can be induced by socio-economic status affecting both lifestyle and air pollution exposure. Our overall aim was to assess potential confounding by missing lifestyle factors on air pollution mortality risk estimates. The first aim was to assess associations between long-term exposure to several air pollutants and lifestyle factors. The second aim was to assess whether these associations were sensitive to adjustment for individual and area-level socioeconomic status (SES), and whether they differed between subgroups of the population. Using the obtained air pollution-lifestyle associations and indirect adjustment methods, our third aim was to investigate the potential bias due to missing lifestyle information on air pollution mortality risk estimates in administrative cohorts. We used a recent Dutch national health survey of 387,195 adults to investigate the associations of PM 10 , PM 2.5 , PM 2.5-10 , PM 2.5 absorbance, OP DTT, OP ESR and NO 2 annual average concentrations at the residential address from land use regression models with individual smoking habits, alcohol consumption, physical activity and body mass index. We assessed the associations with and without adjustment for neighborhood and individual SES characteristics typically available in administrative data cohorts. We illustrated the effect of including lifestyle information on the air pollution mortality risk estimates in administrative cohort studies using a published indirect adjustment method. Current smoking and alcohol consumption were generally positively associated with air pollution. Physical activity and overweight were negatively associated with air pollution. The effect estimates were small (mostly <5% of the air pollutant standard deviations). Direction and magnitude of the associations depended on the pollutant, use of continuous vs. categorical scale of the lifestyle variable, and level of adjustment for individual and area-level SES. Associations further differed between subgroups (age, sex) in the population. Despite the small associations between air pollution and smoking intensity, indirect adjustment resulted in considerable changes of air pollution risk estimates for cardiovascular and especially lung cancer mortality. Individual lifestyle-related risk factors were weakly associated with long-term exposure to air pollution in the Netherlands. Indirect adjustment for missing lifestyle factors in administrative data cohort studies may substantially affect air pollution mortality risk estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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Using the Human Eye to Characterize Displays
NASA Technical Reports Server (NTRS)
Gille, Jennifer; Larimer, James
2001-01-01
Monitor characterization has taken on new importance for non-professional users, who are not usually equipped to make photometric measurements. Our purpose was to examine some of the visual judgments used in characterization schemes that have been proposed for web users. We studied adjusting brightness to set the black level, banding effects due to digitization, and gamma estimation in the light and in the dark, and a color-matching task in the light, on a desktop CRT and a laptop LCD. Observers demonstrated the sensitivity of the visual system for comparative judgments in black-level adjustment, banding visibility, and gamma estimation. The results of the color-matching task were ambiguous. In the brightness adjustment task, the action of the adjustment was not as presumed; however, perceptual judgments were as expected under the actual conditions. When the gamma estimates of observers were compared to photometric measurements, problems with the definition of gamma were identified. Information about absolute light levels that would be important for characterizing a display, given the shortcomings of gamma in measuring apparent contrast, are not measurable by eye alone. The LCD was not studied as extensively as the CRT because of viewing-angle problems, and its transfer function did not follow a power law, rendering gamma estimation meaningless.
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Diallel analysis for sex-linked and maternal effects.
Zhu, J; Weir, B S
1996-01-01
Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.
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Austin, Peter C
2018-01-01
Propensity score methods are frequently used to estimate the effects of interventions using observational data. The propensity score was originally developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (e.g. pack-years of cigarettes smoked, dose of medication, or years of education). We describe how the GPS can be used to estimate the effect of continuous exposures on survival or time-to-event outcomes. To do so we modified the concept of the dose-response function for use with time-to-event outcomes. We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of quantitative exposures on survival or time-to-event outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. The use of methods based on the GPS was compared with the use of conventional G-computation and weighted G-computation. Conventional G-computation resulted in estimates of the dose-response function that displayed the lowest bias and the lowest variability. Amongst the two GPS-based methods, covariate adjustment using the GPS tended to have the better performance. We illustrate the application of these methods by estimating the effect of average neighbourhood income on the probability of survival following hospitalization for an acute myocardial infarction.
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Stey, Anne M; Brook, Robert H; Needleman, Jack; Hall, Bruce L; Zingmond, David S; Lawson, Elise H; Ko, Clifford Y
2015-02-01
This study aims to describe the magnitude of hospital costs among patients undergoing elective colectomy, cholecystectomy, and pancreatectomy, determine whether these costs relate as expected to duration of care, patient case-mix severity and comorbidities, and whether risk-adjusted costs vary significantly by hospital. Correctly estimating the cost of production of surgical care may help decision makers design mechanisms to improve the efficiency of surgical care. Patient data from 202 hospitals in the ACS-NSQIP were linked to Medicare inpatient claims. Patient charges were mapped to cost center cost-to-charge ratios in the Medicare cost reports to estimate costs. The association of patient case-mix severity and comorbidities with cost was analyzed using mixed effects multivariate regression. Cost variation among hospitals was quantified by estimating risk-adjusted hospital cost ratios and 95% confidence intervals from the mixed effects multivariate regression. There were 21,923 patients from 202 hospitals who underwent an elective colectomy (n = 13,945), cholecystectomy (n = 5,569), or pancreatectomy (n = 2,409). Median cost was lowest for cholecystectomy ($15,651) and highest for pancreatectomy ($37,745). Room and board costs accounted for the largest proportion (49%) of costs and were correlated with length of stay, R = 0.89, p < 0.001. The patient case-mix severity and comorbidity variables most associated with cost were American Society of Anesthesiologists (ASA) class IV (estimate 1.72, 95% CI 1.57 to 1.87) and fully dependent functional status (estimate 1.63, 95% CI 1.53 to 1.74). After risk-adjustment, 66 hospitals had significantly lower costs than the average hospital and 57 hospitals had significantly higher costs. The hospital costs estimates appear to be consistent with clinical expectations of hospital resource use and differ significantly among 202 hospitals after risk-adjustment for preoperative patient characteristics and procedure type. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
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ERIC Educational Resources Information Center
Roberts, Greg; Mohammed, Sarojani S.; Vaughn, Sharon
2010-01-01
This study estimated normative reading trajectories for the population of English-proficient language minority students attending U.S. public elementary schools. Achievement of English-language learners (ELLs) was evaluated in terms of native English speakers' progress, and estimates were adjusted for the effects of socioeconomic status (SES). The…
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The health-related social costs of alcohol in Belgium.
Verhaeghe, Nick; Lievens, Delfine; Annemans, Lieven; Vander Laenen, Freya; Putman, Koen
2017-12-16
Alcohol is associated with adverse health effects causing a considerable economic impact to society. A reliable estimate of this economic impact for Belgium is lacking. This is the aim of the study. A prevalence-based approach estimating the direct, indirect and intangible costs for the year 2012 was used. Attributional fractions for a series of health effects were derived from literature. The human capital approach was used to estimate indirect costs, while the concept of disability-adjusted life years was used to estimate intangible costs. Sensitivity and scenario analyses were conducted to assess the uncertainty around cost estimates and to evaluate the impact of alternative modelling assumptions. In 2012, total alcohol-attributable direct costs were estimated at €906.1 million, of which the majority were due to hospitalization (€743.7 million, 82%). The indirect costs amounted to €642.6 million, of which 62% was caused by premature mortality. Alcohol was responsible for 157,500 disability-adjusted life years representing €6.3 billion intangible costs. Despite a number of limitations intrinsic to this kind of research, the study can be considered as the most comprehensive analysis thus far of the health-related social costs of alcohol in Belgium.
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Shimura, Masashi; Maruo, Kazushi; Gosho, Masahiko
2018-04-23
Two-stage designs are widely used to determine whether a clinical trial should be terminated early. In such trials, a maximum likelihood estimate is often adopted to describe the difference in efficacy between the experimental and reference treatments; however, this method is known to display conditional bias. To reduce such bias, a conditional mean-adjusted estimator (CMAE) has been proposed, although the remaining bias may be nonnegligible when a trial is stopped for efficacy at the interim analysis. We propose a new estimator for adjusting the conditional bias of the treatment effect by extending the idea of the CMAE. This estimator is calculated by weighting the maximum likelihood estimate obtained at the interim analysis and the effect size prespecified when calculating the sample size. We evaluate the performance of the proposed estimator through analytical and simulation studies in various settings in which a trial is stopped for efficacy or futility at the interim analysis. We find that the conditional bias of the proposed estimator is smaller than that of the CMAE when the information time at the interim analysis is small. In addition, the mean-squared error of the proposed estimator is also smaller than that of the CMAE. In conclusion, we recommend the use of the proposed estimator for trials that are terminated early for efficacy or futility. Copyright © 2018 John Wiley & Sons, Ltd.
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2014-01-01
Background The reduction of crime is an important outcome of opioid maintenance treatment (OMT). Criminal intensity and treatment regimes vary among OMT patients, but this is rarely adjusted for in statistical analyses, which tend to focus on cohort incidence rates and rate ratios. The purpose of this work was to estimate the relationship between treatment and criminal convictions among OMT patients, adjusting for individual covariate information and timing of events, fitting time-to-event regression models of increasing complexity. Methods National criminal records were cross linked with treatment data on 3221 patients starting OMT in Norway 1997–2003. In addition to calculating cohort incidence rates, criminal convictions was modelled as a recurrent event dependent variable, and treatment a time-dependent covariate, in Cox proportional hazards, Aalen’s additive hazards, and semi-parametric additive hazards regression models. Both fixed and dynamic covariates were included. Results During OMT, the number of days with criminal convictions for the cohort as a whole was 61% lower than when not in treatment. OMT was associated with reduced number of days with criminal convictions in all time-to-event regression models, but the hazard ratio (95% CI) was strongly attenuated when adjusting for covariates; from 0.40 (0.35, 0.45) in a univariate model to 0.79 (0.72, 0.87) in a fully adjusted model. The hazard was lower for females and decreasing with older age, while increasing with high numbers of criminal convictions prior to application to OMT (all p < 0.001). The strongest predictors were level of criminal activity prior to entering into OMT, and having a recent criminal conviction (both p < 0.001). The effect of several predictors was significantly time-varying with their effects diminishing over time. Conclusions Analyzing complex observational data regarding to fixed factors only overlooks important temporal information, and naïve cohort level incidence rates might result in biased estimates of the effect of interventions. Applying time-to-event regression models, properly adjusting for individual covariate information and timing of various events, allows for more precise and reliable effect estimates, as well as painting a more nuanced picture that can aid health care professionals and policy makers. PMID:24886472
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The impact of HIV and ART on recurrent tuberculosis in a sub-Saharan setting.
Houben, Rein M G J; Glynn, Judith R; Mboma, Sebastian; Mzemba, Themba; Mwaungulu, Nimrod J; Mwaungulu, Lorren; Mwenibabu, Michael; Mpunga, James; French, Neil; Crampin, Amelia C
2012-11-13
To estimate the impact of antiretroviral therapy (ART) on the incidence of recurrent tuberculosis (TB) in an African population. A long-term population cohort in Karonga District, northern Malawi. Patients who had completed treatment for laboratory-confirmed TB diagnosed since 1996 were visited annually to record vital status, ART use and screen for TB. Survival analysis estimated the effect of HIV/ART status at completion of treatment on mortality and recurrence. Analyses were stratified by time since treatment completion to estimate the effects on relapse (predominates during first year) and reinfection disease (predominates later). Among 1133 index TB cases contributing 4353 person-years of follow-up, there were 307 deaths and 103 laboratory-confirmed recurrences (recurrence rate 4.6 per 100 person-years). Half the recurrences occurred in the first year since completing treatment. HIV infection increased the recurrence rate [rate ratio adjusted for age, sex, period and TB type 2.69, 95% confidence interval (CI) 1.69-4.26], but with less effect in the first year (adjusted rate ratio 1.71, 95% CI 0.87-3.35) than subsequently (adjusted rate ratio 4.2, 95% CI 2.16-8.15). Recurrence rates on ART were intermediate between those of HIV-negative individuals and HIV-positive individuals without ART. Compared with HIV-positive individuals without ART, the adjusted rate ratio was 0.74 (95% CI 0.27-2.06) in the first year, and 0.43 (95% CI 0.11-1.73) later. The increased incidence of TB recurrence observed in HIV-positive patients appeared to be reduced by ART. The effects are mostly on later (likely reinfection) disease so the impact of ART on reducing recurrence will be highest in high TB incidence settings.
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2018-01-01
Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (eg, dose or quantity of medication, income, or years of education). We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of continuous exposures on binary outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. We examined both the use of ordinary least squares to estimate the propensity function and the use of the covariate balancing propensity score algorithm. The use of methods based on the GPS was compared with the use of G‐computation. All methods resulted in essentially unbiased estimation of the population dose‐response function. However, GPS‐based weighting tended to result in estimates that displayed greater variability and had higher mean squared error when the magnitude of confounding was strong. Of the methods based on the GPS, covariate adjustment using the GPS tended to result in estimates with lower variability and mean squared error when the magnitude of confounding was strong. We illustrate the application of these methods by estimating the effect of average neighborhood income on the probability of death within 1 year of hospitalization for an acute myocardial infarction. PMID:29508424
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Austin, Peter C
2018-05-20
Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (eg, dose or quantity of medication, income, or years of education). We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of continuous exposures on binary outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. We examined both the use of ordinary least squares to estimate the propensity function and the use of the covariate balancing propensity score algorithm. The use of methods based on the GPS was compared with the use of G-computation. All methods resulted in essentially unbiased estimation of the population dose-response function. However, GPS-based weighting tended to result in estimates that displayed greater variability and had higher mean squared error when the magnitude of confounding was strong. Of the methods based on the GPS, covariate adjustment using the GPS tended to result in estimates with lower variability and mean squared error when the magnitude of confounding was strong. We illustrate the application of these methods by estimating the effect of average neighborhood income on the probability of death within 1 year of hospitalization for an acute myocardial infarction. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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NASA Astrophysics Data System (ADS)
Helman, David; Lensky, Itamar M.; Osem, Yagil; Rohatyn, Shani; Rotenberg, Eyal; Yakir, Dan
2017-09-01
Estimations of ecosystem-level evapotranspiration (ET) and CO2 uptake in water-limited environments are scarce and scaling up ground-level measurements is not straightforward. A biophysical approach using remote sensing (RS) and meteorological data (RS-Met) is adjusted to extreme high-energy water-limited Mediterranean ecosystems that suffer from continuous stress conditions to provide daily estimations of ET and CO2 uptake (measured as gross primary production, GPP) at a spatial resolution of 250 m. The RS-Met was adjusted using a seasonal water deficit factor (fWD) based on daily rainfall, temperature and radiation data. We validated our adjusted RS-Met with eddy covariance flux measurements using a newly developed mobile lab system and the single active FLUXNET station operating in this region (Yatir pine forest station) at a total of seven forest and non-forest sites across a climatic transect in Israel (280-770 mm yr-1). RS-Met was also compared to the satellite-borne MODIS-based ET and GPP products (MOD16 and MOD17, respectively) at these sites.Results show that the inclusion of the fWD significantly improved the model, with R = 0.64-0.91 for the ET-adjusted model (compared to 0.05-0.80 for the unadjusted model) and R = 0.72-0.92 for the adjusted GPP model (compared to R = 0.56-0.90 of the non-adjusted model). The RS-Met (with the fWD) successfully tracked observed changes in ET and GPP between dry and wet seasons across the sites. ET and GPP estimates from the adjusted RS-Met also agreed well with eddy covariance estimates on an annual timescale at the FLUXNET station of Yatir (266 ± 61 vs. 257 ± 58 mm yr-1 and 765 ± 112 vs. 748 ± 124 gC m-2 yr-1 for ET and GPP, respectively). Comparison with MODIS products showed consistently lower estimates from the MODIS-based models, particularly at the forest sites. Using the adjusted RS-Met, we show that afforestation significantly increased the water use efficiency (the ratio of carbon uptake to ET) in this region, with the positive effect decreasing when moving from dry to more humid environments, strengthening the importance of drylands afforestation. This simple yet robust biophysical approach shows promise for reliable ecosystem-level estimations of ET and CO2 uptake in extreme high-energy water-limited environments.
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Spatial variability effects on precision and power of forage yield estimation
USDA-ARS?s Scientific Manuscript database
Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...
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Price, A.; Peterson, James T.
2010-01-01
Stream fish managers often use fish sample data to inform management decisions affecting fish populations. Fish sample data, however, can be biased by the same factors affecting fish populations. To minimize the effect of sample biases on decision making, biologists need information on the effectiveness of fish sampling methods. We evaluated single-pass backpack electrofishing and seining combined with electrofishing by following a dual-gear, mark–recapture approach in 61 blocknetted sample units within first- to third-order streams. We also estimated fish movement out of unblocked units during sampling. Capture efficiency and fish abundances were modeled for 50 fish species by use of conditional multinomial capture–recapture models. The best-approximating models indicated that capture efficiencies were generally low and differed among species groups based on family or genus. Efficiencies of single-pass electrofishing and seining combined with electrofishing were greatest for Catostomidae and lowest for Ictaluridae. Fish body length and stream habitat characteristics (mean cross-sectional area, wood density, mean current velocity, and turbidity) also were related to capture efficiency of both methods, but the effects differed among species groups. We estimated that, on average, 23% of fish left the unblocked sample units, but net movement varied among species. Our results suggest that (1) common warmwater stream fish sampling methods have low capture efficiency and (2) failure to adjust for incomplete capture may bias estimates of fish abundance. We suggest that managers minimize bias from incomplete capture by adjusting data for site- and species-specific capture efficiency and by choosing sampling gear that provide estimates with minimal bias and variance. Furthermore, if block nets are not used, we recommend that managers adjust the data based on unconditional capture efficiency.
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Income Elasticity Literature Review | Science Inventory | US ...
Following advice from the SAB Council, when estimating the economic value of reductions in air pollution-related mortality and morbidity risk, EPA accounts for the effect of personal income on the willingness to pay to reduce the risk of adverse health outcomes. These income growth adjustment factors are calculated using a combination of income elasticity estimates and income growth projections, both of which have remained essentially unchanged since 1999. These income elasticity estimates vary according to the severity of illness. EPA recently received advice from the SAB regarding the range of income elasticities to apply as well as the research standards to use when selecting income elasticity estimates. Following this advice, EPA consulted with a contractor to update its income elasticity and income growth projections, and generate new income growth adjustment factors. The SAB would evaluate the income elasticity estimates identified in the EPA-provided literature review, determining the extent to which these estimates are appropriate to use in human health benefits assessments.
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NASA Astrophysics Data System (ADS)
Yamana, Teresa K.; Eltahir, Elfatih A. B.
2011-02-01
This paper describes the use of satellite-based estimates of rainfall to force the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a hydrology-based mechanistic model of malaria transmission. We first examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 h resolution. We then investigated whether HYDREMATS could be effectively forced by satellite-based estimates of rainfall instead of ground-based observations. The Climate Prediction Center morphing technique (CMORPH) precipitation estimates distributed by the National Oceanic and Atmospheric Administration are available at a 30 min temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results demonstrate that adjusted rainfall estimates from satellites can be used with a mechanistic model to accurately simulate the dynamics of mosquito populations.
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Exploring the willingness to pay for a quality-adjusted life-year in the state of Penang, Malaysia
Shafie, Asrul Akmal; Lim, Yen Wei; Chua, Gin Nie; Hassali, Mohammed Azmi Ahmad
2014-01-01
Introduction The incremental cost-effectiveness ratio (ICER) is typically compared with a reference value to support the cost-effectiveness of a decision. One method for estimating this value is to estimate the willingness-to-pay (WTP) for a quality-adjusted life-year (QALY). This study was conducted to explore the WTP for a QALY in the Malaysian population. Methods A cross-sectional, contingent valuation study was conducted in Penang, Malaysia. Respondents were selected from randomly chosen geographical grids of Penang. Respondents’ sociodemographic information, qualities of life, and WTP for one additional QALY were collected using predesigned questionnaires in face-to-face interviews. WTP values were elicited using a double-bound dichotomous choice via a bidding game approach. The Heckman selection model was applied to the analysis of the mean WTP/QALY values, where the “protest zero” values, which may contribute to selection bias, were excluded. Results The mean value of WTP for an additional QALY gained was estimated to be MYR (Malaysian Ringgit) 29,080 (~USD 9,000). Key factors that affected the WTP include ethnicity and estimated monthly household income. Conclusion The study findings suggested that the cost-effectiveness threshold value as studied in Penang, Malaysia was estimated to be MYR 29,080. PMID:25364267
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Exploring the willingness to pay for a quality-adjusted life-year in the state of Penang, Malaysia.
Shafie, Asrul Akmal; Lim, Yen Wei; Chua, Gin Nie; Hassali, Mohammed Azmi Ahmad
2014-01-01
The incremental cost-effectiveness ratio (ICER) is typically compared with a reference value to support the cost-effectiveness of a decision. One method for estimating this value is to estimate the willingness-to-pay (WTP) for a quality-adjusted life-year (QALY). This study was conducted to explore the WTP for a QALY in the Malaysian population. A cross-sectional, contingent valuation study was conducted in Penang, Malaysia. Respondents were selected from randomly chosen geographical grids of Penang. Respondents' sociodemographic information, qualities of life, and WTP for one additional QALY were collected using predesigned questionnaires in face-to-face interviews. WTP values were elicited using a double-bound dichotomous choice via a bidding game approach. The Heckman selection model was applied to the analysis of the mean WTP/QALY values, where the "protest zero" values, which may contribute to selection bias, were excluded. The mean value of WTP for an additional QALY gained was estimated to be MYR (Malaysian Ringgit) 29,080 (~USD 9,000). Key factors that affected the WTP include ethnicity and estimated monthly household income. The study findings suggested that the cost-effectiveness threshold value as studied in Penang, Malaysia was estimated to be MYR 29,080.
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Senn, Stephen; Graf, Erika; Caputo, Angelika
2007-12-30
Stratifying and matching by the propensity score are increasingly popular approaches to deal with confounding in medical studies investigating effects of a treatment or exposure. A more traditional alternative technique is the direct adjustment for confounding in regression models. This paper discusses fundamental differences between the two approaches, with a focus on linear regression and propensity score stratification, and identifies points to be considered for an adequate comparison. The treatment estimators are examined for unbiasedness and efficiency. This is illustrated in an application to real data and supplemented by an investigation on properties of the estimators for a range of underlying linear models. We demonstrate that in specific circumstances the propensity score estimator is identical to the effect estimated from a full linear model, even if it is built on coarser covariate strata than the linear model. As a consequence the coarsening property of the propensity score-adjustment for a one-dimensional confounder instead of a high-dimensional covariate-may be viewed as a way to implement a pre-specified, richly parametrized linear model. We conclude that the propensity score estimator inherits the potential for overfitting and that care should be taken to restrict covariates to those relevant for outcome. Copyright (c) 2007 John Wiley & Sons, Ltd.
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The Cost-Effectiveness of Antibiotic Prophylaxis for Patients at Risk of Infective Endocarditis.
Franklin, Matthew; Wailoo, Allan; Dayer, Mark J; Jones, Simon; Prendergast, Bernard; Baddour, Larry M; Lockhart, Peter B; Thornhill, Martin H
2016-11-15
In March 2008, the National Institute for Health and Care Excellence recommended stopping antibiotic prophylaxis (AP) for those at risk of infective endocarditis (IE) undergoing dental procedures in the United Kingdom, citing a lack of evidence of efficacy and cost-effectiveness. We have performed a new economic evaluation of AP on the basis of contemporary estimates of efficacy, adverse events, and resource implications. A decision analytic cost-effectiveness model was used. Health service costs and benefits (measured as quality-adjusted life-years) were estimated. Rates of IE before and after the National Institute for Health and Care Excellence guidance were available to estimate prophylactic efficacy. AP adverse event rates were derived from recent UK data, and resource implications were based on English Hospital Episode Statistics. AP was less costly and more effective than no AP for all patients at risk of IE. The results are sensitive to AP efficacy, but efficacy would have to be substantially lower for AP not to be cost-effective. AP was even more cost-effective in patients at high risk of IE. Only a marginal reduction in annual IE rates (1.44 cases in high-risk and 33 cases in all at-risk patients) would be required for AP to be considered cost-effective at £20 000 ($26 600) per quality-adjusted life-year. Annual cost savings of £5.5 to £8.2 million ($7.3-$10.9 million) and health gains >2600 quality-adjusted life-years could be achieved from reinstating AP in England. AP is cost-effective for preventing IE, particularly in those at high risk. These findings support the cost-effectiveness of guidelines recommending AP use in high-risk individuals. © 2016 The Authors.
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Riedel, Christina; Schönberger, Katharina; Yang, Seungmi; Koshy, Gibby; Chen, Yang-Ching; Gopinath, Bamini; Ziebarth, Stephanie; von Kries, Rüdiger
2014-10-01
Some studies reported similar effect estimates for the impact of maternal smoking in pregnancy and paternal smoking on childhood obesity, whereas others suggested higher effects for maternal smoking. We performed a meta-analysis to compare the effect of in utero exposure to maternal smoking and that of paternal or household smoking exposure in utero or after birth with mutual adjustment. Meta-analysis of observational studies identified in MEDLINE, EMBASE and Web of Knowledge published in 1900-2013. Study inclusion criterion was assessment of the association of maternal smoking during pregnancy and paternal or household smoking (anyone living in the household who smokes) at any time with childhood overweight and obesity. The analyses were based on all studies with mutually adjusted effect estimates for maternal and paternal/household smoking applying a random-effects model. Data for 109,838 mother/child pairs were reported in 12 studies. The pooled odds ratios (ORs) for overweight 1.33 [95% confidence interval (CI) 1.23;1.44] (n=6, I2=0.00%) and obesity 1.60 (95% CI 1.37;1.88) (n=4, I2=32.47%) for maternal smoking during pregnancy were higher than for paternal smoking: 1.07 (95% CI 1.00;1.16) (n=6, I2=41.34%) and 1.23 (95% CI 1.10;1.38) (n=4, I2=14.61%), respectively. Similar estimates with widely overlapping confidence limits were found for maternal smoking during pregnancy and childhood overweight and obesity: 1.35 (95% CI 1.20;1.51) (n=3, I2=0.00%) and 1.28 (95% CI 1.07;1.54) (n=3, I2=0.00%) compared with household smoking 1.22 (95% CI 1.06;1.39) (n=3, I2=72.14%) and 1.31 (95% CI 1.15;1.50)] (n=3, I2=0.00%). Higher effect estimates for maternal smoking in pregnancy compared with paternal smoking in mutually adjusted models may suggest a direct intrauterine effect. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Mauskopf, Josephine; Chirila, Costel; Birt, Julie; Boye, Kristina S; Bowman, Lee
2013-04-01
Determine whether reimbursement restrictions recommended by the National Institute for Health and Clinical Excellence (NICE) have impacted the United Kingdom (UK) National Health Service (NHS) budget. Data were abstracted from NICE guidance documents and costing statements through March 2011. Estimated maximum and adjusted potential budget impact (PBI) on the NHS was derived using estimates of the UK marketing-approved population and the annual cost for the new drug. Descriptive and logistic analyses were used to estimate the correlation between the degree of restrictions on reimbursement recommended by NICE for each new drug indication and the PBI controlling for clinical effectiveness and cost-effectiveness. PBI was significantly correlated with the degree of reimbursement restrictions. In descriptive analysis, the adjusted PBI for drugs that were recommended without restrictions was £20.3 million (SD = 22.2) compared with £49.8 million (SD = 90.8) for those recommended with restrictions and £71.1 million (SE = 99.9) for those not recommended. In logistic analysis, the odds ratio for less restrictive reimbursement was 0.848 (95% CI, 0.762-0.945) for each £20 million increase in the adjusted PBI. Results were similar using the maximum PBI. After controlling for clinical effectiveness and cost-effectiveness, the degree of reimbursement restriction recommended by NICE remains significantly correlated with the PBI, despite that fact that the NICE decision process does not consider budget impact. This correlation might be due to NICE consideration of effectiveness and cost-effectiveness for subgroups of the approved population. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
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Dieleman, Joseph L; Baral, Ranju; Johnson, Elizabeth; Bulchis, Anne; Birger, Maxwell; Bui, Anthony L; Campbell, Madeline; Chapin, Abigail; Gabert, Rose; Hamavid, Hannah; Horst, Cody; Joseph, Jonathan; Lomsadze, Liya; Squires, Ellen; Tobias, Martin
2017-08-29
One of the major challenges in estimating health care spending spent on each cause of illness is allocating spending for a health care event to a single cause of illness in the presence of comorbidities. Comorbidities, the secondary diagnoses, are common across many causes of illness and often correlate with worse health outcomes and more expensive health care. In this study, we propose a method for measuring the average spending for each cause of illness with and without comorbidities. Our strategy for measuring cause of illness-specific spending and adjusting for the presence of comorbidities uses a regression-based framework to estimate excess spending due to comorbidities. We consider multiple causes simultaneously, allowing causes of illness to appear as either a primary diagnosis or a comorbidity. Our adjustment method distributes excess spending away from primary diagnoses (outflows), exaggerated due to the presence of comorbidities, and allocates that spending towards causes of illness that appear as comorbidities (inflows). We apply this framework for spending adjustment to the National Inpatient Survey data in the United States for years 1996-2012 to generate comorbidity-adjusted health care spending estimates for 154 causes of illness by age and sex. The primary diagnoses with the greatest number of comorbidities in the NIS dataset were acute renal failure, septicemia, and endocarditis. Hypertension, diabetes, and ischemic heart disease were the most common comorbidities across all age groups. After adjusting for comorbidities, chronic kidney diseases, atrial fibrillation and flutter, and chronic obstructive pulmonary disease increased by 74.1%, 40.9%, and 21.0%, respectively, while pancreatitis, lower respiratory infections, and septicemia decreased by 21.3%, 17.2%, and 16.0%. For many diseases, comorbidity adjustments had varying effects on spending for different age groups. Our methodology takes a unified approach to account for excess spending caused by the presence of comorbidities. Adjusting for comorbidities provides a substantially altered, more accurate estimate of the spending attributed to specific cause of illness. Making these adjustments supports improved resource tracking, accountability, and planning for future resource allocation.
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Candel, Math J J M; Van Breukelen, Gerard J P
2010-06-30
Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.
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Price Elasticity of Alcohol Demand in India.
Kumar, Santosh
2017-05-01
Using a household survey conducted in 2014, this study estimates price elasticity of demand (PED) for beer, country liquor and spirits in India. Ordinary least-square models were used to estimate the responsiveness in alcohol demand due to price change. A large number of control variables were included to adjust for potential confounding in the model. Inter-district variation in alcohol consumption is adjusted for by including district fixed effects. Alcohol prices are negatively associated with demand for alcoholic beverages. The PED ranged from -0.14 for spirits to -0.46 for country liquor. Low level of education was positively associated with spirits consumption. The magnitude of elasticity varied by rural-urban, education and gender. Results indicate that a policy mix of price controls and awareness campaigns would be most effective in tackling the adverse effects of harmful drinking in India. The demand for beer, country liquor and spirits is negatively associated with its own price. The elasticity estimates ranged from -0.14 for spirits to -0.44 for country liquor. The elasticity estimates varied by rural-urban, gender and by education levels of the drinkers. © The Author 2017. Medical Council on Alcohol and Oxford University Press. All rights reserved
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Gustafson, Paul; Gilbert, Mark; Xia, Michelle; Michelow, Warren; Robert, Wayne; Trussler, Terry; McGuire, Marissa; Paquette, Dana; Moore, David M; Gustafson, Reka
2013-05-15
Venue sampling is a common sampling method for populations of men who have sex with men (MSM); however, men who visit venues frequently are more likely to be recruited. While statistical adjustment methods are recommended, these have received scant attention in the literature. We developed a novel approach to adjust for frequency of venue attendance (FVA) and assess the impact of associated bias in the ManCount Study, a venue-based survey of MSM conducted in Vancouver, British Columbia, Canada, in 2008-2009 to measure the prevalence of human immunodeficiency virus and other infections and associated behaviors. Sampling weights were determined from an abbreviated list of questions on venue attendance and were used to adjust estimates of prevalence for health and behavioral indicators using a Bayesian, model-based approach. We found little effect of FVA adjustment on biological or sexual behavior indicators (primary outcomes); however, adjustment for FVA did result in differences in the prevalence of demographic indicators, testing behaviors, and a small number of additional variables. While these findings are reassuring and lend credence to unadjusted prevalence estimates from this venue-based survey, adjustment for FVA did shed important insights on MSM subpopulations that were not well represented in the sample.
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MIXOR: a computer program for mixed-effects ordinal regression analysis.
Hedeker, D; Gibbons, R D
1996-03-01
MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.
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Respirator use and its impact on particulate matter exposure in aluminum manufacturing facilities.
Liu, Sa; Noth, Elizabeth; Eisen, Ellen; Cullen, Mark R; Hammond, Katharine
2018-05-31
Objectives As part of a large epidemiologic study of particulate health effect, this study aimed to report respirator use among total particulate matter (TPM) samples collected in a major aluminum manufacturing company from 1966‒2013 and evaluate the impact of respirator-use adjustment on exposure estimation. Methods Descriptive analyses were performed to evaluate respirator use across facilities and by facility type and job. Protection factors were applied to TPM measurements for recorded respirator use. Estimated TPM exposure for each job ‒ before and after respirator-use adjustment ‒ were compared to assess the impact of adjustment on exposure estimation. Results Respirator use was noted for 37% of 12 402 full-shift personal TPM samples. Measured TPM concentration ranged from less than detectable to 8220 mg/m3, with arithmetic mean, median and standard deviation being 10.6, 0.87 and 130 mg/m 3 , respectively. Respirators were used more often in smelting facilities (52% of TPM measurements) than in fabricating (17%) or refinery facilities (28%) (P<0.01). Sixty-two percent of jobs in smelting facilities were subject to respirator-use adjustment, whereas it was 20% and 70% in fabricating and refinery facilities, respectively. Applying protection factors to TPM measurements significantly reduced estimated job mean TPM exposures and changed exposure categories in these facilities, with larger impact in smelting than fabricating facilities. Conclusions Respirator use varied by time, facility and job. Adjusting respirator use resulted in differential impact in smelting and fabricating facilities, which will need to be incorporated into ongoing epidemiologic studies accordingly.
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Measuring Child Work and Residence Adjustments to Parents' Long-Term Care Needs.
ERIC Educational Resources Information Center
Stern, Steven
1996-01-01
Estimates the effects of various parent and child characteristics on the choice of care arrangement of the parent, taking into account the potential endogeneity of some of the child characteristics. Three equations are estimated: care choice, child location, and child work. Results suggest a hierarchy of family decision making; child locations…
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Wang, Li-Pen; Ochoa-Rodríguez, Susana; Simões, Nuno Eduardo; Onof, Christian; Maksimović, Cedo
2013-01-01
The applicability of the operational radar and raingauge networks for urban hydrology is insufficient. Radar rainfall estimates provide a good description of the spatiotemporal variability of rainfall; however, their accuracy is in general insufficient. It is therefore necessary to adjust radar measurements using raingauge data, which provide accurate point rainfall information. Several gauge-based radar rainfall adjustment techniques have been developed and mainly applied at coarser spatial and temporal scales; however, their suitability for small-scale urban hydrology is seldom explored. In this paper a review of gauge-based adjustment techniques is first provided. After that, two techniques, respectively based upon the ideas of mean bias reduction and error variance minimisation, were selected and tested using as case study an urban catchment (∼8.65 km(2)) in North-East London. The radar rainfall estimates of four historical events (2010-2012) were adjusted using in situ raingauge estimates and the adjusted rainfall fields were applied to the hydraulic model of the study area. The results show that both techniques can effectively reduce mean bias; however, the technique based upon error variance minimisation can in general better reproduce the spatial and temporal variability of rainfall, which proved to have a significant impact on the subsequent hydraulic outputs. This suggests that error variance minimisation based methods may be more appropriate for urban-scale hydrological applications.
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Guy, S Z Y; Li, L; Thomson, P C; Hermesch, S
2017-12-01
Environmental descriptors derived from mean performances of contemporary groups (CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia (n = 31,230). Firstly, CG estimates of average daily gain (ADG) and backfat (BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model (p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a practical approach for the genetic improvement of disease resilience. © 2017 Blackwell Verlag GmbH.
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Vågerö, Denny; Garcy, Anthony M
2016-10-01
Mass unemployment in Europe is endemic, especially among the young. Does it cause mortality? We analyzed long-term effects of unemployment occurring during the deep Swedish recession 1992-96. Mortality from all and selected causes was examined in the 6-year period after the recession among those employed in 1990 (3.4 million). Direct health selection was analyzed as risk of unemployment by prior medical history based on all hospitalizations 1981-91. Unemployment effects on mortality were estimated with and without adjustment for prior social characteristics and for prior medical history. A prior circulatory disease history did not predict unemployment; a history of alcohol-related disease or suicide attempts did, in men and women. Unemployment predicted excess male, but not female, mortality from circulatory disease, both ischemic heart disease and stroke, and from all causes combined, after full adjustment. Adjustment for prior social characteristics reduced estimates considerably; additional adjustment for prior medical history did not. Mortality from external and alcohol-related causes was raised in men and women experiencing unemployment, after adjustment for social characteristics and medical history. For the youngest birth cohorts fully adjusted alcohol mortality HRs were substantial (male HR = 4.44; female HR = 5.73). The effect of unemployment on mortality was not uniform across the population; men, those with a low education, low income, unmarried or in urban employment were more vulnerable. Direct selection by medical history explains a modest fraction of any increased mortality risk following unemployment. Mass unemployment imposes long-term mortality risk on a sizeable segment of the population. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association.
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Garcy, Anthony M.
2016-01-01
Abstract Background: Mass unemployment in Europe is endemic, especially among the young. Does it cause mortality? Methods: We analyzed long-term effects of unemployment occurring during the deep Swedish recession 1992–96. Mortality from all and selected causes was examined in the 6-year period after the recession among those employed in 1990 (3.4 million). Direct health selection was analyzed as risk of unemployment by prior medical history based on all hospitalizations 1981–91. Unemployment effects on mortality were estimated with and without adjustment for prior social characteristics and for prior medical history. Results: A prior circulatory disease history did not predict unemployment; a history of alcohol-related disease or suicide attempts did, in men and women. Unemployment predicted excess male, but not female, mortality from circulatory disease, both ischemic heart disease and stroke, and from all causes combined, after full adjustment. Adjustment for prior social characteristics reduced estimates considerably; additional adjustment for prior medical history did not. Mortality from external and alcohol-related causes was raised in men and women experiencing unemployment, after adjustment for social characteristics and medical history. For the youngest birth cohorts fully adjusted alcohol mortality HRs were substantial (male HR = 4.44; female HR = 5.73). The effect of unemployment on mortality was not uniform across the population; men, those with a low education, low income, unmarried or in urban employment were more vulnerable. Conclusions: Direct selection by medical history explains a modest fraction of any increased mortality risk following unemployment. Mass unemployment imposes long-term mortality risk on a sizeable segment of the population. PMID:27085193
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Baldwin, Austin K.; Graczyk, David J.; Robertson, Dale M.; Saad, David A.; Magruder, Christopher
2012-01-01
The models to estimate chloride concentrations all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity as explanatory variables. Adjusted R2 values for the chloride models ranged from 0.74 to 0.97. Models to estimate total suspended solids and total phosphorus used turbidity as the only explanatory variable. Adjusted R2 values ranged from 0.77 to 0.94 for the total suspended solids models and from 0.55 to 0.75 for the total phosphorus models. Models to estimate indicator bacteria used water temperature and turbidity as the explanatory variables, with adjusted R2 values from 0.54 to 0.69 for Escherichia coli bacteria models and from 0.54 to 0.74 for fecal coliform bacteria models. Dissolved oxygen was not used in any of the final models. These models may help managers measure the effects of land-use changes and improvement projects, establish total maximum daily loads, estimate important water-quality indicators such as bacteria concentrations, and enable informed decision making in the future.
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Helin-Salmivaara, Arja; Lavikainen, Piia; Aarnio, Emma; Huupponen, Risto; Korhonen, Maarit Jaana
2014-01-01
Sequential cohort design (SCD) applying matching for propensity scores (PS) in accrual periods has been proposed to mitigate bias caused by channeling when calendar time is a proxy for strong confounders. We studied the channeling of patients according to atorvastatin and simvastatin initiation in Finland, starting from the market introduction of atorvastatin in 1998, and explored the SCD PS approach to analyzing the comparative effectiveness of atorvastatin versus simvastatin in the prevention of cardiovascular events (CVE). Initiators of atorvastatin or simvastatin use in the 45-75-year age range in 1998-2006 were characterized by their propensity of receiving atorvastatin over simvastatin, as estimated for 17 six-month periods. Atorvastatin (10 mg) and simvastatin (20 mg) initiators were matched 1∶1 on the PS, as estimated for the whole cohort and within each period. Cox regression models were fitted conventionally, and also for the PS matched cohort and the periodically PS matched cohort, to estimate the hazard ratios (HR) for CVEs. Atorvastatin (10 mg) was associated with a 11%-12% lower incidence of CVE in comparison with simvastatin (20 mg). The HR estimates were the same for a conventional Cox model (0.88, 95% confidence interval 0.85-0.91), for the analysis in which the PS was used to match across all periods and the Cox model was adjusted for strong confounders (0.89, 0.85-0.92), and for the analysis in which PS matching was applied within sequential periods (0.88, 0.84-0.92). The HR from a traditional PS matched analysis was 0.80 (0.77-0.83). The SCD PS approach produced effect estimates similar to those obtained in matching for PS within the whole cohort and adjusting the outcome model for strong confounders, but at the cost of efficiency. A traditional PS matched analysis without further adjustment in the outcome model produced estimates further away from unity.
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Deep space network software cost estimation model
NASA Technical Reports Server (NTRS)
Tausworthe, R. C.
1981-01-01
A parametric software cost estimation model prepared for Jet PRopulsion Laboratory (JPL) Deep Space Network (DSN) Data System implementation tasks is described. The resource estimation mdel modifies and combines a number of existing models. The model calibrates the task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software life-cycle statistics.
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Trutschel, Diana; Palm, Rebecca; Holle, Bernhard; Simon, Michael
2017-11-01
Because not every scientific question on effectiveness can be answered with randomised controlled trials, research methods that minimise bias in observational studies are required. Two major concerns influence the internal validity of effect estimates: selection bias and clustering. Hence, to reduce the bias of the effect estimates, more sophisticated statistical methods are needed. To introduce statistical approaches such as propensity score matching and mixed models into representative real-world analysis and to conduct the implementation in statistical software R to reproduce the results. Additionally, the implementation in R is presented to allow the results to be reproduced. We perform a two-level analytic strategy to address the problems of bias and clustering: (i) generalised models with different abilities to adjust for dependencies are used to analyse binary data and (ii) the genetic matching and covariate adjustment methods are used to adjust for selection bias. Hence, we analyse the data from two population samples, the sample produced by the matching method and the full sample. The different analysis methods in this article present different results but still point in the same direction. In our example, the estimate of the probability of receiving a case conference is higher in the treatment group than in the control group. Both strategies, genetic matching and covariate adjustment, have their limitations but complement each other to provide the whole picture. The statistical approaches were feasible for reducing bias but were nevertheless limited by the sample used. For each study and obtained sample, the pros and cons of the different methods have to be weighted. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
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Diagnostic Risk Adjustment for Medicaid: The Disability Payment System
Kronick, Richard; Dreyfus, Tony; Lee, Lora; Zhou, Zhiyuan
1996-01-01
This article describes a system of diagnostic categories that Medicaid programs can use for adjusting capitation payments to health plans that enroll people with disability. Medicaid claims from Colorado, Michigan, Missouri, New York, and Ohio are analyzed to demonstrate that the greater predictability of costs among people with disabilities makes risk adjustment more feasible than for a general population and more critical to creating health systems for people with disability. The application of our diagnostic categories to State claims data is described, including estimated effects on subsequent-year costs of various diagnoses. The challenges of implementing adjustment by diagnosis are explored. PMID:10172665
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Stukel, Thérèse A.; Fisher, Elliott S; Wennberg, David E.; Alter, David A.; Gottlieb, Daniel J.; Vermeulen, Marian J.
2007-01-01
Context Comparisons of outcomes between patients treated and untreated in observational studies may be biased due to differences in patient prognosis between groups, often because of unobserved treatment selection biases. Objective To compare 4 analytic methods for removing the effects of selection bias in observational studies: multivariable model risk adjustment, propensity score risk adjustment, propensity-based matching, and instrumental variable analysis. Design, Setting, and Patients A national cohort of 122 124 patients who were elderly (aged 65–84 years), receiving Medicare, and hospitalized with acute myocardial infarction (AMI) in 1994–1995, and who were eligible for cardiac catheterization. Baseline chart reviews were taken from the Cooperative Cardiovascular Project and linked to Medicare health administrative data to provide a rich set of prognostic variables. Patients were followed up for 7 years through December 31, 2001, to assess the association between long-term survival and cardiac catheterization within 30 days of hospital admission. Main Outcome Measure Risk-adjusted relative mortality rate using each of the analytic methods. Results Patients who received cardiac catheterization (n=73 238) were younger and had lower AMI severity than those who did not. After adjustment for prognostic factors by using standard statistical risk-adjustment methods, cardiac catheterization was associated with a 50% relative decrease in mortality (for multivariable model risk adjustment: adjusted relative risk [RR], 0.51; 95% confidence interval [CI], 0.50–0.52; for propensity score risk adjustment: adjusted RR, 0.54; 95% CI, 0.53–0.55; and for propensity-based matching: adjusted RR, 0.54; 95% CI, 0.52–0.56). Using regional catheterization rate as an instrument, instrumental variable analysis showed a 16% relative decrease in mortality (adjusted RR, 0.84; 95% CI, 0.79–0.90). The survival benefits of routine invasive care from randomized clinical trials are between 8% and 21 %. Conclusions Estimates of the observational association of cardiac catheterization with long-term AMI mortality are highly sensitive to analytic method. All standard risk-adjustment methods have the same limitations regarding removal of unmeasured treatment selection biases. Compared with standard modeling, instrumental variable analysis may produce less biased estimates of treatment effects, but is more suited to answering policy questions than specific clinical questions. PMID:17227979
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Ozminkowski, R J; Hassol, A; Firkusny, I; Noether, M; Miles, M A; Newmann, J; Sharda, C; Guterman, S; Schmitz, R
1995-04-01
The Medicare program's base payment rate for outpatient dialysis services has never been adjusted for the effects of inflation, productivity changes, or scientific and technological advancement on the costs of treating patients with end-stage renal disease. In recognition of this, Congress asked the Prospective Payment Assessment Commission to annually recommend an adjustment to Medicare's base payment rate to dialysis facilities. One component of this adjustment addresses the cost-increasing effects of technological change--the scientific and technological advances (S&TA) component. The S&TA component is intended to encourage dialysis facilities to adopt technologies that, when applied appropriately, enhance the quality of patient care, even though they may also increase costs. We found the appropriate increase to the composite payment rate for Medicare outpatient dialysis services in fiscal year 1995 to vary from 0.18% to 2.18%. These estimates depend on whether one accounts for the lack of previous adjustments to the composite rate. Mathematically, the S&TA adjustment also depends on whether one considers the likelihood of missing some dialysis sessions because of illness or hospitalization. The S&TA estimates also allow for differences in the incremental costs of technological change that are based on the varying advice of experts in the dialysis industry. The major contributors to the cost of technological change in dialysis services are the use of twin-bag disconnect peritoneal dialysis systems, automated peritoneal dialysis cyclers, and the new generation of hemodialysis machines currently on the market. Factors beyond the control of dialysis facility personnel that influence the cost of patient care should be considered when payment rates are set, and those rates should be updated as market conditions change. The S&TA adjustment is one example of how the composite rate payment system for outpatient dialysis services can be modified to provide appropriate incentives for producing high-quality care efficiently.
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Foppa, Ivo M; Ferdinands, Jill M; Chaves, Sandra S; Haber, Michael J; Reynolds, Sue B; Flannery, Brendan; Fry, Alicia M
2016-12-01
The test-negative design (TND) to evaluate influenza vaccine effectiveness is based on patients seeking care for acute respiratory infection, with those who test positive for influenza as cases and the test-negatives serving as controls. This design has not been validated for the inpatient setting where selection bias might be different from an outpatient setting. We derived mathematical expressions for vaccine effectiveness (VE) against laboratory-confirmed influenza hospitalizations and used numerical simulations to verify theoretical results exploring expected biases under various scenarios. We explored meaningful interpretations of VE estimates from inpatient TND studies. VE estimates from inpatient TND studies capture the vaccine-mediated protection of the source population against laboratory-confirmed influenza hospitalizations. If vaccination does not modify disease severity, these estimates are equivalent to VE against influenza virus infection. If chronic cardiopulmonary individuals are enrolled because of non-infectious exacerbation, biased VE estimates (too high) will result. If chronic cardiopulmonary disease status is adjusted for accurately, the VE estimates will be unbiased. If chronic cardiopulmonary illness cannot be adequately be characterized, excluding these individuals may provide unbiased VE estimates. The inpatient TND offers logistic advantages and can provide valid estimates of influenza VE. If highly vaccinated patients with respiratory exacerbation of chronic cardiopulmonary conditions are eligible for study inclusion, biased VE estimates will result unless this group is well characterized and the analysis can adequately adjust for it. Otherwise, such groups of subjects should be excluded from the analysis. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Costs of cervical cancer treatment: population-based estimates from Ontario
Pendrith, C.; Thind, A.; Zaric, G.S.; Sarma, S.
2016-01-01
Objectives The objectives of the present study were to estimate the overall and specific medical care costs associated with cervical cancer in the first 5 years after diagnosis in Ontario. Methods Incident cases of invasive cervical cancer during 2007–2010 were identified from the Ontario Cancer Registry and linked to administrative databases held at the Institute for Clinical Evaluative Sciences. Mean costs in 2010 Canadian dollars were estimated using the arithmetic mean and estimators that adjust for censored data. Results Mean age of the patients in the study cohort (779 cases) was 49.3 years. The mean overall medical care cost was $39,187 [standard error (se): $1,327] in the 1st year after diagnosis. Costs in year 1 ranged from $34,648 (se: $1,275) for those who survived at least 1 year to $69,142 (se: $4,818) for those who died from cervical cancer within 1 year. At 5 years after diagnosis, the mean overall unadjusted cost was $63,131 (se: $3,131), and the cost adjusted for censoring was $68,745 (se: $2,963). Inpatient hospitalizations and cancer-related care were the two largest components of cancer treatment costs. Conclusions We found that the estimated mean costs that did not account for censoring were consistently undervalued, highlighting the importance of estimates based on censoring-adjusted costs in cervical cancer. Our results are reliable for estimating the economic burden of cervical cancer and the cost-effectiveness of cervical cancer prevention strategies. PMID:27122978
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Distribution of the two-sample t-test statistic following blinded sample size re-estimation.
Lu, Kaifeng
2016-05-01
We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Statistical primer: propensity score matching and its alternatives.
Benedetto, Umberto; Head, Stuart J; Angelini, Gianni D; Blackstone, Eugene H
2018-06-01
Propensity score (PS) methods offer certain advantages over more traditional regression methods to control for confounding by indication in observational studies. Although multivariable regression models adjust for confounders by modelling the relationship between covariates and outcome, the PS methods estimate the treatment effect by modelling the relationship between confounders and treatment assignment. Therefore, methods based on the PS are not limited by the number of events, and their use may be warranted when the number of confounders is large, or the number of outcomes is small. The PS is the probability for a subject to receive a treatment conditional on a set of baseline characteristics (confounders). The PS is commonly estimated using logistic regression, and it is used to match patients with similar distribution of confounders so that difference in outcomes gives unbiased estimate of treatment effect. This review summarizes basic concepts of the PS matching and provides guidance in implementing matching and other methods based on the PS, such as stratification, weighting and covariate adjustment.
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ECCM Scheme against Interrupted Sampling Repeater Jammer Based on Parameter-Adjusted Waveform Design
Wei, Zhenhua; Peng, Bo; Shen, Rui
2018-01-01
Interrupted sampling repeater jamming (ISRJ) is an effective way of deceiving coherent radar sensors, especially for linear frequency modulated (LFM) radar. In this paper, for a simplified scenario with a single jammer, we propose a dynamic electronic counter-counter measure (ECCM) scheme based on jammer parameter estimation and transmitted signal design. Firstly, the LFM waveform is transmitted to estimate the main jamming parameters by investigating the discontinuousness of the ISRJ’s time-frequency (TF) characteristics. Then, a parameter-adjusted intra-pulse frequency coded signal, whose ISRJ signal after matched filtering only forms a single false target, is designed adaptively according to the estimated parameters, i.e., sampling interval, sampling duration and repeater times. Ultimately, for typical jamming scenes with different jamming signal ratio (JSR) and duty cycle, we propose two particular ISRJ suppression approaches. Simulation results validate the effective performance of the proposed scheme for countering the ISRJ, and the trade-off relationship between the two approaches is demonstrated. PMID:29642508
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Poisson sampling - The adjusted and unadjusted estimator revisited
Michael S. Williams; Hans T. Schreuder; Gerardo H. Terrazas
1998-01-01
The prevailing assumption, that for Poisson sampling the adjusted estimator "Y-hat a" is always substantially more efficient than the unadjusted estimator "Y-hat u" , is shown to be incorrect. Some well known theoretical results are applicable since "Y-hat a" is a ratio-of-means estimator and "Y-hat u" a simple unbiased estimator...
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Frequency Estimator Performance for a Software-Based Beacon Receiver
NASA Technical Reports Server (NTRS)
Zemba, Michael J.; Morse, Jacquelynne Rose; Nessel, James A.; Miranda, Felix
2014-01-01
As propagation terminals have evolved, their design has trended more toward a software-based approach that facilitates convenient adjustment and customization of the receiver algorithms. One potential improvement is the implementation of a frequency estimation algorithm, through which the primary frequency component of the received signal can be estimated with a much greater resolution than with a simple peak search of the FFT spectrum. To select an estimator for usage in a QV-band beacon receiver, analysis of six frequency estimators was conducted to characterize their effectiveness as they relate to beacon receiver design.
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Caçola, Priscila; Gabbard, Carl
2012-04-01
This study examined age-related characteristics associated with tool use in the perception and modulation of peripersonal and extrapersonal space. Seventy-six (76) children representing age groups 7-, 9-, 11 years and 36 adults were presented with two experiments using an estimation of reach paradigm involving arm and tool conditions and a switch-block of the opposite condition. Experiment 1 tested Arm and Tool (20 cm length) estimation and found a significant effect for Age, Space, and an Age × Space interaction (ps < 0.05). Both children and adults were less accurate in extrapersonal space, indicating an overestimation bias. Interestingly, the adjustment period during the switch-block condition was immediate and similar across age. Experiment 2 was similar to Experiment 1 with the exception of using a 40-cm-length tool. Results also revealed an age effect and a difference in Space (ps < 0.05), however, participants underestimated. Speculatively, participants were less confident when presented with a longer tool, even though the adjustment period with both tool lengths was similar. Considered together, these results hint that: (1) children as young as 6 years of age are capable of being as accurate when estimating reach with a tool as they are with their arm, (2) the adjustment period associated with extending and retracting spaces is immediate rather than gradual, and (3) tool length influences estimations of reach.
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Mixed model approaches for diallel analysis based on a bio-model.
Zhu, J; Weir, B S
1996-12-01
A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.
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Economic Evaluation of Telemedicine for Patients in ICUs.
Yoo, Byung-Kwang; Kim, Minchul; Sasaki, Tomoko; Melnikow, Joy; Marcin, James P
2016-02-01
Despite telemedicine's potential to improve patients' health outcomes and reduce costs in the ICU, hospitals have been slow to introduce telemedicine in the ICU due to high up-front costs and mixed evidence on effectiveness. This study's first aim was to conduct a cost-effectiveness analysis to estimate the incremental cost-effectiveness ratio of telemedicine in the ICU, compared with ICU without telemedicine, from the healthcare system perspective. The second aim was to examine potential cost saving of telemedicine in the ICU through probabilistic analyses and break-even analyses. Simulation analyses performed by standard decision models. Hypothetical ICU defined by the U.S. literature. Hypothetical adult patients in ICU defined by the U.S. literature. The intervention was the introduction of telemedicine in the ICU, which was assumed to affect per-patient per-hospital-stay ICU cost and hospital mortality. Telemedicine in the ICU operation costs included the telemedicine equipment-installation (start-up) costs with 5-year depreciation, maintenance costs, and clinician staffing costs. Telemedicine in the ICU effectiveness was measured by cumulative quality-adjusted life years for 5 years after ICU discharge. The base case cost-effectiveness analysis estimated telemedicine in the ICU to extend 0.011 quality-adjusted life years with an incremental cost of $516 per patient compared with ICU without telemedicine, resulting in an incremental cost-effectiveness ratio of $45,320 per additional quality-adjusted life year (= $516/0.011). The probabilistic cost-effectiveness analysis estimated an incremental cost-effectiveness ratio of $50,265 with a wide 95% CI from a negative value (suggesting cost savings) to $375,870. These probabilistic analyses projected that cost saving is achieved 37% of 1,000 iterations. Cost saving is also feasible if the per-patient per-hospital-stay operational cost and physician cost were less than $422 and less than $155, respectively, based on break-even analyses. Our analyses suggest that telemedicine in the ICU is cost-effective in most cases and cost saving in some cases. The thresholds of cost and effectiveness, estimated by break-even analyses, help hospitals determine the impact of telemedicine in the ICU and potential cost saving.
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Kashima, Saori; Yorifuji, Takashi; Tsuda, Toshihide; Ibrahim, Juliani; Doi, Hiroyuki
2010-03-01
To evaluate the effects of outdoor air pollution, taking into account indoor air pollution, in Indonesia. The subjects were 15,242 children from 2002 to 2003 Indonesia Demographic and Health Survey. The odds ratios and their confidence intervals for adverse health effects were estimated. Proximity increased the prevalence of acute respiratory infection both in urban and rural areas after adjusting for indoor air pollution. In urban areas, the prevalence of acute upper respiratory infection increased by 1.012 (95% confidence intervals: 1.005 to 1.019) per 2 km proximity to a major road. Adjusted odds ratios tended to be higher in the high indoor air pollution group. Exposure to traffic-related outdoor air pollution would increase adverse health effects after adjusting for indoor air pollution. Furthermore, indoor air pollution could exacerbate the effects of outdoor air pollution.
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Adaptive pre-specification in randomized trials with and without pair-matching.
Balzer, Laura B; van der Laan, Mark J; Petersen, Maya L
2016-11-10
In randomized trials, adjustment for measured covariates during the analysis can reduce variance and increase power. To avoid misleading inference, the analysis plan must be pre-specified. However, it is often unclear a priori which baseline covariates (if any) should be adjusted for in the analysis. Consider, for example, the Sustainable East Africa Research in Community Health (SEARCH) trial for HIV prevention and treatment. There are 16 matched pairs of communities and many potential adjustment variables, including region, HIV prevalence, male circumcision coverage, and measures of community-level viral load. In this paper, we propose a rigorous procedure to data-adaptively select the adjustment set, which maximizes the efficiency of the analysis. Specifically, we use cross-validation to select from a pre-specified library the candidate targeted maximum likelihood estimator (TMLE) that minimizes the estimated variance. For further gains in precision, we also propose a collaborative procedure for estimating the known exposure mechanism. Our small sample simulations demonstrate the promise of the methodology to maximize study power, while maintaining nominal confidence interval coverage. We show how our procedure can be tailored to the scientific question (intervention effect for the study sample vs. for the target population) and study design (pair-matched or not). Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Nguyen, Tri-Long; Collins, Gary S; Spence, Jessica; Daurès, Jean-Pierre; Devereaux, P J; Landais, Paul; Le Manach, Yannick
2017-04-28
Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression. We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds. We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions. If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering.
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ERIC Educational Resources Information Center
Mazur, James E.
2005-01-01
In Experiment 1 with rats, a left lever press led to a 5-s delay and then a possible reinforcer. A right lever press led to an adjusting delay and then a certain reinforcer. This delay was adjusted over trials to estimate an indifference point, or a delay at which the two alternatives were chosen about equally often. Indifference points increased…
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The Social Distribution of Health: Estimating Quality-Adjusted Life Expectancy in England.
Love-Koh, James; Asaria, Miqdad; Cookson, Richard; Griffin, Susan
2015-07-01
To model the social distribution of quality-adjusted life expectancy (QALE) in England by combining survey data on health-related quality of life with administrative data on mortality. Health Survey for England data sets for 2010, 2011, and 2012 were pooled (n = 35,062) and used to model health-related quality of life as a function of sex, age, and socioeconomic status (SES). Office for National Statistics mortality rates were used to construct life tables for age-sex-SES groups. These quality-of-life and length-of-life estimates were then combined to predict QALE as a function of these characteristics. Missing data were imputed, and Monte-Carlo simulation was used to estimate standard errors. Sensitivity analysis was conducted to explore alternative regression models and measures of SES. Socioeconomic inequality in QALE at birth was estimated at 11.87 quality-adjusted life-years (QALYs), with a sex difference of 1 QALY. When the socioeconomic-sex subgroups are ranked by QALE, a differential of 10.97 QALYs is found between the most and least healthy quintile groups. This differential can be broken down into a life expectancy difference of 7.28 years and a quality-of-life adjustment of 3.69 years. The methods proposed in this article refine simple binary quality-adjustment measures such as the widely used disability-free life expectancy, providing a more accurate picture of overall health inequality in society than has hitherto been available. The predictions also lend themselves well to the task of evaluating the health inequality impact of interventions in the context of cost-effectiveness analysis. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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Assessing model uncertainty using hexavalent chromium and ...
Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective of this analysis is to characterize model uncertainty by evaluating the variance in estimates across several epidemiologic analyses.Methods: This analysis compared 7 publications analyzing two different chromate production sites in Ohio and Maryland. The Ohio cohort consisted of 482 workers employed from 1940-72, while the Maryland site employed 2,357 workers from 1950-74. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability in estimates across and within model forms. A total of 7 similarly parameterized analyses were considered across model forms, and 23 analyses with alternative parameterizations were considered within model form (14 Cox; 9 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients for 7 similar analyses ranged from 2.47
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Exposure to ultrafine particles and respiratory hospitalisations in five European cities.
Samoli, Evangelia; Andersen, Zorana Jovanovic; Katsouyanni, Klea; Hennig, Frauke; Kuhlbusch, Thomas A J; Bellander, Tom; Cattani, Giorgio; Cyrys, Josef; Forastiere, Francesco; Jacquemin, Bénédicte; Kulmala, Markku; Lanki, Timo; Loft, Steffen; Massling, Andreas; Tobias, Aurelio; Stafoggia, Massimo
2016-09-01
Epidemiological evidence on the associations between exposure to ultrafine particles (UFP), with aerodynamic electrical mobility diameters <100 nm, and health is limited. We gathered data on UFP from five European cities within 2001-2011 to investigate associations between short-term changes in concentrations and respiratory hospitalisations.We applied city-specific Poisson regression models and combined city-specific estimates to obtain pooled estimates. We evaluated the sensitivity of our findings to co-pollutant adjustment and investigated effect modification patterns by period of the year, age at admission and specific diagnoses.Our results for the whole time period do not support an association between UFP and respiratory hospitalisations, although we found suggestive associations among those 0-14 years old. We nevertheless report consistent adverse effect estimates during the warm period of the year, statistically significant after lag 2 when an increase by 10 000 particles per cm(3) was associated with a 4.27% (95% CI 1.68-6.92%) increase in hospitalisations. These effect estimates were robust to particles' mass or gaseous pollutants adjustment.Considering that our findings during the warm period may reflect better exposure assessment and that the main source of non-soluble UFP in urban areas is traffic, our results call for improved regulation of traffic emissions. Copyright ©ERS 2016.
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Rafia, Rachid; Dodd, Peter J; Brennan, Alan; Meier, Petra S; Hope, Vivian D; Ncube, Fortune; Byford, Sarah; Tie, Hiong; Metrebian, Nicola; Hellier, Jennifer; Weaver, Tim; Strang, John
2016-09-01
To determine whether the provision of contingency management using financial incentives to improve hepatitis B vaccine completion in people who inject drugs entering community treatment represents a cost-effective use of health-care resources. A probabilistic cost-effectiveness analysis was conducted, using a decision-tree to estimate the short-term clinical and health-care cost impact of the vaccination strategies, followed by a Markov process to evaluate the long-term clinical consequences and costs associated with hepatitis B infection. Data on attendance to vaccination from a UK cluster randomized trial. Two contingency management options were examined in the trial: fixed versus escalating schedule financial incentives. Life-time health-care costs and quality-adjusted life years discounted at 3.5% annually; incremental cost-effectiveness ratios. The resulting estimate for the incremental life-time health-care cost of the contingency management strategy versus usual care was £21.86 [95% confidence interval (CI) = -£12.20 to 39.86] per person offered the incentive. For 1000 people offered the incentive, the incremental reduction in numbers of hepatitis B infections avoided over their lifetime was estimated at 19 (95% CI = 8-30). The probabilistic incremental cost per quality adjusted life-year gained of the contingency management programme was estimated to be £6738 (95% CI = £6297-7172), with an 89% probability of being considered cost-effective at a threshold of £20 000 per quality-adjusted life years gained (97.60% at £30 000). Using financial incentives to increase hepatitis B vaccination completion in people who inject drugs could be a cost-effective use of health-care resources in the UK as long as the incidence remains above 1.2%. © 2016 Society for the Study of Addiction.
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Alternative evaluation metrics for risk adjustment methods.
Park, Sungchul; Basu, Anirban
2018-06-01
Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk-adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high-expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk-adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013-2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution-based estimators achieve higher group-level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual-level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade-off in selecting an appropriate risk-adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors. Copyright © 2018 John Wiley & Sons, Ltd.
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Sun, Shanxia; Delgado, Michael S; Sesmero, Juan P
2016-07-15
Input- and output-based economic policies designed to reduce water pollution from fertilizer runoff by adjusting management practices are theoretically justified and well-understood. Yet, in practice, adjustment in fertilizer application or land allocation may be sluggish. We provide practical guidance for policymakers regarding the relative magnitude and speed of adjustment of input- and output-based policies. Through a dynamic dual model of corn production that takes fertilizer as one of several production inputs, we measure the short- and long-term effects of policies that affect the relative prices of inputs and outputs through the short- and long-term price elasticities of fertilizer application, and also the total time required for different policies to affect fertilizer application through the adjustment rates of capital and land. These estimates allow us to compare input- and output-based policies based on their relative cost-effectiveness. Using data from Indiana and Illinois, we find that input-based policies are more cost-effective than their output-based counterparts in achieving a target reduction in fertilizer application. We show that input- and output-based policies yield adjustment in fertilizer application at the same speed, and that most of the adjustment takes place in the short-term. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Double propensity-score adjustment: A solution to design bias or bias due to incomplete matching.
Austin, Peter C
2017-02-01
Propensity-score matching is frequently used to reduce the effects of confounding when using observational data to estimate the effects of treatments. Matching allows one to estimate the average effect of treatment in the treated. Rosenbaum and Rubin coined the term "bias due to incomplete matching" to describe the bias that can occur when some treated subjects are excluded from the matched sample because no appropriate control subject was available. The presence of incomplete matching raises important questions around the generalizability of estimated treatment effects to the entire population of treated subjects. We describe an analytic solution to address the bias due to incomplete matching. Our method is based on using optimal or nearest neighbor matching, rather than caliper matching (which frequently results in the exclusion of some treated subjects). Within the sample matched on the propensity score, covariate adjustment using the propensity score is then employed to impute missing potential outcomes under lack of treatment for each treated subject. Using Monte Carlo simulations, we found that the proposed method resulted in estimates of treatment effect that were essentially unbiased. This method resulted in decreased bias compared to caliper matching alone and compared to either optimal matching or nearest neighbor matching alone. Caliper matching alone resulted in design bias or bias due to incomplete matching, while optimal matching or nearest neighbor matching alone resulted in bias due to residual confounding. The proposed method also tended to result in estimates with decreased mean squared error compared to when caliper matching was used.
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Double propensity-score adjustment: A solution to design bias or bias due to incomplete matching
2016-01-01
Propensity-score matching is frequently used to reduce the effects of confounding when using observational data to estimate the effects of treatments. Matching allows one to estimate the average effect of treatment in the treated. Rosenbaum and Rubin coined the term “bias due to incomplete matching” to describe the bias that can occur when some treated subjects are excluded from the matched sample because no appropriate control subject was available. The presence of incomplete matching raises important questions around the generalizability of estimated treatment effects to the entire population of treated subjects. We describe an analytic solution to address the bias due to incomplete matching. Our method is based on using optimal or nearest neighbor matching, rather than caliper matching (which frequently results in the exclusion of some treated subjects). Within the sample matched on the propensity score, covariate adjustment using the propensity score is then employed to impute missing potential outcomes under lack of treatment for each treated subject. Using Monte Carlo simulations, we found that the proposed method resulted in estimates of treatment effect that were essentially unbiased. This method resulted in decreased bias compared to caliper matching alone and compared to either optimal matching or nearest neighbor matching alone. Caliper matching alone resulted in design bias or bias due to incomplete matching, while optimal matching or nearest neighbor matching alone resulted in bias due to residual confounding. The proposed method also tended to result in estimates with decreased mean squared error compared to when caliper matching was used. PMID:25038071
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Present-Day Vegetation Helps Quantifying Past Land Cover in Selected Regions of the Czech Republic
Abraham, Vojtěch; Oušková, Veronika; Kuneš, Petr
2014-01-01
The REVEALS model is a tool for recalculating pollen data into vegetation abundances on a regional scale. We explored the general effect of selected parameters by performing simulations and ascertained the best model setting for the Czech Republic using the shallowest samples from 120 fossil sites and data on actual regional vegetation (60 km radius). Vegetation proportions of 17 taxa were obtained by combining the CORINE Land Cover map with forest inventories, agricultural statistics and habitat mapping data. Our simulation shows that changing the site radius for all taxa substantially affects REVEALS estimates of taxa with heavy or light pollen grains. Decreasing the site radius has a similar effect as increasing the wind speed parameter. However, adjusting the site radius to 1 m for local taxa only (even taxa with light pollen) yields lower, more correct estimates despite their high pollen signal. Increasing the background radius does not affect the estimates significantly. Our comparison of estimates with actual vegetation in seven regions shows that the most accurate relative pollen productivity estimates (PPEs) come from Central Europe and Southern Sweden. The initial simulation and pollen data yielded unrealistic estimates for Abies under the default setting of the wind speed parameter (3 m/s). We therefore propose the setting of 4 m/s, which corresponds to the spring average in most regions of the Czech Republic studied. Ad hoc adjustment of PPEs with this setting improves the match 3–4-fold. We consider these values (apart from four exceptions) to be appropriate, because they are within the ranges of standard errors, so they are related to original PPEs. Setting a 1 m radius for local taxa (Alnus, Salix, Poaceae) significantly improves the match between estimates and actual vegetation. However, further adjustments to PPEs exceed the ranges of original values, so their relevance is uncertain. PMID:24936973
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Measuring the Value of Mortality Risk Reductions in Turkey
Tekeşin, Cem; Ara, Shihomi
2014-01-01
The willingness to pay (WTP) for mortality risk reduction from four causes (lung cancer, other type of cancer, respiratory disease, traffic accident) are estimated using random parameter logit model with data from choice experiment for three regions in Turkey. The value of statistical life (VSL) estimated for Afsin-Elbistan, Kutahya-Tavsanli, Ankara and the pooled case are found as 0.56, 0.35, 0.46 and 0.49 million Purchasing Power Parity (PPP) adjusted 2012 US dollars (USD). Different types of risk cause different VSL estimates and we found the lung cancer premium of 213% against traffic accident. The effects of one-year-delayed provision of risk-reduction service are the reduction of WTP by 482 TL ($318 in PPP adjusted USD) per person on average, and the disutility from status-quo (zero risk reduction) against alternative is found to be 891 TL ($589 in PPP adjusted USD) per person on average. Senior discounts of VSL are partially determined by status-quo preference and the amount of discount decreases once the status-quo bias is removed. The peak VSL is found to be for the age group 30–39 and the average VSL for the age group is 0.8 million PPP adjusted USD). Turkey’s compliance to European Union (EU) air quality standard will cause welfare gains of total 373 million PPP adjusted USD for our study areas in terms of reduced number of premature mortality. PMID:25000150
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Length bias correction in one-day cross-sectional assessments - The nutritionDay study.
Frantal, Sophie; Pernicka, Elisabeth; Hiesmayr, Michael; Schindler, Karin; Bauer, Peter
2016-04-01
A major problem occurring in cross-sectional studies is sampling bias. Length of hospital stay (LOS) differs strongly between patients and causes a length bias as patients with longer LOS are more likely to be included and are therefore overrepresented in this type of study. To adjust for the length bias higher weights are allocated to patients with shorter LOS. We determined the effect of length-bias adjustment in two independent populations. Length-bias correction is applied to the data of the nutritionDay project, a one-day multinational cross-sectional audit capturing data on disease and nutrition of patients admitted to hospital wards with right-censoring after 30 days follow-up. We applied the weighting method for estimating the distribution function of patient baseline variables based on the method of non-parametric maximum likelihood. Results are validated using data from all patients admitted to the General Hospital of Vienna between 2005 and 2009, where the distribution of LOS can be assumed to be known. Additionally, a simplified calculation scheme for estimating the adjusted distribution function of LOS is demonstrated on a small patient example. The crude median (lower quartile; upper quartile) LOS in the cross-sectional sample was 14 (8; 24) and decreased to 7 (4; 12) when adjusted. Hence, adjustment for length bias in cross-sectional studies is essential to get appropriate estimates. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
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Gorman, Emma; Leyland, Alastair H.; McCartney, Gerry; Katikireddi, Srinivasa Vittal; Rutherford, Lisa; Graham, Lesley; Robinson, Mark
2017-01-01
Abstract Background and aims Analytical approaches to addressing survey non‐participation bias typically use only demographic information to improve estimates. We applied a novel methodology which uses health information from data linkage to adjust for non‐representativeness. We illustrate the method by presenting adjusted alcohol consumption estimates for Scotland. Design Data on consenting respondents to the Scottish Health Surveys (SHeSs) 1995–2010 were linked confidentially to routinely collected hospital admission and mortality records. Synthetic observations representing non‐respondents were created using general population data. Multiple imputation was performed to compute adjusted alcohol estimates given a range of assumptions about the missing data. Adjusted estimates of mean weekly consumption were additionally calibrated to per‐capita alcohol sales data. Setting Scotland. Participants 13 936 male and 18 021 female respondents to the SHeSs 1995–2010, aged 20–64 years. Measurements Weekly alcohol consumption, non‐, binge‐ and problem‐drinking. Findings Initial adjustment for non‐response resulted in estimates of mean weekly consumption that were elevated by up to 17.8% [26.5 units (18.6–34.4)] compared with corrections based solely on socio‐demographic data [22.5 (17.7–27.3)]; other drinking behaviour estimates were little changed. Under more extreme assumptions the overall difference was up to 53%, and calibrating to sales estimates resulted in up to 88% difference. Increases were especially pronounced among males in deprived areas. Conclusions The use of routinely collected health data to reduce bias arising from survey non‐response resulted in higher alcohol consumption estimates among working‐age males in Scotland, with less impact for females. This new method of bias reduction can be generalized to other surveys to improve estimates of alternative harmful behaviours. PMID:28276110
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Djami-Tchatchou, Arnaud T; Norton, Gavin R; Redelinghuys, Michelle; Maseko, Muzi J; Majane, Olebogeng H I; Woodiwiss, Angela J
2014-12-01
An inability to show consistent relationships between gene variants and blood pressure (BP) may be confounded by the use of office BP measurement. Whether the difference between office BP and day BP (office-day) is genetically predetermined is unknown. We therefore aimed to determine the intrafamilial aggregation and heritability of office-day BP. Nurse-derived office BP (mean of 5 measurements according to guidelines) and 24-h ambulatory BP were determined for 592 participants from 198 families (67 spouse pairs, 361 parent-child pairs, and 169 sibling-sibling pairs), with 12 families having three generations, from an urban developing community of black Africans. Heritability estimates were determined using SAGE software. With adjustments for confounders, office systolic BP (SBP) (h=0.35±0.09, P<0.0001) showed comparable heritability estimates to 24-h SBP (h=0.33±0.09, P<0.0001). Similarly, with adjustments for confounders, office diastolic BP (DBP) (h=0.37±0.09, P<0.0001) showed comparable heritability estimates as 24-h DBP (h=0.35±0.09, P<0.0001). However, multivariate adjusted heritability estimates of day SBP (h=0.29±0.09, P<0.0001) and DBP (h=0.33±0.09, P<0.0001) were not diminished by further adjustments for office SBP (h=0.42±0.09, P<0.0001) or DBP (h=0.34±0.09, P<0.0001). Further, independent of confounders, office-day BP showed significant intrafamilial aggregation and heritability (SBP: h=0.51±0.10, P<0.0001; DBP: h=0.37±0.09, P<0.0001), effects that persisted with further adjustments for office, day, or day-night BP (P<0.0005 for SBP and DBP). Although office and ambulatory BP may show similar heritability estimates, genetic associations with carefully determined office BP measurements may be confounded by the heritability of office-day BP differences.
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Doubly robust matching estimators for high dimensional confounding adjustment.
Antonelli, Joseph; Cefalu, Matthew; Palmer, Nathan; Agniel, Denis
2018-05-11
Valid estimation of treatment effects from observational data requires proper control of confounding. If the number of covariates is large relative to the number of observations, then controlling for all available covariates is infeasible. In cases where a sparsity condition holds, variable selection or penalization can reduce the dimension of the covariate space in a manner that allows for valid estimation of treatment effects. In this article, we propose matching on both the estimated propensity score and the estimated prognostic scores when the number of covariates is large relative to the number of observations. We derive asymptotic results for the matching estimator and show that it is doubly robust in the sense that only one of the two score models need be correct to obtain a consistent estimator. We show via simulation its effectiveness in controlling for confounding and highlight its potential to address nonlinear confounding. Finally, we apply the proposed procedure to analyze the effect of gender on prescription opioid use using insurance claims data. © 2018, The International Biometric Society.
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Comparison of Globally Complete Versions of GPCP and CMAP Monthly Precipitation Analyses
NASA Technical Reports Server (NTRS)
Curtis, Scott; Adler, Robert; Huffman, George
1998-01-01
In this study two global observational precipitation products, namely the Global Precipitation Climatology Project's (GPCP) community data set and CPC's Merged Analysis of Precipitation (CMAP), are compared on global to regional scales in the context of the different satellite and gauge data inputs and merger techniques. The average annual global precipitation rates, calculated from data common in regions/times to both GPCP and CMAP, are similar for the two. However, CMAP is larger than GPCP in the tropics because: (1) CMAP values in the tropics are adjusted month-by month to atoll gauge data in the West Pacific, which are greater than any satellite observations used; and (2) CMAP is produced from a linear combination of data inputs, which tends to give higher values than the microwave emission estimates alone to which the inputs are adjusted in the GPCP merger over the ocean. The CMAP month-to-month adjustment to the atolls also appears to introduce temporal variations throughout the tropics which are not detected by satellite-only products. On the other hand, GPCP is larger than CMAP in the high-latitude oceans, where CMAP includes the scattering based microwave estimates which are consistently smaller than the emission estimates used in both techniques. Also, in the polar regions GPCP transitions from the emission microwave estimates to the larger TOVS-based estimates. Finally, in high-latitude land areas GPCP can be significantly larger than CMAP because GPCP attempts to correct the gauge estimates for errors due to wind loss effects.
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Nonparametric methods for doubly robust estimation of continuous treatment effects.
Kennedy, Edward H; Ma, Zongming; McHugh, Matthew D; Small, Dylan S
2017-09-01
Continuous treatments (e.g., doses) arise often in practice, but many available causal effect estimators are limited by either requiring parametric models for the effect curve, or by not allowing doubly robust covariate adjustment. We develop a novel kernel smoothing approach that requires only mild smoothness assumptions on the effect curve, and still allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and give a procedure for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.
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Furutani, Eiko; Nishigaki, Yuki; Kanda, Chiaki; Takeda, Toshihiro; Shirakami, Gotaro
2013-01-01
This paper proposes a novel hypnosis control method using Auditory Evoked Potential Index (aepEX) as a hypnosis index. In order to avoid side effects of an anesthetic drug, it is desirable to reduce the amount of an anesthetic drug during surgery. For this purpose many studies of hypnosis control systems have been done. Most of them use Bispectral Index (BIS), another hypnosis index, but it has problems of dependence on anesthetic drugs and nonsmooth change near some particular values. On the other hand, aepEX has an ability of clear distinction between patient consciousness and unconsciousness and independence of anesthetic drugs. The control method proposed in this paper consists of two elements: estimating the minimum effect-site concentration for maintaining appropriate hypnosis and adjusting infusion rate of an anesthetic drug, propofol, using model predictive control. The minimum effect-site concentration is estimated utilizing the property of aepEX pharmacodynamics. The infusion rate of propofol is adjusted so that effect-site concentration of propofol may be kept near and always above the minimum effect-site concentration. Simulation results of hypnosis control using the proposed method show that the minimum concentration can be estimated appropriately and that the proposed control method can maintain hypnosis adequately and reduce the total infusion amount of propofol.
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Perin, Jamie; Walker, Neff
2015-01-01
Background Recent steep declines in child mortality have been attributed in part to increased use of contraceptives and the resulting change in fertility behaviour, including an increase in the time between births. Previous observational studies have documented strong associations between short birth spacing and an increase in the risk of neonatal, infant, and under-five mortality, compared to births with longer preceding birth intervals. In this analysis, we compare two methods to estimate the association between short birth intervals and mortality risk to better inform modelling efforts linking family planning and mortality in children. Objectives Our goal was to estimate the mortality risk for neonates, infants, and young children by preceding birth space using household survey data, controlling for mother-level factors and to compare the results to those from previous analyses with survey data. Design We assessed the potential for confounding when estimating the relative mortality risk by preceding birth interval and estimated mortality risk by birth interval in four categories: less than 18 months, 18–23 months, 24–35 months, and 36 months or longer. We estimated the relative risks among women who were 35 and older at the time of the survey with two methods: in a Cox proportional hazards regression adjusting for potential confounders and also by stratifying Cox regression by mother, to control for all factors that remain constant over a woman's childbearing years. We estimated the overall effects for birth spacing in a meta-analysis with random survey effects. Results We identified several factors known for their associations with neonatal, infant, and child mortality that are also associated with preceding birth interval. When estimating the effect of birth spacing on mortality, we found that regression adjustment for these factors does not substantially change the risk ratio for short birth intervals compared to an unadjusted mortality ratio. For birth intervals less than 18 months, standard regression adjustment for confounding factors estimated a risk ratio for neonatal mortality of 2.28 (95% confidence interval: 2.18–2.37). This same effect estimated within mother is 1.57 (95% confidence interval: 1.52–1.63), a decline of almost one-third in the effect on neonatal mortality. Conclusions Neonatal, infant, and child mortality are strongly and significantly related to preceding birth interval, where births within a short interval of time after the previous birth have increased mortality. Previous analyses have demonstrated this relationship on average across all births; however, women who have short spaces between births are different from women with long spaces. Among women 35 years and older where a comparison of birth spaces within mother is possible, we find a much reduced although still significant effect of short birth spaces on child mortality. PMID:26562139
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Perin, Jamie; Walker, Neff
2015-01-01
Recent steep declines in child mortality have been attributed in part to increased use of contraceptives and the resulting change in fertility behaviour, including an increase in the time between births. Previous observational studies have documented strong associations between short birth spacing and an increase in the risk of neonatal, infant, and under-five mortality, compared to births with longer preceding birth intervals. In this analysis, we compare two methods to estimate the association between short birth intervals and mortality risk to better inform modelling efforts linking family planning and mortality in children. Our goal was to estimate the mortality risk for neonates, infants, and young children by preceding birth space using household survey data, controlling for mother-level factors and to compare the results to those from previous analyses with survey data. We assessed the potential for confounding when estimating the relative mortality risk by preceding birth interval and estimated mortality risk by birth interval in four categories: less than 18 months, 18-23 months, 24-35 months, and 36 months or longer. We estimated the relative risks among women who were 35 and older at the time of the survey with two methods: in a Cox proportional hazards regression adjusting for potential confounders and also by stratifying Cox regression by mother, to control for all factors that remain constant over a woman's childbearing years. We estimated the overall effects for birth spacing in a meta-analysis with random survey effects. We identified several factors known for their associations with neonatal, infant, and child mortality that are also associated with preceding birth interval. When estimating the effect of birth spacing on mortality, we found that regression adjustment for these factors does not substantially change the risk ratio for short birth intervals compared to an unadjusted mortality ratio. For birth intervals less than 18 months, standard regression adjustment for confounding factors estimated a risk ratio for neonatal mortality of 2.28 (95% confidence interval: 2.18-2.37). This same effect estimated within mother is 1.57 (95% confidence interval: 1.52-1.63), a decline of almost one-third in the effect on neonatal mortality. Neonatal, infant, and child mortality are strongly and significantly related to preceding birth interval, where births within a short interval of time after the previous birth have increased mortality. Previous analyses have demonstrated this relationship on average across all births; however, women who have short spaces between births are different from women with long spaces. Among women 35 years and older where a comparison of birth spaces within mother is possible, we find a much reduced although still significant effect of short birth spaces on child mortality.
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Cost-effectiveness of implementing computed tomography screening for lung cancer in Taiwan.
Yang, Szu-Chun; Lai, Wu-Wei; Lin, Chien-Chung; Su, Wu-Chou; Ku, Li-Jung; Hwang, Jing-Shiang; Wang, Jung-Der
2017-06-01
A screening program for lung cancer requires more empirical evidence. Based on the experience of the National Lung Screening Trial (NLST), we developed a method to adjust lead-time bias and quality-of-life changes for estimating the cost-effectiveness of implementing computed tomography (CT) screening in Taiwan. The target population was high-risk (≥30 pack-years) smokers between 55 and 75 years of age. From a nation-wide, 13-year follow-up cohort, we estimated quality-adjusted life expectancy (QALE), loss-of-QALE, and lifetime healthcare expenditures per case of lung cancer stratified by pathology and stage. Cumulative stage distributions for CT-screening and no-screening were assumed equal to those for CT-screening and radiography-screening in the NLST to estimate the savings of loss-of-QALE and additional costs of lifetime healthcare expenditures after CT screening. Costs attributable to screen-negative subjects, false-positive cases and radiation-induced lung cancer were included to obtain the incremental cost-effectiveness ratio from the public payer's perspective. The incremental costs were US$22,755 per person. After dividing this by savings of loss-of-QALE (1.16 quality-adjusted life year (QALY)), the incremental cost-effectiveness ratio was US$19,683 per QALY. This ratio would fall to US$10,947 per QALY if the stage distribution for CT-screening was the same as that of screen-detected cancers in the NELSON trial. Low-dose CT screening for lung cancer among high-risk smokers would be cost-effective in Taiwan. As only about 5% of our women are smokers, future research is necessary to identify the high-risk groups among non-smokers and increase the coverage. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
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Incorporating the sampling design in weighting adjustments for panel attrition
Chen, Qixuan; Gelman, Andrew; Tracy, Melissa; Norris, Fran H.; Galea, Sandro
2015-01-01
We review weighting adjustment methods for panel attrition and suggest approaches for incorporating design variables, such as strata, clusters and baseline sample weights. Design information can typically be included in attrition analysis using multilevel models or decision tree methods such as the CHAID algorithm. We use simulation to show that these weighting approaches can effectively reduce bias in the survey estimates that would occur from omitting the effect of design factors on attrition while keeping the resulted weights stable. We provide a step-by-step illustration on creating weighting adjustments for panel attrition in the Galveston Bay Recovery Study, a survey of residents in a community following a disaster, and provide suggestions to analysts in decision making about weighting approaches. PMID:26239405
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Incorporating climate into belowground carbon estimates in the national greenhouse gas inventory
Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Anthony W. D’Amato
2015-01-01
Refined estimation of carbon (C) stocks within forest ecosystems is a critical component of efforts to reduce greenhouse gas emissions and mitigate the effects of projected climate change through forest C management. Recent evidence has pointed to the importance of climate as a driver of belowground C stocks. This study describes an approach for adjusting allometric...
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Relative Pose Estimation Using Image Feature Triplets
NASA Astrophysics Data System (ADS)
Chuang, T. Y.; Rottensteiner, F.; Heipke, C.
2015-03-01
A fully automated reconstruction of the trajectory of image sequences using point correspondences is turning into a routine practice. However, there are cases in which point features are hardly detectable, cannot be localized in a stable distribution, and consequently lead to an insufficient pose estimation. This paper presents a triplet-wise scheme for calibrated relative pose estimation from image point and line triplets, and investigates the effectiveness of the feature integration upon the relative pose estimation. To this end, we employ an existing point matching technique and propose a method for line triplet matching in which the relative poses are resolved during the matching procedure. The line matching method aims at establishing hypotheses about potential minimal line matches that can be used for determining the parameters of relative orientation (pose estimation) of two images with respect to the reference one; then, quantifying the agreement using the estimated orientation parameters. Rather than randomly choosing the line candidates in the matching process, we generate an associated lookup table to guide the selection of potential line matches. In addition, we integrate the homologous point and line triplets into a common adjustment procedure. In order to be able to also work with image sequences the adjustment is formulated in an incremental manner. The proposed scheme is evaluated with both synthetic and real datasets, demonstrating its satisfactory performance and revealing the effectiveness of image feature integration.
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Elderly poverty and Supplemental Security Income.
Nicholas, Joyce; Wiseman, Michael
2009-01-01
In the United States, poverty is generally assessed on the basis of income, as reported in the Current Population Survey's (CPS's) Annual Social and Economic Supplement (ASEC), using an official poverty standard established in the 1960s. The prevalence of receipt of means-tested transfers is underreported in the CPS, with uncertain consequences for the measurement of poverty rates by both the official standard and by using alternative "relative" measures linked to the contemporaneous income distribution. The article reports results estimating the prevalence of poverty in 2002. We complete this effort by using a version of the 2003 CPS/ASEC for which a substantial majority (76 percent) of respondents have individual records matching administrative data from the Social Security Administration on earnings and receipt of income from the Old-Age, Survivors, and Disability Insurance and Supplemental Security Income (SSI) programs. Adjustment of the CPS income data with administrative data substantially improves coverage of SSI receipt. The consequence for general poverty is sensitive to the merge procedures employed, but under both sets of merge procedures considered, the estimated poverty rate among all elderly persons and among elderly SSI recipients is substantially less than rates estimated using the unadjusted CPS. The effect of the administrative adjustment is less significant for perception of relative poverty than for absolute poverty. We emphasize the effect of these adjustments on perception of poverty among the elderly in general and elderly SSI recipients in particular.
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Bond, H S; Sullivan, S G; Cowling, B J
2016-06-01
Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.
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Frequency Estimator Performance for a Software-Based Beacon Receiver
NASA Technical Reports Server (NTRS)
Zemba, Michael J.; Morse, Jacquelynne R.; Nessel, James A.
2014-01-01
As propagation terminals have evolved, their design has trended more toward a software-based approach that facilitates convenient adjustment and customization of the receiver algorithms. One potential improvement is the implementation of a frequency estimation algorithm, through which the primary frequency component of the received signal can be estimated with a much greater resolution than with a simple peak search of the FFT spectrum. To select an estimator for usage in a Q/V-band beacon receiver, analysis of six frequency estimators was conducted to characterize their effectiveness as they relate to beacon receiver design.
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Latimer, Nicholas R; Abrams, Keith R; Lambert, Paul C; Crowther, Michael J; Wailoo, Allan J; Morden, James P; Akehurst, Ron L; Campbell, Michael J
2014-04-01
Treatment switching commonly occurs in clinical trials of novel interventions in the advanced or metastatic cancer setting. However, methods to adjust for switching have been used inconsistently and potentially inappropriately in health technology assessments (HTAs). We present recommendations on the use of methods to adjust survival estimates in the presence of treatment switching in the context of economic evaluations. We provide background on the treatment switching issue and summarize methods used to adjust for it in HTAs. We discuss the assumptions and limitations associated with adjustment methods and draw on results of a simulation study to make recommendations on their use. We demonstrate that methods used to adjust for treatment switching have important limitations and often produce bias in realistic scenarios. We present an analysis framework that aims to increase the probability that suitable adjustment methods can be identified on a case-by-case basis. We recommend that the characteristics of clinical trials, and the treatment switching mechanism observed within them, should be considered alongside the key assumptions of the adjustment methods. Key assumptions include the "no unmeasured confounders" assumption associated with the inverse probability of censoring weights (IPCW) method and the "common treatment effect" assumption associated with the rank preserving structural failure time model (RPSFTM). The limitations associated with switching adjustment methods such as the RPSFTM and IPCW mean that they are appropriate in different scenarios. In some scenarios, both methods may be prone to bias; "2-stage" methods should be considered, and intention-to-treat analyses may sometimes produce the least bias. The data requirements of adjustment methods also have important implications for clinical trialists.
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Neher, Chris J.; Duffield, John; Bair, Lucas S.; Patterson, David A.; Neher, Katherine
2017-01-01
We directly compare trip willingness to pay (WTP) values between 1985 and 2015 stated preference surveys of private party Grand Canyon boaters using identically designed valuation methods. The temporal gap of 30 years between these two studies is well beyond that of any tests of WTP temporal stability in the literature. Comparisons were made of mean WTP estimates for four hypothetical Colorado River flow level scenarios. WTP values from the 1985 survey were adjusted to 2015 levels using the consumer price index. Mean WTP precision was estimated through simulation. No statistically significant differences were detected between the adjusted Bishop et al. (1987) and the current study mean WTP estimates. Examination of pooled models of the data from the studies suggest that while the estimated WTP values are stable over time, the underlying valuation functions may not be, particularly when the data and models are corrected to account for differing bid structures and possible panel effects.
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Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality.
Bishara, Anthony J; Hittner, James B
2015-10-01
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box-Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples ( n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated.
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Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality
Hittner, James B.
2014-01-01
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box–Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples (n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated. PMID:29795841
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NASA Astrophysics Data System (ADS)
Kennedy, J. J.; Rayner, N. A.; Smith, R. O.; Parker, D. E.; Saunby, M.
2011-07-01
Changes in instrumentation and data availability have caused time-varying biases in estimates of global and regional average sea surface temperature. The size of the biases arising from these changes are estimated and their uncertainties evaluated. The estimated biases and their associated uncertainties are largest during the period immediately following the Second World War, reflecting the rapid and incompletely documented changes in shipping and data availability at the time. Adjustments have been applied to reduce these effects in gridded data sets of sea surface temperature and the results are presented as a set of interchangeable realizations. Uncertainties of estimated trends in global and regional average sea surface temperature due to bias adjustments since the Second World War are found to be larger than uncertainties arising from the choice of analysis technique, indicating that this is an important source of uncertainty in analyses of historical sea surface temperatures. Despite this, trends over the twentieth century remain qualitatively consistent.
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NASA Astrophysics Data System (ADS)
Neher, Chris; Duffield, John; Bair, Lucas; Patterson, David; Neher, Katherine
2017-12-01
We directly compare trip willingness to pay (WTP) values between 1985 and 2015 stated preference surveys of private party Grand Canyon boaters using identically designed valuation methods. The temporal gap of 30 years between these two studies is well beyond that of any tests of WTP temporal stability in the literature. Comparisons were made of mean WTP estimates for four hypothetical Colorado River flow level scenarios. WTP values from the 1985 survey were adjusted to 2015 levels using the consumer price index. Mean WTP precision was estimated through simulation. No statistically significant differences were detected between the adjusted Bishop et al. (1987) and the current study mean WTP estimates. Examination of pooled models of the data from the studies suggest that while the estimated WTP values are stable over time, the underlying valuation functions may not be, particularly when the data and models are corrected to account for differing bid structures and possible panel effects.
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A risk adjustment approach to estimating the burden of skin disease in the United States.
Lim, Henry W; Collins, Scott A B; Resneck, Jack S; Bolognia, Jean; Hodge, Julie A; Rohrer, Thomas A; Van Beek, Marta J; Margolis, David J; Sober, Arthur J; Weinstock, Martin A; Nerenz, David R; Begolka, Wendy Smith; Moyano, Jose V
2018-01-01
Direct insurance claims tabulation and risk adjustment statistical methods can be used to estimate health care costs associated with various diseases. In this third manuscript derived from the new national Burden of Skin Disease Report from the American Academy of Dermatology, a risk adjustment method that was based on modeling the average annual costs of individuals with or without specific diseases, and specifically tailored for 24 skin disease categories, was used to estimate the economic burden of skin disease. The results were compared with the claims tabulation method used in the first 2 parts of this project. The risk adjustment method estimated the direct health care costs of skin diseases to be $46 billion in 2013, approximately $15 billion less than estimates using claims tabulation. For individual skin diseases, the risk adjustment cost estimates ranged from 11% to 297% of those obtained using claims tabulation for the 10 most costly skin disease categories. Although either method may be used for purposes of estimating the costs of skin disease, the choice of method will affect the end result. These findings serve as an important reference for future discussions about the method chosen in health care payment models to estimate both the cost of skin disease and the potential cost impact of care changes. Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.
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Estimating disease prevalence from two-phase surveys with non-response at the second phase
Gao, Sujuan; Hui, Siu L.; Hall, Kathleen S.; Hendrie, Hugh C.
2010-01-01
SUMMARY In this paper we compare several methods for estimating population disease prevalence from data collected by two-phase sampling when there is non-response at the second phase. The traditional weighting type estimator requires the missing completely at random assumption and may yield biased estimates if the assumption does not hold. We review two approaches and propose one new approach to adjust for non-response assuming that the non-response depends on a set of covariates collected at the first phase: an adjusted weighting type estimator using estimated response probability from a response model; a modelling type estimator using predicted disease probability from a disease model; and a regression type estimator combining the adjusted weighting type estimator and the modelling type estimator. These estimators are illustrated using data from an Alzheimer’s disease study in two populations. Simulation results are presented to investigate the performances of the proposed estimators under various situations. PMID:10931514
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Gaba, Ann; Zhang, Kuan; Moskowitz, Carol B; Boozer, Carol N; Marder, Karen
2008-10-01
Weight loss and energy metabolism are important clinical research areas in understanding the disease mechanisms in Huntington's disease. Having an accurate method to estimate expected total energy expenditure would likely facilitate the development of studies about these features of the disease. The Harris-Benedict equation is a formula commonly used to estimate basal energy expenditure of individuals, adjusted for height, weight, age and gender. This estimate is then multiplied by a physical activity factor to estimate total daily energy needs to maintain the given weight. Data from 24-h indirect calorimetry was utilized to derive an adjustment formula for the physical activity factor of the Harris-Benedict equation for 13 early to mid-stage Huntington's disease patients. The adjusted activity factor provided the most accurate estimate of energy needs. This adjusted formula can be used in clinical assessments of Huntington's disease patients, as well as in research studies when indirect calorimetry has not been performed.
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Two-step estimation in ratio-of-mediator-probability weighted causal mediation analysis.
Bein, Edward; Deutsch, Jonah; Hong, Guanglei; Porter, Kristin E; Qin, Xu; Yang, Cheng
2018-04-15
This study investigates appropriate estimation of estimator variability in the context of causal mediation analysis that employs propensity score-based weighting. Such an analysis decomposes the total effect of a treatment on the outcome into an indirect effect transmitted through a focal mediator and a direct effect bypassing the mediator. Ratio-of-mediator-probability weighting estimates these causal effects by adjusting for the confounding impact of a large number of pretreatment covariates through propensity score-based weighting. In step 1, a propensity score model is estimated. In step 2, the causal effects of interest are estimated using weights derived from the prior step's regression coefficient estimates. Statistical inferences obtained from this 2-step estimation procedure are potentially problematic if the estimated standard errors of the causal effect estimates do not reflect the sampling uncertainty in the estimation of the weights. This study extends to ratio-of-mediator-probability weighting analysis a solution to the 2-step estimation problem by stacking the score functions from both steps. We derive the asymptotic variance-covariance matrix for the indirect effect and direct effect 2-step estimators, provide simulation results, and illustrate with an application study. Our simulation results indicate that the sampling uncertainty in the estimated weights should not be ignored. The standard error estimation using the stacking procedure offers a viable alternative to bootstrap standard error estimation. We discuss broad implications of this approach for causal analysis involving propensity score-based weighting. Copyright © 2018 John Wiley & Sons, Ltd.
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The Distributional Impact of Social Security Policy Options.
Couch, Kenneth A; Reznik, Gayle L; Tamborini, Christopher R; Iams, Howard M
2017-01-01
Using microsimulation, we estimate the effects of three policy proposals that would alter Social Security's eligibility rules or benefit structure to reflect changes in women's labor force activity, marital patterns, and differential mortality among the aged. First, we estimate a set of options related to the duration of marriage required to receive divorced spouse and survivor benefits. Second, we estimate the effects of an earnings sharing proposal with survivor benefits, in which benefits are based entirely on earned benefits with spouses sharing their earnings during years of marriage. Third, we estimate the effects of adjusting benefits to reflect the increasing differential life expectancy by lifetime earnings. The results advance our understanding of the distributional effects of these alternative policy options on projected benefits and retirement income, including poverty and supplemental poverty status, of divorced and widowed women aged 60 or older in 2030.
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Estimated Short-Term Effects of Coarse Particles on Daily Mortality in Stockholm, Sweden
Johansson, Christer; Forsberg, Bertil
2011-01-01
Background: Although serious health effects associated with particulate matter (PM) with aerodynamic diameter ≤ 10 μm (PM10) and ≤ 2.5 μm (PM2.5; fine fraction) are documented in many studies, the effects of coarse PM (PM2.5–10) are still under debate. Objective: In this study, we estimated the effects of short-term exposure of PM2.5–10 on daily mortality in Stockholm, Sweden. Method: We collected data on daily mortality for the years 2000 through 2008. Concentrations of PM10, PM2.5, ozone, and carbon monoxide were measured simultaneously in central Stockholm. We used additive Poisson regression models to examine the association between daily mortality and PM2.5–10 on the day of death and the day before. Effect estimates were adjusted for other pollutants (two-pollutant models) during different seasons. Results: We estimated a 1.68% increase [95% confidence interval (CI): 0.20%, 3.15%] in daily mortality per 10-μg/m3 increase in PM2.5–10 (single-pollutant model). The association with PM2.5–10 was stronger for November through May, when road dust is most important (1.69% increase; 95% CI: 0.21%, 3.17%), compared with the rest of the year (1.31% increase; 95% CI: –2.08%, 4.70%), although the difference was not statistically significant. When adjusted for other pollutants, particularly PM2.5, the effect estimates per 10 μg/m3 for PM2.5–10 decreased slightly but were still higher than corresponding effect estimates for PM2.5. Conclusions: Our analysis shows an increase in daily mortality associated with elevated urban background levels of PM2.5–10. Regulation of PM2.5–10 should be considered, along with actions to specifically reduce PM2.5–10 emissions, especially road dust suspension, in cities. PMID:22182596
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Luo, Kai; Li, Runkui; Wang, Zongshuang; Zhang, Ruiming; Xu, Qun
2017-11-01
There is limited evidence showing the mortality effects of temperature variability (TV) on cardiovascular diseases. The joint effects between TV and air pollutants are also less well-established. This study aims to assess the effect modification of TV-cardiovascular mortality by air pollutants in three Chinese cities (Beijing, Nanjing and Chengdu). Data of daily mortality, air pollutants and meteorological factors from 2008 to 2011 was collected from each city. TV was calculated as the standard deviation of daily maximum and minimum temperatures over exposure days. The city-specific effect estimates of TV on cardiovascular mortality were calculated using a quasi-Poisson regression model, adjusting for potential confounders (e.g., seasonality and temperature). An interaction term of TV and a three-level air pollutants stratum indicator was included in the models. Effect modifications by air pollutants were assessed by comparing the estimates of TV's effect between pollutant stratums and calculating the corresponding 95% confidential interval of the differences. Multivariate meta-analysis was conducted to obtain the pooled estimates. The data showed that TV was associated with increased risk of cardiovascular mortality, especially for longer TV exposure days (0-8 days, TV08). This association was still observed after adjusting for air pollutants on current day or the previous two days. Stronger estimates were observed in females, but no significant difference between males and females was detected, indicating the absence of evidence of effect modification by gender. Estimates of TV-cardiovascular mortality varied across two season periods (warm and cool season) and age groups, but the evidence of effect modification by age and seasons was absent. Regarding the effect modification of TV-cardiovascular mortality association by air pollutants, a significant effect modification was identified for PM 10, but not for NO 2 and SO 2 in the whole population for all TV exposure days. This finding also persisted in subgroups, specifically in females and the elderly. Copyright © 2017 Elsevier Ltd. All rights reserved.
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The effectiveness of automatic belts in reducing fatality rates in Toyota Cressidas.
Nash, C E
1989-12-01
Toyota Cressidas have had motor driven automatic belts since 1981. Their observed use rates have been consistently close to 100%. This paper compares fatality rates in Toyota Cressidas with those in the similar Nissan Maximas (which are equipped with three-point manual belts) using the latest data from the Fatal Accident Reporting System. After making adjustments for differences in the average ages of front seat occupants of the two fleets, the Toyotas have a fatality rate that is about three-quarters that of the Nissans. From this, the fatality-reducing effectiveness for the Toyota automatic belts is estimated to be 40% with an uncertainty of +/- 8%. This effectiveness estimate is consistent with earlier estimates of automatic belt effectiveness.
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Haloacetic acids in drinking water and risk for stillbirth
King, W; Dodds, L; Allen, A; Armson, B; Fell, D; Nimrod, C
2005-01-01
Aims: To investigate the effects of haloacetic acid (HAA) compounds in drinking water on stillbirth risk. Methods: A population based case-control study was conducted in Nova Scotia and Eastern Ontario, Canada. Estimates of daily exposure to total and specific HAAs were based on household water samples and questionnaire information on water consumption at home and work. Results: The analysis included 112 stillbirth cases and 398 live birth controls. In analysis without adjustment for total THM exposure, a relative risk greater than 2 was observed for an intermediate exposure category for total HAA and dichloroacetic acid measures. After adjustment for total THM exposure, the risk estimates for intermediate exposure categories were diminished, the relative risk associated with the highest category was in the direction of a protective effect, and all confidence intervals included the null value. Conclusions: No association was observed between HAA exposures and stillbirth risk after controlling for THM exposures. PMID:15657195
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Respondent-Driven Sampling in a Multi-Site Study of Black and Latino Men Who Have Sex with Men.
Murrill, Christopher S; Bingham, Trista; Lauby, Jennifer; Liu, Kai-Lih; Wheeler, Darrell; Carballo-Diéguez, Alex; Marks, Gary; Millett, Gregorio A
2016-02-01
Respondent-driven sampling (RDS) was used to recruit four samples of Black and Latino men who have sex with men (MSM) in three metropolitan areas to measure HIV prevalence and sexual and drug use behaviors. We compared demographic and behavioral risk characteristics of participants across sites, assessed the extent to which the RDS statistical adjustment procedure provides estimates that differ from the crude results, and summarized our experiences using RDS. From June 2005 to March 2006 a total of 2,235 MSM were recruited and interviewed: 614 Black MSM and 516 Latino MSM in New York City, 540 Black MSM in Philadelphia, and 565 Latino MSM in Los Angeles County. Crude point estimates for demographic characteristics, behavioral risk factors and HIV prevalence were calculated for each of the four samples. RDS Analysis Tool was used to obtain population-based estimates of each sampled population's characteristics. RDS adjusted estimates were similar to the crude estimates for each study sample on demographic characteristics such as age, income, education and employment status. Adjusted estimates of the prevalence of risk behaviors were lower than the crude estimates, and for three of the study samples, the adjusted HIV prevalence estimates were lower than the crude estimates. However, even the adjusted HIV prevalence estimates were higher than what has been previously estimated for these groups of MSM in these cities. Each site faced unique circumstances in implementing RDS. Our experience in using RDS among Black and Latino MSM resulted in diverse recruitment patterns and uncertainties in the estimated HIV prevalence and risk behaviors by study site. Copyright © 2016. Published by Elsevier Inc.
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Liese, Angela D; Crandell, Jamie L; Tooze, Janet A; Kipnis, Victor; Bell, Ronny; Couch, Sarah C; Dabelea, Dana; Crume, Tessa L; Mayer-Davis, Elizabeth J
2015-08-14
The SEARCH Nutrition Ancillary Study aims to investigate the role of dietary intake on the development of long-term complications of type 1 diabetes in youth, and capitalise on measurement error (ME) adjustment methodology. Using the National Cancer Institute (NCI) method for episodically consumed foods, we evaluated the relationship between sugar-sweetened beverage (SSB) intake and cardiovascular risk factor profile, with the application of ME adjustment methodology. The calibration sample included 166 youth with two FFQ and three 24 h dietary recall data within 1 month. The full sample included 2286 youth with type 1 diabetes. SSB intake was significantly associated with higher TAG, total and LDL-cholesterol concentrations, after adjusting for energy, age, diabetes duration, race/ethnicity, sex and education. The estimated effect size was larger (model coefficients increased approximately 3-fold) after the application of the NCI method than without adjustment for ME. Compared with individuals consuming one serving of SSB every 2 weeks, those who consumed one serving of SSB every 2 d had 3.7 mg/dl (0.04 mmol/l) higher TAG concentrations and 4.0 mg/dl (0.10 mmol/l) higher total cholesterol and LDL-cholesterol concentrations, after adjusting for ME and covariates. SSB intake was not associated with measures of adiposity and blood pressure. Our findings suggest that SSB intake is significantly related to increased lipid levels in youth with type 1 diabetes, and that estimates of the effect size of SSB on lipid levels are severely attenuated in the presence of ME. Future studies in youth with diabetes should consider a design that will allow for the adjustment for ME when studying the influence of diet on health status.
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[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].
Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L
2017-03-10
To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.
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Assessment of Confounders in Comparative Effectiveness Studies From Secondary Databases.
Franklin, Jessica M; Schneeweiss, Sebastian; Solomon, Daniel H
2017-03-15
Secondary clinical databases are an important and growing source of data for comparative effectiveness research (CER) studies. However, measurement of confounders, such as biomarker values or patient-reported health status, in secondary clinical databases may not align with the initiation of a new treatment. In many published CER analyses of registry data, investigators assessed confounders based on the first questionnaire in which the new exposure was recorded. However, it is known that adjustment for confounders measured after the start of exposure can lead to biased treatment effect estimates. In the present study, we conducted simulations to compare assessment strategies for a dynamic clinical confounder in a registry-based comparative effectiveness study of 2 therapies. As expected, we found that adjustment for the confounder value at the time of the first questionnaire after the start of exposure creates a biased estimate the total effect of exposure choice on outcome when the confounder mediates part of the effect. However, adjustment for the prior value can also be badly biased when measured long before exposure initiation. Thus, investigators should carefully consider the timing of confounder measurements relative to exposure initiation and the rate of change in the confounder in order to choose the most relevant measure for each patient. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Marseille, Elliot; Jiwani, Aliya; Raut, Abhishek; Verguet, Stéphane; Walson, Judd; Kahn, James G
2014-01-01
Objective This study estimated the health impact, cost and cost-effectiveness of an integrated prevention campaign (IPC) focused on diarrhoea, malaria and HIV in 70 countries ranked by per capita disability-adjusted life-year (DALY) burden for the three diseases. Methods We constructed a deterministic cost-effectiveness model portraying an IPC combining counselling and testing, cotrimoxazole prophylaxis, referral to treatment and condom distribution for HIV prevention; bed nets for malaria prevention; and provision of household water filters for diarrhoea prevention. We developed a mix of empirical and modelled cost and health impact estimates applied to all 70 countries. One-way, multiway and scenario sensitivity analyses were conducted to document the strength of our findings. We used a healthcare payer's perspective, discounted costs and DALYs at 3% per year and denominated cost in 2012 US dollars. Primary and secondary outcomes The primary outcome was cost-effectiveness expressed as net cost per DALY averted. Other outcomes included cost of the IPC; net IPC costs adjusted for averted and additional medical costs and DALYs averted. Results Implementation of the IPC in the 10 most cost-effective countries at 15% population coverage would cost US$583 million over 3 years (adjusted costs of US$398 million), averting 8.0 million DALYs. Extending IPC programmes to all 70 of the identified high-burden countries at 15% coverage would cost an adjusted US$51.3 billion and avert 78.7 million DALYs. Incremental cost-effectiveness ranged from US$49 per DALY averted for the 10 countries with the most favourable cost-effectiveness to US$119, US$181, US$335, US$1692 and US$8340 per DALY averted as each successive group of 10 countries is added ordered by decreasing cost-effectiveness. Conclusions IPC appears cost-effective in many settings, and has the potential to substantially reduce the burden of disease in resource-poor countries. This study increases confidence that IPC can be an important new approach for enhancing global health. PMID:24969782
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Carville, Kylie S; Grant, Kristina A; Sullivan, Sheena G; Fielding, James E; Lane, Courtney R; Franklin, Lucinda; Druce, Julian; Kelly, Heath A
2015-01-03
The influenza virus undergoes frequent antigenic drift, necessitating annual review of the composition of the influenza vaccine. Vaccination is an important strategy for reducing the impact and burden of influenza, and estimating vaccine effectiveness (VE) each year informs surveillance and preventative measures. We aimed to describe the influenza season and to estimate the effectiveness of the influenza vaccine in Victoria, Australia, in 2013. Routine laboratory notifications, general practitioner sentinel surveillance (including a medical deputising service) data, and sentinel hospital admission surveillance data for the influenza season (29 April to 27 October 2013) were collated in Victoria, Australia, to describe influenza-like illness or confirmed influenza during the season. General practitioner sentinel surveillance data were used to estimate VE against medically-attended laboratory confirmed influenza. VE was estimated using the case test negative design as 1-adjusted odds ratio (odds of vaccination in cases compared with controls) × 100%. Cases tested positive for influenza while non-cases (controls) tested negative. Estimates were adjusted for age group, week of onset, time to swabbing and co-morbidities. The 2013 influenza season was characterised by relatively low activity with a late peak. Influenza B circulation preceded that of influenza A(H1)pdm09, with very little influenza A(H3) circulation. Adjusted VE for all influenza was 55% (95%CI: -11, 82), for influenza A(H1)pdm09 was 43% (95%CI: -132, 86), and for influenza B was 56% (95%CI: -51, 87) Imputation of missing data raised the influenza VE point estimate to 64% (95%CI: 13, 85). Clinicians can continue to promote a positive approach to influenza vaccination, understanding that inactivated influenza vaccines prevent at least 50% of laboratory-confirmed outcomes in hospitals and the community. Copyright © 2014 Elsevier Ltd. All rights reserved.
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The impact of selection bias on vaccine effectiveness estimates from test-negative studies.
Jackson, Michael L; Phillips, C Hallie; Benoit, Joyce; Kiniry, Erika; Madziwa, Lawrence; Nelson, Jennifer C; Jackson, Lisa A
2018-01-29
Estimates of vaccine effectiveness (VE) from test-negative studies may be subject to selection bias. In the context of influenza VE, we used simulations to identify situations in which meaningful selection bias can occur. We also analyzed observational study data for evidence of selection bias. For the simulation study, we defined a hypothetical population whose members are at risk for acute respiratory illness (ARI) due to influenza and other pathogens. An unmeasured "healthcare seeking proclivity" affects both probability of vaccination and probability of seeking care for an ARI. We varied the direction and magnitude of these effects and identified situations where meaningful bias occurred. For the observational study, we reanalyzed data from the United States Influenza VE Network, an ongoing test-negative study. We compared "bias-naïve" VE estimates to bias-adjusted estimates, which used data from the source populations to correct for sampling bias. In the simulation study, an unmeasured care-seeking proclivity could create selection bias if persons with influenza ARI were more (or less) likely to seek care than persons with non-influenza ARI. However, selection bias was only meaningful when rates of care seeking between influenza ARI and non-influenza ARI were very different. In the observational study, the bias-naïve VE estimate of 55% (95% CI, 47--62%) was trivially different from the bias-adjusted VE estimate of 57% (95% CI, 49--63%). In combination, these studies suggest that while selection bias is possible in test-negative VE studies, this bias in unlikely to be meaningful under conditions likely to be encountered in practice. Researchers and public health officials can continue to rely on VE estimates from test-negative studies. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Effects of heat waves on mortality: effect modification and confounding by air pollutants.
Analitis, Antonis; Michelozzi, Paola; D'Ippoliti, Daniela; De'Donato, Francesca; Menne, Bettina; Matthies, Franziska; Atkinson, Richard W; Iñiguez, Carmen; Basagaña, Xavier; Schneider, Alexandra; Lefranc, Agnès; Paldy, Anna; Bisanti, Luigi; Katsouyanni, Klea
2014-01-01
Heat waves and air pollution are both associated with increased mortality. Their joint effects are less well understood. We explored the role of air pollution in modifying the effects of heat waves on mortality, within the EuroHEAT project. Daily mortality, meteorologic, and air pollution data from nine European cities for the years 1990-2004 were assembled. We defined heat waves by taking both intensity and duration into account. The city-specific effects of heat wave episodes were estimated using generalized estimating equation models, adjusting for potential confounders with and without inclusion of air pollutants (particles, ozone, nitrogen dioxide, sulphur dioxide, carbon monoxide). To investigate effect modification, we introduced an interaction term between heat waves and each single pollutant in the models. Random effects meta-analysis was used to summarize the city-specific results. The increase in the number of daily deaths during heat wave episodes was 54% higher on high ozone days compared with low, among people age 75-84 years. The heat wave effect on high PM10 days was increased by 36% and 106% in the 75-84 year and 85+ year age groups, respectively. A similar pattern was observed for effects on cardiovascular mortality. Effect modification was less evident for respiratory mortality, although the heat wave effect itself was greater for this cause of death. The heat wave effect was smaller (15-30%) after adjustment for ozone or PM10. The heat wave effect on mortality was larger during high ozone or high PM10 days. When assessing the effect of heat waves on mortality, lack of adjustment for ozone and especially PM10 overestimates effect parameters. This bias has implications for public health policy.
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Native American ancestry, lung function, and COPD in Costa Ricans.
Chen, Wei; Brehm, John M; Boutaoui, Nadia; Soto-Quiros, Manuel; Avila, Lydiana; Celli, Bartolome R; Bruse, Shannon; Tesfaigzi, Yohannes; Celedón, Juan C
2014-04-01
Whether Native American ancestry (NAA) is associated with COPD or lung function in a racially admixed Hispanic population is unknown. We recruited 578 Costa Ricans with and without COPD into a hybrid case-control/family-based cohort, including 316 members of families of index case subjects. All participants completed questionnaires and spirometry and gave a blood sample for DNA extraction. Genome-wide genotyping was conducted with the Illumina Human610-Quad and HumanOmniExpress BeadChip kits (Illumina Inc), and individual ancestral proportions were estimated from these genotypic data and reference panels. For unrelated individuals, linear or logistic regression was used for the analysis of NAA and COPD (GOLD [Global Initiative for Chronic Obstructive Lung Disease] stage II or greater) or lung function. For extended families, linear mixed models and generalized estimating equations were used for the analysis. All models were adjusted for age, sex, educational level, and smoking behavior; models for FEV1 were also adjusted for height. The average proportion of European, Native American, and African ancestry among participants was 62%, 35%, and 3%, respectively. After adjustment for current smoking and other covariates, NAA was inversely associated with COPD (OR per 10% increment, 0.55; 95% CI, 0.41-0.75) but positively associated with FEV1, FVC, and FEV1/FVC. After additional adjustment for pack-years of smoking, the association between NAA and COPD or lung function measures was slightly attenuated. We found that about 31% of the estimated effect of NAA on COPD is mediated by pack-years of smoking. NAA is inversely associated with COPD but positively associated with FEV1 or FVC in Costa Ricans. Ancestral effects on smoking behavior partly explain the findings for COPD but not for FEV1 or FVC.
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Native American Ancestry, Lung Function, and COPD in Costa Ricans
Chen, Wei; Brehm, John M.; Boutaoui, Nadia; Soto-Quiros, Manuel; Avila, Lydiana; Celli, Bartolome R.; Bruse, Shannon; Tesfaigzi, Yohannes
2014-01-01
Background: Whether Native American ancestry (NAA) is associated with COPD or lung function in a racially admixed Hispanic population is unknown. Methods: We recruited 578 Costa Ricans with and without COPD into a hybrid case-control/family-based cohort, including 316 members of families of index case subjects. All participants completed questionnaires and spirometry and gave a blood sample for DNA extraction. Genome-wide genotyping was conducted with the Illumina Human610-Quad and HumanOmniExpress BeadChip kits (Illumina Inc), and individual ancestral proportions were estimated from these genotypic data and reference panels. For unrelated individuals, linear or logistic regression was used for the analysis of NAA and COPD (GOLD [Global Initiative for Chronic Obstructive Lung Disease] stage II or greater) or lung function. For extended families, linear mixed models and generalized estimating equations were used for the analysis. All models were adjusted for age, sex, educational level, and smoking behavior; models for FEV1 were also adjusted for height. Results: The average proportion of European, Native American, and African ancestry among participants was 62%, 35%, and 3%, respectively. After adjustment for current smoking and other covariates, NAA was inversely associated with COPD (OR per 10% increment, 0.55; 95% CI, 0.41-0.75) but positively associated with FEV1, FVC, and FEV1/FVC. After additional adjustment for pack-years of smoking, the association between NAA and COPD or lung function measures was slightly attenuated. We found that about 31% of the estimated effect of NAA on COPD is mediated by pack-years of smoking. Conclusions: NAA is inversely associated with COPD but positively associated with FEV1 or FVC in Costa Ricans. Ancestral effects on smoking behavior partly explain the findings for COPD but not for FEV1 or FVC. PMID:24306962
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Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law.
Olsen, Cody S; Thomas, Andrea M; Singleton, Michael; Gaichas, Anna M; Smith, Tracy J; Smith, Gary A; Peng, Justin; Bauer, Michael J; Qu, Ming; Yeager, Denise; Kerns, Timothy; Burch, Cynthia; Cook, Lawrence J
2016-12-01
Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S. We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative risks (RR) and 95 % confidence intervals (CIs) for head, facial, traumatic brain, and moderate to severe head/facial injuries associated with helmet use within each helmet law setting using generalized log-binomial regression. Reported helmet use was higher in universal law states (88 % vs. 42 %). Median charges, adjusted for inflation and differences in state-incomes, were higher in partial law states (emergency department $1987 vs. $1443; inpatient $31,506 vs. $25,949). Injuries to the head and face, including traumatic brain injuries, were more common in partial law states. Effectiveness estimates of helmet use were higher in partial law states (adjusted-RR (CI) of head injury: 2.1 (1.9-2.2) partial law single vehicle; 1.4 (1.2, 1.6) universal law single vehicle; 1.8 (1.6-2.0) partial law multi-vehicle; 1.2 (1.1-1.4) universal law multi-vehicle). Medical charges and rates of head, facial, and brain injuries among motorcyclists were lower in universal law states. Helmets were effective in reducing injury in both helmet law settings; lower effectiveness estimates were observed in universal law states.
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Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law.
Olsen, Cody S; Thomas, Andrea M; Singleton, Michael; Gaichas, Anna M; Smith, Tracy J; Smith, Gary A; Peng, Justin; Bauer, Michael J; Qu, Ming; Yeager, Denise; Kerns, Timothy; Burch, Cynthia; Cook, Lawrence J
Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S. We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative risks (RR) and 95 % confidence intervals (CIs) for head, facial, traumatic brain, and moderate to severe head/facial injuries associated with helmet use within each helmet law setting using generalized log-binomial regression. Reported helmet use was higher in universal law states (88 % vs. 42 %). Median charges, adjusted for inflation and differences in state-incomes, were higher in partial law states (emergency department $1987 vs. $1443; inpatient $31,506 vs. $25,949). Injuries to the head and face, including traumatic brain injuries, were more common in partial law states. Effectiveness estimates of helmet use were higher in partial law states (adjusted-RR (CI) of head injury: 2.1 (1.9-2.2) partial law single vehicle; 1.4 (1.2, 1.6) universal law single vehicle; 1.8 (1.6-2.0) partial law multi-vehicle; 1.2 (1.1-1.4) universal law multi-vehicle). Medical charges and rates of head, facial, and brain injuries among motorcyclists were lower in universal law states. Helmets were effective in reducing injury in both helmet law settings; lower effectiveness estimates were observed in universal law states.
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Jacklyn, Gemma; Glasziou, Paul; Macaskill, Petra; Barratt, Alexandra
2016-01-01
Background: Women require information about the impact of regularly attending screening mammography on breast cancer mortality and overdiagnosis to make informed decisions. To provide this information we aimed to meta-analyse randomised controlled trials adjusted for adherence to the trial protocol. Methods: Nine screening mammography trials used in the Independent UK Breast Screening Report were selected. Extending an existing approach to adjust intention-to-treat (ITT) estimates for less than 100% adherence rates, we conducted a random-effects meta-analysis. This produced a combined deattenuated prevented fraction and a combined deattenuated percentage risk of overdiagnosis. Results: In women aged 39–75 years invited to screen, the prevented fraction of breast cancer mortality at 13-year follow-up was 0.22 (95% CI 0.15–0.28) and it increased to 0.30 (95% CI 0.18–0.42) with deattenuation. In women aged 40–69 years invited to screen, the ITT percentage risk of overdiagnosis during the screening period was 19.0% (95% CI 15.2–22.7%), deattenuation increased this to 29.7% (95% CI 17.8–41.5%). Conclusions: Adjustment for nonadherence increased the size of the mortality benefit and risk of overdiagnosis by up to 50%. These estimates are more appropriate when developing quantitative information to support individual decisions about attending screening mammography. PMID:27124337
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Effects of LiDAR point density and landscape context on estimates of urban forest biomass
NASA Astrophysics Data System (ADS)
Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.
2015-03-01
Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density.
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Holbrook, Christopher M.; Perry, Russell W.; Brandes, Patricia L.; Adams, Noah S.
2013-01-01
In telemetry studies, premature tag failure causes negative bias in fish survival estimates because tag failure is interpreted as fish mortality. We used mark-recapture modeling to adjust estimates of fish survival for a previous study where premature tag failure was documented. High rates of tag failure occurred during the Vernalis Adaptive Management Plan’s (VAMP) 2008 study to estimate survival of fall-run Chinook salmon (Oncorhynchus tshawytscha) during migration through the San Joaquin River and Sacramento-San Joaquin Delta, California. Due to a high rate of tag failure, the observed travel time distribution was likely negatively biased, resulting in an underestimate of tag survival probability in this study. Consequently, the bias-adjustment method resulted in only a small increase in estimated fish survival when the observed travel time distribution was used to estimate the probability of tag survival. Since the bias-adjustment failed to remove bias, we used historical travel time data and conducted a sensitivity analysis to examine how fish survival might have varied across a range of tag survival probabilities. Our analysis suggested that fish survival estimates were low (95% confidence bounds range from 0.052 to 0.227) over a wide range of plausible tag survival probabilities (0.48–1.00), and this finding is consistent with other studies in this system. When tags fail at a high rate, available methods to adjust for the bias may perform poorly. Our example highlights the importance of evaluating the tag life assumption during survival studies, and presents a simple framework for evaluating adjusted survival estimates when auxiliary travel time data are available.
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Assessing uncertainty in published risk estimates using ...
Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective is to characterize model uncertainty by evaluating estimates across published epidemiologic studies of the same cohort.Methods: This analysis was based on 5 studies analyzing a cohort of 2,357 workers employed from 1950-74 in a chromate production plant in Maryland. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability within and between model forms. A total of 5 similarly parameterized analyses were considered across model form, and 16 analyses with alternative parameterizations were considered within model form (10 Cox; 6 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients (betas) for 5 similar analyses ranged from 2.47 to 4.33 (mean=2.97, σ2=0.63). Within the 10 Cox models, coefficients ranged from 2.53 to 4.42 (mean=3.29, σ2=0.
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Pollmanns, Johannes; Romano, Patrick S; Weyermann, Maria; Geraedts, Max; Drösler, Saskia E
2018-04-01
To explore effects of disease prevalence adjustment on ambulatory care-sensitive hospitalization (ACSH) rates used for quality comparisons. County-level hospital administrative data on adults discharged from German hospitals in 2011 and prevalence estimates based on administrative ambulatory diagnosis data were used. A retrospective cross-sectional study using in- and outpatient secondary data was performed. Hospitalization data for hypertension, diabetes, heart failure, chronic obstructive pulmonary disease, and asthma were obtained from the German Diagnosis Related Groups (DRG) database. Prevalence estimates were obtained from the German Central Research Institute of Ambulatory Health Care. Crude hospitalization rates varied substantially across counties (coefficients of variation [CV] 28-37 percent across conditions); this variation was reduced by prevalence adjustment (CV 21-28 percent). Prevalence explained 40-50 percent of the observed variation (r = 0.65-0.70) in ACSH rates for all conditions except asthma (r = 0.07). Between 30 percent and 38 percent of areas moved into or outside condition-specific control limits with prevalence adjustment. Unadjusted ACSH rates should be used with caution for high-stakes public reporting as differences in prevalence may have a marked impact. Prevalence adjustment should be considered in models analyzing ACSH. © Health Research and Educational Trust.
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Analysis of conditional genetic effects and variance components in developmental genetics.
Zhu, J
1995-12-01
A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.
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Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics
Zhu, J.
1995-01-01
A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500
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Index to Estimate the Efficiency of an Ophthalmic Practice.
Chen, Andrew; Kim, Eun Ah; Aigner, Dennis J; Afifi, Abdelmonem; Caprioli, Joseph
2015-08-01
A metric of efficiency, a function of the ratio of quality to cost per patient, will allow the health care system to better measure the impact of specific reforms and compare the effectiveness of each. To develop and evaluate an efficiency index that estimates the performance of an ophthalmologist's practice as a function of cost, number of patients receiving care, and quality of care. Retrospective review of 36 ophthalmology subspecialty practices from October 2011 to September 2012 at a university-based eye institute. The efficiency index (E) was defined as a function of adjusted number of patients (N(a)), total practice adjusted costs (C(a)), and a preliminary measure of quality (Q). Constant b limits E between 0 and 1. Constant y modifies the influence of Q on E. Relative value units and geographic cost indices determined by the Centers for Medicare and Medicaid for 2012 were used to calculate adjusted costs. The efficiency index is expressed as the following: E = b(N(a)/C(a))Q(y). Independent, masked auditors reviewed 20 random patient medical records for each practice and filled out 3 questionnaires to obtain a process-based quality measure. The adjusted number of patients, adjusted costs, quality, and efficiency index were calculated for 36 ophthalmology subspecialties. The median adjusted number of patients was 5516 (interquartile range, 3450-11,863), the median adjusted cost was 1.34 (interquartile range, 0.99-1.96), the median quality was 0.89 (interquartile range, 0.79-0.91), and the median value of the efficiency index was 0.26 (interquartile range, 0.08-0.42). The described efficiency index is a metric that provides a broad overview of performance for a variety of ophthalmology specialties as estimated by resources used and a preliminary measure of quality of care provided. The results of the efficiency index could be used in future investigations to determine its sensitivity to detect the impact of interventions on a practice such as training modules or practice restructuring.
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Taylor, Colman; Jan, Stephen; Curtis, Kate; Tzannes, Alex; Li, Qiang; Palmer, Cameron; Dickson, Cara; Myburgh, John
2012-11-01
Helicopter Emergency Medical Services (HEMS) are highly resource-intensive facilities that are well established as part of trauma systems in many high-income countries. We evaluated the cost-effectiveness of a physician-staffed HEMS intervention in combination with treatment at a major trauma centre versus ground ambulance or indirect transport (via a referral hospital) in New South Wales (NSW), Australia. Cost and effectiveness estimates were derived from a cohort of trauma patients arriving at St George Hospital in NSW, Australia during an 11-year period. Adjusted estimates of in-hospital mortality were derived using logistic regression and adjusted hospital costs were estimated through a general linear model incorporating a gamma distribution and log link. These estimates along with other assumptions were incorporated into a Markov model with an annual cycle length to estimate a cost per life saved and a cost per life-year saved at one year and over a patient's lifetime respectively in three patient groups (all patients; patients with serious injury [Injury Severity Score>12]; patients with traumatic brain injury [TBI]). Results showed HEMS to be more costly but more effective at reducing in-hospital mortality leading to a cost per life saved of $1,566,379, $533,781 and $519,787 in all patients, patients with serious injury and patients with TBI respectively. When modelled over a patient's lifetime, the improved mortality associated with HEMS led to a cost per life year saved of $96,524, $50,035 and $49,159 in the three patient groups respectively. Sensitivity analyses revealed a higher probability of HEMS being cost-effective in patients with serious injury and TBI. Our investigation confirms a HEMS intervention is associated with improved mortality in trauma patients, especially in patients with serious injury and TBI. The improved benefit of HEMS in patients with serious injury and TBI leads to improved estimated cost-effectiveness. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Modeling longitudinal data, I: principles of multivariate analysis.
Ravani, Pietro; Barrett, Brendan; Parfrey, Patrick
2009-01-01
Statistical models are used to study the relationship between exposure and disease while accounting for the potential role of other factors' impact on outcomes. This adjustment is useful to obtain unbiased estimates of true effects or to predict future outcomes. Statistical models include a systematic component and an error component. The systematic component explains the variability of the response variable as a function of the predictors and is summarized in the effect estimates (model coefficients). The error element of the model represents the variability in the data unexplained by the model and is used to build measures of precision around the point estimates (confidence intervals).
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Samuelsson, Kersti; Björk, Maarit; Erdugan, Ann-Marie; Hansson, Anna-Karin; Rustner, Birgitta
2009-09-01
A wheelchair seat and position help clients perform daily activities. The comfort of the wheelchair can encourage clients to participate in daily activities and can help prevent future complications. This study evaluates how a shaped seat-cushion and two different back supports affect under-seat pressure, comfort, and pelvic rotation. Thirty healthy subjects were tested using two differently equipped manual wheelchairs. One wheelchair had a Velcro adjustable back seat and a plane seat-cushion. The other wheelchair had a non-adjustable sling-back seat and a plane cushion. The second wheelchair was also equipped with a shaped cushion and/or a detachable lumbar support. Under-seat pressure, estimated comfort, and pelvic rotation were measured after 10 min in each wheelchair outfit. Peak pressure increased with the shaped cushion compared to the plane cushion. No significant difference in estimated comfort was found. Pelvic posterior-rotation was reduced with the adjustable or detachable back-support irrespective of the shape of the seat cushion. To support a neutral pelvic position and spinal curvature, a combination of a shaped cushion and a marked lumbar support is most effective.
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Zhang, Y J; Xue, F X; Bai, Z P
2017-03-06
The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression (LUR) models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.
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Goodman, David M; Ramaswamy, Rohit; Jeuland, Marc; Srofenyoh, Emmanuel K; Engmann, Cyril M; Olufolabi, Adeyemi J; Owen, Medge D
2017-01-01
To evaluate the cost-effectiveness of a quality improvement intervention aimed at reducing maternal and fetal mortality in Accra, Ghana. Quasi-experimental, time-sequence intervention, retrospective cost-effectiveness analysis. Data were collected on the cost and outcomes of a 5-year Kybele-Ghana Health Service Quality Improvement (QI) intervention conducted at Ridge Regional Hospital, a tertiary referral center in Accra, Ghana, focused on systems, personnel, and communication. Maternal deaths prevented were estimated comparing observed rates with counterfactual projections of maternal mortality and case-fatality rates for hypertensive disorders of pregnancy and obstetric hemorrhage. Stillbirths prevented were estimated based on counterfactual estimates of stillbirth rates. Cost-effectiveness was then calculated using estimated disability-adjusted life years averted and subjected to Monte Carlo and one-way sensitivity analyses to test the importance of assumptions inherent in the calculations. Incremental Cost-effectiveness ratio (ICER), which represents the cost per disability-adjusted life-year (DALY) averted by the intervention compared to a model counterfactual. From 2007-2011, 39,234 deliveries were affected by the QI intervention implemented at Ridge Regional Hospital. The total budget for the program was $2,363,100. Based on program estimates, 236 (±5) maternal deaths and 129 (±13) intrapartum stillbirths were averted (14,876 DALYs), implying an ICER of $158 ($129-$195) USD. This value is well below the highly cost-effective threshold of $1268 USD. Sensitivity analysis considered DALY calculation methods, and yearly prevalence of risk factors and case fatality rates. In each of these analyses, the program remained highly cost-effective with an ICER ranging from $97-$218. QI interventions to reduce maternal and fetal mortality in low resource settings can be highly cost effective. Cost-effectiveness analysis is feasible and should regularly be conducted to encourage fiscal responsibility in the pursuit of improved maternal and child health.
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Cost-effectiveness of supported employment for veterans with spinal cord injuries.
Sinnott, Patricia L; Joyce, Vilija; Su, Pon; Ottomanelli, Lisa; Goetz, Lance L; Wagner, Todd H
2014-07-01
To estimate the cost-effectiveness of a supported employment (SE) intervention that had been previously found effective in veterans with spinal cord injuries (SCIs). Cost-effectiveness analysis, using cost and quality-of-life data gathered in a trial of SE for veterans with SCI. SCI centers in the Veterans Health Administration. Subjects (N=157) who completed a study of SE in 6 SCI centers. Subjects were randomly assigned to the intervention of SE (n=81) or treatment as usual (n=76). A vocational rehabilitation program of SE for veterans with SCI. Costs and quality-adjusted life years, which were estimated from the Veterans Rand 36-Item Health Survey, extrapolated to Veterans Rand 6 Dimension utilities. Average cost for the SE intervention was $1821. In 1 year of follow-up, estimated total costs, including health care utilization and travel expenses, and average quality-adjusted life years were not significantly different between groups, suggesting the Spinal Cord Injury Vocational Integration Program intervention was not cost-effective compared with usual care. An intensive program of SE for veterans with SCI, which is more effective in achieving competitive employment, is not cost-effective after 1 year of follow-up. Longer follow-up and a larger study sample will be necessary to determine whether SE yields benefits and is cost-effective in the long run for a population with SCI. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
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The Economic Impact of Blindness in Europe.
Chakravarthy, Usha; Biundo, Eliana; Saka, Rasit Omer; Fasser, Christina; Bourne, Rupert; Little, Julie-Anne
2017-08-01
To estimate the annual loss of productivity from blindness and moderate to severe visual impairment (MSVI) in the population aged >50 years in the European Union (EU). We estimated the cost of lost productivity using three simple models reported in the literature based on (1) minimum wage (MW), (2) gross national income (GNI), and (3) purchasing power parity-adjusted gross domestic product (GDP-PPP) losses. In the first two models, assumptions included that all individuals worked until 65 years of age, and that half of all visual impairment cases in the >50-year age group would be in those aged between 50 and 65 years. Loss of productivity was estimated to be 100% for blind individuals and 30% for those with MSVI. None of these models included direct medical costs related to visual impairment. The estimated number of blind people in the EU population aged >50 years is ~1.28 million, with a further 9.99 million living with MSVI. Based on the three models, the estimated cost of blindness is €7.81 billion, €6.29 billion and €17.29 billion and that of MSVI €18.02 billion, €24.80 billion and €39.23 billion, with their combined costs €25.83 billion, €31.09 billion and €56.52 billion, respectively. The estimates from the MW and adjusted GDP-PPP models were generally comparable, whereas the GNI model estimates were higher, probably reflecting the lack of adjustment for unemployment. The cost of blindness and MSVI in the EU is substantial. Wider use of available cost-effective treatment and prevention strategies may reduce the burden significantly.
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Shakiba, Maryam; Mansournia, Mohammad Ali; Salari, Arsalan; Soori, Hamid; Mansournia, Nasrin; Kaufman, Jay S
2018-06-01
In longitudinal studies, standard analysis may yield biased estimates of exposure effect in the presence of time-varying confounders that are also intermediate variables. We aimed to quantify the relationship between obesity and coronary heart disease (CHD) by appropriately adjusting for time-varying confounders. This study was performed in a subset of participants from the Atherosclerosis Risk in Communities (ARIC) Study (1987-2010), a US study designed to investigate risk factors for atherosclerosis. General obesity was defined as body mass index (weight (kg)/height (m)2) ≥30, and abdominal obesity (AOB) was defined according to either waist circumference (≥102 cm in men and ≥88 cm in women) or waist:hip ratio (≥0.9 in men and ≥0.85 in women). The association of obesity with CHD was estimated by G-estimation and compared with results from accelerated failure-time models using 3 specifications. The first model, which adjusted for baseline covariates, excluding metabolic mediators of obesity, showed increased risk of CHD for all obesity measures. Further adjustment for metabolic mediators in the second model and time-varying variables in the third model produced negligible changes in the hazard ratios. The hazard ratios estimated by G-estimation were 1.15 (95% confidence interval (CI): 0.83, 1.47) for general obesity, 1.65 (95% CI: 1.35, 1.92) for AOB based on waist circumference, and 1.38 (95% CI: 1.13, 1.99) for AOB based on waist:hip ratio, suggesting that AOB increased the risk of CHD. The G-estimated hazard ratios for both measures were further from the null than those derived from standard models.
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NASA Astrophysics Data System (ADS)
Wang, J.; Yin, H.; Chung, F.
2008-12-01
While the population growth, the future land use change, and the desire for better environmental preservation and protection are adding up pressure on water resources management in California, California is facing an extra challenge of addressing potential climate change impacts on water supple and demand in California. The concerns on water facilities planning and flood control caused by climate change include modified precipitation patterns, changes in snow levels and runoff patterns due to increased air temperatures. Although long-term climate projections are largely uncertain, there appears to be a strong consistency in predicting the warming trend of future surface temperature, and the resulting shift in the seasonal patterns of runoff. However, projected changes in precipitation (wetting or drying), which control annual runoff, are far less certain. This paper attempts to separate the effects of warming trend from the effects of precipitation trend on water planning especially in California where reservoir operations are more sensitive to seasonal patterns of runoff than to the total annual runoff. The water resources systems planning model, CALSIM2, is used to evaluate climate change impact on water resource management in California. Rather than directly ingesting estimated streamflows from climate model projections into CALSIM2, a three step perturbation ratio method is proposed to introduce climate change impact into the planning model. Firstly, monthly perturbation ratio of projected monthly inflow to simulated historical monthly inflow is applied to observed historical monthly inflow to generate climate change inflows to major dams and reservoirs. To isolate the effects of warming trend on water resources, a further annual inflow adjustment is applied to the inflows generated in step one to preserve the volume of the observed annual inflow. To re-introduce the effects of precipitation trend on water resources, an additional inflow trend adjustment is applied to the adjusted climate change inflow. Therefore, three CALSIM2 experiments will be implemented: (1) base run with the observed historic inflow (1921 to 2003); (2) sensitivity run with the adjusted climate change inflow through annual inflow adjustment; (3) sensitivity run with the adjusted climate change inflow through annual inflow adjustment and inflow trend adjustment. To account for the variability of various climate models in projecting future climates, the uncertainty in future emission scenarios, and the difference in different projection periods, estimated inflows from 6 climate models for 2 emission scenarios (A2 and B1) and two projection periods (2030-2059 and 2070-2099) are included in the CALSIM model experiments.
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NASA Astrophysics Data System (ADS)
Borup, Morten; Grum, Morten; Linde, Jens Jørgen; Mikkelsen, Peter Steen
2016-08-01
Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5-30 min of rain data recorded by multiple rain gauges and propagating the rainfall estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable, well defined, 64 ha urban catchment, for nine overflow generating rain events. The dynamically adjusted radar data perform best when the aggregation period is as small as 10-20 min, in which case it performs much better than static adjusted radar data and data from rain gauges situated 2-3 km away.
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Cost effectiveness of a community-based crisis intervention program for people bereaved by suicide.
Comans, Tracy; Visser, Victoria; Scuffham, Paul
2013-01-01
Postvention services aim to ameliorate distress and reduce future incidences of suicide. The StandBy Response Service is one such service operating in Australia for those bereaved through suicide. Few previous studies have reported estimates or evaluations of the economic impact and outcomes associated with the implementation of bereavement/grief interventions. To estimate the cost-effectiveness of a postvention service from a societal perspective. A Markov model was constructed to estimate the health outcomes, quality-adjusted life years, and associated costs such as medical costs and time off work. Data were obtained from a prospective cross-sectional study comparing previous clients of the StandBy service with a control group of people bereaved by suicide who had not had contact with StandBy. Costs and outcomes were measured at 1 year after suicide bereavement and an incremental cost-effectiveness ratio was calculated. The base case found that the StandBy service dominated usual care with a cost saving from providing the StandBy service of AUS $803 and an increase in quality-adjusted life years of 0.02. Probabilistic sensitivity analysis indicates there is an 81% chance the service would be cost-effective given a range of possible scenarios. Postvention services are a cost-effective strategy and may even be cost-saving if all costs to society from suicide are taken into account.
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One giant leap for mankind? A cost-utility analysis of abolishing the law of gravity
Cyr, Claude; Lanthier, Luc
2007-01-01
Background Canada's Neo Rhino Party, a joke political party created in 2006 as a successor to the Parti Rhinocéros, is planning a new regulation to repeal the law of gravity, which could have an important impact on diseases attributable to gravity on earth. Methods We sought to estimate the number of quality-adjusted life-years that would be saved if the proposed regulation is passed and determine the cost-effectiveness of adapting Boris Volfson's antigravity machine1 for use on earth. We performed an economic analysis using a hidden Markov model. Results Our results suggest that a microgravity environment would save over 2 million quality-adjusted life-years. The cost for every quality-adjusted life-year saved is estimated to be $328. Interpretation Microgravity is the solution to the health care crisis in Canada. In addition, using technological, statistical and medical jargon gives us the opportunity to defy the laws of physics, mathematics and medicine. PMID:18056617
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Quantum metrology and estimation of Unruh effect
Wang, Jieci; Tian, Zehua; Jing, Jiliang; Fan, Heng
2014-01-01
We study the quantum metrology for a pair of entangled Unruh-Dewitt detectors when one of them is accelerated and coupled to a massless scalar field. Comparing with previous schemes, our model requires only local interaction and avoids the use of cavities in the probe state preparation process. We show that the probe state preparation and the interaction between the accelerated detector and the external field have significant effects on the value of quantum Fisher information, correspondingly pose variable ultimate limit of precision in the estimation of Unruh effect. We find that the precision of the estimation can be improved by a larger effective coupling strength and a longer interaction time. Alternatively, the energy gap of the detector has a range that can provide us a better precision. Thus we may adjust those parameters and attain a higher precision in the estimation. We also find that an extremely high acceleration is not required in the quantum metrology process. PMID:25424772
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Frontier production function estimates for steam electric generation: a comparative analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kopp, R.J.; Smith, V.K.
1980-04-01
The performance of three frontier steam electric generation estimators is compared in terms of the consideration given to new production technologies and their technical efficiency. The Cobb-Douglas, constant elasticity of substitution, and translog production functions are examined, using the Aigner-Chu linear programming, the sophisticated Aigner-Lovell-Schmidt stochastic frontier, and the direct method of adjusted ordinary least squares frontier estimators. The use of Cobb-Douglas specification is judged to have narrowed the perceived difference between competing estimators. The choice of frontier estimator is concluded to have a greater effect on the plant efficiency than functional form. 19 references. (DCK)
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Posthospitalization home health care use and changes in functional status in a Medicare population.
Hadley, J; Rabin, D; Epstein, A; Stein, S; Rimes, C
2000-05-01
The objective of this work was to estimate the effect of Medicare beneficiaries' use of home health care (HHC) for 6 months after hospital discharge on the change in functional status over a 1-year period beginning before hospitalization. Data came from the Medicare Current Beneficiary Survey, which is a nationally representative sample of Medicare beneficiaries, in-person interview data, and Medicare claims for 1991 through 1994 for 2,127 nondisabled, community-dwelling, elderly Medicare beneficiaries who were hospitalized within 6 months of their annual in-person interviews. Econometric estimation with the instrumental variable method was used to correct for observational data bias, ie, the nonrandom allocation of discharged beneficiaries to the use of posthospitalization HHC. The analysis estimates a first-stage model of HHC use from which an instrumental variable estimate is constructed to estimate the effect on change in functional status. The instrumental variable estimates suggest that HHC users experienced greater improvements in functional status than nonusers as measured by the change in a continuous scale based on the number and mix of activities of daily living and instrumental activities of daily living before and after hospitalization. The estimated improvement in functional status could be as large as 13% for a 10% increase in HHC use. In contrast, estimation with the observational data on HHC use implies that HHC users had poorer health outcomes. Adjusting for potential observational data bias is critical to obtaining estimates of the relationship between the use of posthospitalization HHC and the change in health before and after hospitalization. After adjustment, the results suggest that efforts to constrain Medicare's spending for HHC, as required by the Balanced Budget Act of 1997, may lead to poorer health outcomes for some beneficiaries.
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Deep space network software cost estimation model
NASA Technical Reports Server (NTRS)
Tausworthe, R. C.
1981-01-01
A parametric software cost estimation model prepared for Deep Space Network (DSN) Data Systems implementation tasks is presented. The resource estimation model incorporates principles and data from a number of existing models. The model calibrates task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit DSN software life cycle statistics. The estimation model output scales a standard DSN Work Breakdown Structure skeleton, which is then input into a PERT/CPM system, producing a detailed schedule and resource budget for the project being planned.
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Yurimoto, Terumi; Hara, Shintaro; Isoyama, Takashi; Saito, Itsuro; Ono, Toshiya; Abe, Yusuke
2016-09-01
Estimation of pressure and flow has been an important subject for developing implantable artificial hearts. To realize real-time viscosity-adjusted estimation of pressure head and pump flow for a total artificial heart, we propose the table estimation method with quasi-pulsatile modulation of rotary blood pump in which systolic high flow and diastolic low flow phased are generated. The table estimation method utilizes three kinds of tables: viscosity, pressure and flow tables. Viscosity is estimated from the characteristic that differential value in motor speed between systolic and diastolic phases varies depending on viscosity. Potential of this estimation method was investigated using mock circulation system. Glycerin solution diluted with salty water was used to adjust viscosity of fluid. In verification of this method using continuous flow data, fairly good estimation could be possible when differential pulse width modulation (PWM) value of the motor between systolic and diastolic phases was high. In estimation under quasi-pulsatile condition, inertia correction was provided and fairly good estimation was possible when the differential PWM value was high, which was not different from the verification results using continuous flow data. In the experiment of real-time estimation applying moving average method to the estimated viscosity, fair estimation could be possible when the differential PWM value was high, showing that real-time viscosity-adjusted estimation of pressure head and pump flow would be possible with this novel estimation method when the differential PWM value would be set high.
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NASA Astrophysics Data System (ADS)
Li, Shuiqing; Guan, Shoude; Hou, Yijun; Liu, Yahao; Bi, Fan
2018-05-01
A long-term trend of significant wave height (SWH) in China's coastal seas was examined based on three datasets derived from satellite measurements and numerical hindcasts. One set of altimeter data were obtained from the GlobWave, while the other two datasets of numerical hindcasts were obtained from the third-generation wind wave model, WAVEWATCH III, forced by wind fields from the Cross-Calibrated Multi-Platform (CCMP) and NCEP's Climate Forecast System Reanalysis (CFSR). The mean and extreme wave trends were estimated for the period 1992-2010 with respect to the annual mean and the 99th-percentile values of SWH, respectively. The altimeter wave trend estimates feature considerable uncertainties owing to the sparse sampling rate. Furthermore, the extreme wave trend tends to be overestimated because of the increasing sampling rate over time. Numerical wave trends strongly depend on the quality of the wind fields, as the CCMP waves significantly overestimate the wave trend, whereas the CFSR waves tend to underestimate the trend. Corresponding adjustments were applied which effectively improved the trend estimates from the altimeter and numerical data. The adjusted results show generally increasing mean wave trends, while the extreme wave trends are more spatially-varied, from decreasing trends prevailing in the South China Sea to significant increasing trends mainly in the East China Sea.
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Graham-Bermann, Sandra A; Perkins, Suzanne
2010-01-01
Children exposed to overwhelming and potentially traumatic events early in their lives are considered at-risk for problems in adjustment. Yet it is not known whether it is the age of first exposure (AFE) to violence or the amount of violence that the child witnessed in their lifetime that has the greatest impact on adjustment. For a sample of 190 children ages 6 to 12 exposed to intimate partner violence, their mothers reported that the average length of their abusive relationship was 10 years. The majority of children were first exposed to family violence as infants (64%), with only 12% first exposed when school-aged. Both the AFE and an estimate of the cumulative amount of violence were significantly and negatively related to children's behavioral problems. However, in regression analyses controlling for child sex, ethnicity, age, and family environment variables, cumulative violence exposure accounted for greater variance in adjustment than did AFE. Furthermore, cumulative violence exposure mediated the relationship between AFE and externalizing behavior problems, indicating that the cumulative exposure to IPV outweighed the AFE in its effect on child adjustment.
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Hilgard, Joseph; Engelhardt, Christopher R; Rouder, Jeffrey N
2017-07-01
Violent video games are theorized to be a significant cause of aggressive thoughts, feelings, and behaviors. Important evidence for this claim comes from a large meta-analysis by Anderson and colleagues (2010), who found effects of violent games in experimental, cross-sectional, and longitudinal research. In that meta-analysis, the authors argued that there is little publication or analytic bias in the literature, an argument supported by their use of the trim-and-fill procedure. In the present manuscript, we reexamine their meta-analysis using a wider array of techniques for detecting bias and adjusting effect sizes. Our conclusions differ from those of Anderson and colleagues in 3 salient ways. First, we detect substantial publication bias in experimental research on the effects of violent games on aggressive affect and aggressive behavior. Second, after adjustment for bias, the effects of violent games on aggressive behavior in experimental research are estimated as being very small, and estimates of effects on aggressive affect are much reduced. In contrast, the cross-sectional literature finds correlations that appear largely unbiased. Third, experiments meeting the original authors' criteria for methodological quality do not yield larger adjusted effects than other experiments, but instead yield larger indications of bias, indicating that perhaps they were selected for significance. We outline future directions for stronger experimental research. The results indicate the need for an open, transparent, and preregistered research process to test the existence of the basic phenomenon. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Mukabutera, Assumpta; Thomson, Dana R; Hedt-Gauthier, Bethany L; Atwood, Sidney; Basinga, Paulin; Nyirazinyoye, Laetitia; Savage, Kevin P; Habimana, Marcellin; Murray, Megan
2017-12-01
Public health interventions are often implemented at large scale, and their evaluation seems to be difficult because they are usually multiple and their pathways to effect are complex and subject to modification by contextual factors. We assessed whether controlling for rainfall-related variables altered estimates of the efficacy of a health programme in rural Rwanda and have a quantifiable effect on an intervention evaluation outcomes. We conducted a retrospective quasi-experimental study using previously collected cross-sectional data from the 2005 and 2010 Rwanda Demographic and Health Surveys (DHS), 2010 DHS oversampled data, monthly rainfall data collected from meteorological stations over the same period, and modelled output of long-term rainfall averages, soil moisture, and rain water run-off. Difference-in-difference models were used. Rainfall factors confounded the PIH intervention impact evaluation. When we adjusted our estimates of programme effect by controlling for a variety of rainfall variables, several effectiveness estimates changed by 10% or more. The analyses that did not adjust for rainfall-related variables underestimated the intervention effect on the prevalence of ARI by 14.3%, fever by 52.4% and stunting by 10.2%. Conversely, the unadjusted analysis overestimated the intervention's effect on diarrhoea by 56.5% and wasting by 80%. Rainfall-related patterns have a quantifiable effect on programme evaluation results and highlighted the importance and complexity of controlling for contextual factors in quasi-experimental design evaluations. © 2017 John Wiley & Sons Ltd.
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Impact and cost-effectiveness of Haemophilus influenzae type b conjugate vaccination in India.
Clark, Andrew D; Griffiths, Ulla K; Abbas, Syed Shahid; Rao, Krishna D; Privor-Dumm, Lois; Hajjeh, Rana; Johnson, Hope; Sanderson, Colin; Santosham, Mathuram
2013-07-01
To estimate the potential health impact and cost-effectiveness of nationwide Haemophilus influenzae type b (Hib) vaccination in India. A decision support model was used, bringing together estimates of demography, epidemiology, Hib vaccine effectiveness, Hib vaccine costs, and health care costs. Scenarios favorable and unfavorable to the vaccine were evaluated. State-level analyses indicate where the vaccine might have the greatest impact and value. Between 2012 and 2031, Hib conjugate vaccination is estimated to prevent over 200 000 child deaths (∼1% of deaths in children <5 years of age) in India at an incremental cost of US$127 million per year. From a government perspective, state-level cost-effectiveness ranged from US$192 to US$1033 per discounted disability adjusted life years averted. With the inclusion of household health care costs, cost-effectiveness ranged from US$155-US$939 per discounted disability adjusted life year averted. These values are below the World Health Organization thresholds for cost effectiveness of public health interventions. Hib conjugate vaccination is a cost-effective intervention in all States of India. This conclusion does not alter with plausible changes in key parameters. Although investment in Hib conjugate vaccination would significantly increase the cost of the Universal Immunization Program, about 15% of the incremental cost would be offset by health care cost savings. Efforts should be made to expedite the nationwide introduction of Hib conjugate vaccination in India. Copyright © 2013. Published by Mosby, Inc.
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Impact and Cost-Effectiveness of Haemophilus influenzae Type b Conjugate Vaccination in India
Clark, Andrew D.; Griffiths, Ulla K.; Abbas, Syed Shahid; Rao, Krishna D.; Privor-Dumm, Lois; Hajjeh, Rana; Johnson, Hope; Sanderson, Colin; Santosham, Mathuram
2017-01-01
Objective To estimate the potential health impact and cost-effectiveness of nationwide Haemophilus influenzae type b (Hib) vaccination in India. Study design A decision support model was used, bringing together estimates of demography, epidemiology, Hib vaccine effectiveness, Hib vaccine costs, and health care costs. Scenarios favorable and unfavorable to the vaccine were evaluated. State-level analyses indicate where the vaccine might have the greatest impact and value. Results Between 2012 and 2031, Hib conjugate vaccination is estimated to prevent over 200 000 child deaths (~1% of deaths in children <5 years of age) in India at an incremental cost of US$127 million per year. From a government perspective, state-level cost-effectiveness ranged from US$192 to US$1033 per discounted disability adjusted life years averted. With the inclusion of household health care costs, cost-effectiveness ranged from US$155-US$939 per discounted disability adjusted life year averted. These values are below the World Health Organization thresholds for cost effectiveness of public health interventions. Conclusions Hib conjugate vaccination is a cost-effective intervention in all States of India. This conclusion does not alter with plausible changes in key parameters. Although investment in Hib conjugate vaccination would significantly increase the cost of the Universal Immunization Program, about 15% of the incremental cost would be offset by health care cost savings. Efforts should be made to expedite the nationwide introduction of Hib conjugate vaccination in India. PMID:23773596
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Jensen, Cathrine Elgaard; Riis, Allan; Petersen, Karin Dam; Jensen, Martin Bach; Pedersen, Kjeld Møller
2017-05-01
In connection with the publication of a clinical practice guideline on the management of low back pain (LBP) in general practice in Denmark, a cluster randomised controlled trial was conducted. In this trial, a multifaceted guideline implementation strategy to improve general practitioners' treatment of patients with LBP was compared with a usual implementation strategy. The aim was to determine whether the multifaceted strategy was cost effective, as compared with the usual implementation strategy. The economic evaluation was conducted as a cost-utility analysis where cost collected from a societal perspective and quality-adjusted life years were used as outcome measures. The analysis was conducted as a within-trial analysis with a 12-month time horizon consistent with the follow-up period of the clinical trial. To adjust for a priori selected covariates, generalised linear models with a gamma family were used to estimate incremental costs and quality-adjusted life years. Furthermore, both deterministic and probabilistic sensitivity analyses were conducted. Results showed that costs associated with primary health care were higher, whereas secondary health care costs were lower for the intervention group when compared with the control group. When adjusting for covariates, the intervention was less costly, and there was no significant difference in effect between the 2 groups. Sensitivity analyses showed that results were sensitive to uncertainty. In conclusion, the multifaceted implementation strategy was cost saving when compared with the usual strategy for implementing LBP clinical practice guidelines in general practice. Furthermore, there was no significant difference in effect, and the estimate was sensitive to uncertainty.
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Choudhry, Niteesh K.; Patrick, Amanda R.; Antman, Elliott M.; Avorn, Jerry; Shrank, William H.
2009-01-01
Background Effective therapies for the secondary prevention of coronary heart disease–related events are significantly underused, and attempts to improve adherence have often yielded disappointing results. Elimination of patient out-of-pocket costs may be an effective strategy to enhance medication use. We sought to estimate the incremental cost-effectiveness of providing full coverage for aspirin, β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and statins (combination pharmacotherapy) to individuals enrolled in the Medicare drug benefit program after acute myocardial infarction. Methods and Results We created a Markov cost-effectiveness model to estimate the incremental cost-effectiveness of providing Medicare beneficiaries with full coverage for combination pharmacotherapy compared with current coverage under the Medicare Part D program. Our analysis was conducted from the societal perspective and considered a lifetime time horizon. In a sensitivity analysis, we repeated our analysis from the perspective of Medicare. In the model, post–myocardial infarction Medicare beneficiaries who received usual prescription drug coverage under the Part D program lived an average of 8.21 quality-adjusted life-years after their initial event, incurring coronary heart disease–related medical costs of $114 000. Those who received prescription drug coverage without deductibles or copayments lived an average of 8.56 quality-adjusted life-years and incurred $111 600 in coronary heart disease–related costs. Compared with current prescription drug coverage, full coverage for post–myocardial infarction secondary prevention therapies would result in greater functional life expectancy (0.35 quality-adjusted life-year) and less resource use ($2500). From the perspective of Medicare, full drug coverage was highly cost-effective ($7182/quality-adjusted life-year) but not cost saving. Conclusions Our analysis suggests that providing full coverage for combination therapy to post–myocardial infarction Medicare beneficiaries would save both lives and money from the societal perspective. PMID:18285564
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Norton, Giulia; McDonough, Christine M; Cabral, Howard; Shwartz, Michael; Burgess, James F
2015-05-15
Markov cost-utility model. To evaluate the cost-utility of cognitive behavioral therapy (CBT) for the treatment of persistent nonspecific low back pain (LBP) from the perspective of US commercial payers. CBT is widely deemed clinically effective for LBP treatment. The evidence is suggestive of cost-effectiveness. We constructed and validated a Markov intention-to-treat model to estimate the cost-utility of CBT, with 1-year and 10-year time horizons. We applied likelihood of improvement and utilities from a randomized controlled trial assessing CBT to treat LBP. The trial randomized subjects to treatment but subjects freely sought health care services. We derived the cost of equivalent rates and types of services from US commercial claims for LBP for a similar population. For the 10-year estimates, we derived recurrence rates from the literature. The base case included medical and pharmaceutical services and assumed gradual loss of skill in applying CBT techniques. Sensitivity analyses assessed the distribution of service utilization, utility values, and rate of LBP recurrence. We compared health plan designs. Results are based on 5000 iterations of each model and expressed as an incremental cost per quality-adjusted life-year. The incremental cost-utility of CBT was $7197 per quality-adjusted life-year in the first year and $5855 per quality-adjusted life-year over 10 years. The results are robust across numerous sensitivity analyses. No change of parameter estimate resulted in a difference of more than 7% from the base case for either time horizon. Including chiropractic and/or acupuncture care did not substantively affect cost-effectiveness. The model with medical but no pharmaceutical costs was more cost-effective ($5238 for 1 yr and $3849 for 10 yr). CBT is a cost-effective approach to manage chronic LBP among commercial health plans members. Cost-effectiveness is demonstrated for multiple plan designs. 2.
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Association of weather and air pollution interactions on daily mortality in 12 Canadian cities.
Vanos, J K; Cakmak, S; Kalkstein, L S; Yagouti, Abderrahmane
It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981-2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter <2.5 μm). We assess both single- and two-pollutant interactions to determine dependent and independent pollutant effects using the relatively new time series technique of distributed lag nonlinear modeling (DLNM). Results display dry tropical (DT) and moist tropical plus (MT+) weathers to result in a fourfold and twofold increased likelihood, respectively, of an extreme pollution event (top 5 % of pollution concentrations throughout the 28 years) occurring. We also demonstrate statistically significant effects of single-pollutant exposure on mortality ( p < 0.05) to be dependent on summer weather type, where stronger results occur in dry moderate (fair weather) and DT or MT+ weather types. The overall average single-effect RR increases due to pollutant exposure within DT and MT+ weather types are 14.9 and 11.9 %, respectively. Adjusted exposures (two-way pollutant effect estimates) generally results in decreased RR estimates, indicating that the pollutants are not independent. Adjusting for ozone significantly lowers 67 % of the single-pollutant RR estimates and reduces model variability, which demonstrates that ozone significantly controls a portion of the mortality signal from the model. Our findings demonstrate the mortality risks of air pollution exposure to differ by weather type, with increased accuracy obtained when accounting for interactive effects through adjustment for dependent pollutants using a DLNM.
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Karasik, David; Demissie, Serkalem; Lu, Darlene; Broe, Kerry E; Boyd, Steven K; Liu, Ching-Ti; Hsu, Yi-Hsiang; Bouxsein, Mary L; Kiel, Douglas P
2017-11-01
Genetic factors contribute to the risk of bone fractures, partly because of effects on bone strength. High-resolution peripheral quantitative computed tomography (HR-pQCT) estimates bone strength using micro-finite element analysis (µFEA). The goal of this study was to investigate if the bone failure load estimated by HR-pQCT-based µFEA is heritable and to what extent it shares genetic regulation with areal bone mineral density (aBMD). Bone microarchitecture was measured by HR-pQCT at the ultradistal tibia and ultradistal radius in adults from the Framingham Heart Study (n = 1087, mean age 72 years; 57% women). Radial and tibial failure load in compression were estimated by µFEA. Femoral neck (FN) and ultradistal forearm (UD) aBMD were measured by dual-energy X-ray absorptiometry (DXA). Heritability (h 2 ) of failure load and aBMD and genetic correlations between them was estimated adjusting for covariates (age and sex). Failure load values at the non-weight-bearing ultradistal radius and at the weight-bearing ultradistal tibia were highly correlated (r = 0.906; p < 0.001). Estimates of h 2 adjusted for covariates were 0.522 for the radius and 0.497 for the tibia. Additional adjustment for height did not impact on the h 2 results, but adjustment for aBMD at the UD and FN somewhat decreased h 2 point estimates: 0.222 and 0.380 for radius and tibia, respectively. In bivariate analysis, there was a high phenotypic and genetic correlation between covariate-adjusted failure load at the radius and UD aBMD (ρ P = 0.826, ρ G = 0.954, respectively), whereas environmental correlations were lower (ρ E = 0.696), all highly significant (p < 0.001). Similar correlations were observed between tibial failure load and femoral neck aBMD (ρ P = 0.577, ρ G = 0.703, both p < 0.001; ρ E = 0.432, p < 0.05). These data from adult members of families from a population-based cohort suggest that bone strength of distal extremities estimated by micro-finite element analysis is heritable and shares some genetic composition with areal BMD, regardless of the skeletal site. © 2017 American Society for Bone and Mineral Research. © 2017 American Society for Bone and Mineral Research.
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Ground Motion Prediction Models for Caucasus Region
NASA Astrophysics Data System (ADS)
Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino
2016-04-01
Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.
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Recent tobacco tax rate adjustment and its potential impact on tobacco control in China.
Hu, Teh-Wei; Mao, Zhengzhong; Shi, Jian
2010-02-01
To compare the new tobacco tax structure effective from May 2009 with the tax structure before May 2009 and to analyse its potential impact. Published government statistics and estimated price elasticities of the demand for cigarettes are used to estimate the impact of the new tax rate adjustment on cigarette consumption and population health. The new adjustment increased the tax rate by 11.7% points at the producer price level. Converting this 11.7% point increase to the retail price level would mean an increase of 3.4% points in the retail price tax rate. Thus, China's new cigarette tax rate at the retail level would be 43.4% instead of the previous 40%. The primary motivation for the recent Chinese government tobacco tax adjustment is to raise additional government revenue. Because the additional ad valorem tax has not yet been transferred to smokers, there is no public health benefit. It is hoped that the Chinese government will pass along these taxes to the retail price level, which would result in between 640,000 and two million smokers quitting smoking and between 210,000 and 700,000 quitters avoiding smoking-related premature death.
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Melnikow, Joy; Birch, Stephen; Slee, Christina; McCarthy, Theodore J; Helms, L Jay; Kuppermann, Miriam
2008-09-01
In cost-effectiveness analysis (CEA), the effects of health-care interventions on multiple health dimensions typically require consideration of both quantity and quality of life. To explore the impact of alternative approaches to quality-of-life adjustment using patient preferences (utilities) on the outcome of a CEA on use of tamoxifen for breast cancer risk reduction. A state transition Markov model tracked hypothetical cohorts of women who did or did not take 5 years of tamoxifen for breast cancer risk reduction. Incremental quality-adjusted effectiveness and cost-effectiveness ratios (ICERs) for models including and excluding a utility adjustment for menopausal symptoms were compared with each other and to a global utility model. Two hundred fifty-five women aged 50 and over with estimated 5-year breast cancer risk >or=1.67% participated in utility assessment interviews. Standard gamble utilities were assessed for specified tamoxifen-related health outcomes, current health, and for a global assessment of possible outcomes of tamoxifen use. Inclusion of a utility for menopausal symptoms in the outcome-specific models substantially increased the ICER; at the threshold 5-year breast cancer risk of 1.67%, tamoxifen was dominated. When a global utility for tamoxifen was used in place of outcome-specific utilities, tamoxifen was dominated under all circumstances. CEAs may be profoundly affected by the types of outcomes considered for quality-of-life adjustment and how these outcomes are grouped for utility assessment. Comparisons of ICERs across analyses must consider effects of different approaches to using utilities for quality-of-life adjustment.
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Darvishian, Maryam; van den Heuvel, Edwin R; Bissielo, Ange; Castilla, Jesus; Cohen, Cheryl; Englund, Helene; Gefenaite, Giedre; Huang, Wan-Ting; la Bastide-van Gemert, Sacha; Martinez-Baz, Iván; McAnerney, Johanna M; Ntshoe, Genevie M; Suzuki, Motoi; Turner, Nikki; Hak, Eelko
2017-03-01
Several aggregate data meta-analyses have provided estimates of the effectiveness of influenza vaccination in community-dwelling elderly people. However, these studies ignored the effects of patient-level confounders such as sex, age, and chronic diseases that could bias effectiveness estimates. We aimed to assess the confounder-adjusted effectiveness of influenza vaccines on laboratory-confirmed influenza among elderly people by conducting a global individual participant data meta-analysis. In this individual participant data meta-analysis, we considered studies included in a previously conducted aggregate data meta-analysis that included test-negative design case-control studies published up to July 13, 2014. We contacted all authors of the included studies on Dec 1, 2014, to request individual participant data. Patients were excluded if their unique identifier was missing, their vaccination status was unknown, their outcome status was unknown, or they had had suspected influenza infection more than once in the same influenza season. Cases were patients with influenza-like illness symptoms who tested positive for at least one of A H1N1, A H1N1 pdm09, A H3N2, or B viruses; controls were patients with influenza-like illness symptoms who tested negative for these virus types or subtypes. Influenza vaccine effectiveness against overall and subtype-specific laboratory-confirmed influenza were the primary and secondary outcomes. We used a generalised linear mixed model to calculate adjusted vaccine effectiveness according to vaccine match to the circulating strains of influenza virus and intensity of the virus activity (epidemic or non-epidemic). Vaccine effectiveness was defined as the relative reduction in risk of laboratory-confirmed influenza in vaccinated patients compared with unvaccinated patients. We did subgroup analyses to estimate vaccine effectiveness according to hemisphere, age category, and health status. We received 23 of the 53 datasets included in the aggregate data meta-analysis. Furthermore, six additional datasets were provided by data collaborators, which resulted in individual participant data for a total of 5210 participants. A total of 4975 patients had the required data for analysis. Of these, 3146 (63%) were controls and 1829 (37%) were cases. Influenza vaccination was significantly effective during epidemic seasons irrespective of vaccine match status (matched adjusted vaccine effectiveness 44·38%, 95% CI 22·63-60·01; mismatched adjusted vaccine effectiveness 20·00%, 95% CI 3·46-33·68; analyses in the imputed dataset). Seasonal influenza vaccination did not show significant effectiveness during non-epidemic seasons. We found substantial variation in vaccine effectiveness across virus types and subtypes, with the highest estimate for A H1N1 pdm09 (53·19%, 10·25-75·58) and the lowest estimate for B virus types (-1·52%, -39·58 to 26·16). Although we observed no significant differences between subgroups in each category (hemisphere, age, and health status), influenza vaccination showed a protective effect among elderly people with cardiovascular disease, lung disease, or aged 75 years and younger. Influenza vaccination is moderately effective against laboratory-confirmed influenza in elderly people during epidemic seasons. More research is needed to investigate factors affecting vaccine protection (eg, brand-specific or type-specific vaccine effectiveness and repeated annual vaccination) in elderly people. University Medical Center Groningen. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Maher, Gillian M; O'Keeffe, Gerard W; Kearney, Patricia M; Kenny, Louise C; Dinan, Timothy G; Mattsson, Molly; Khashan, Ali S
2018-06-06
Although research suggests an association between hypertensive disorders of pregnancy (HDP) and autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and other neurodevelopmental disorders in offspring, consensus is lacking. Given the increasing prevalence of hypertension in pregnancy, it is important to examine the association of HDP with neurodevelopmental outcome. To synthesize the published literature on the association between HDP and risk of neurodevelopmental disorders in offspring in a systematic review and meta-analysis. On the basis of a preprepared protocol, a systematic search of PubMed, CINAHL, Embase, PsycINFO, and Web of Science was performed from inception through June 7, 2017, supplemented by hand searching of reference lists. Two investigators independently reviewed titles, abstracts, and full-text articles. English-language cohort and case-control studies were included in which HDP and neurodevelopmental disorders were reported. Data extraction and quality appraisal were performed independently by 2 reviewers. Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed throughout. Random-effects meta-analyses of estimated pooled odds ratios (ORs) for HDP and ASD and for HDP and ADHD. Stand-alone estimates were reported for all other neurodevelopmental disorders. Of 1166 studies identified, 61 unique articles met inclusion criteria. Twenty studies reported estimates for ASD. Eleven of these (including 777 518 participants) reported adjusted estimates, with a pooled adjusted OR of 1.35 (95% CI, 1.11-1.64). Ten studies reported estimates for ADHD. Six of these (including 1 395 605 participants) reported adjusted estimates, with a pooled adjusted OR of 1.29 (95% CI, 1.22-1.36). Subgroup analyses according to type of exposure (ie, preeclampsia or other HDP) showed no statistically significant differences for ASD or ADHD. Thirty-one studies met inclusion criteria for all other neurodevelopmental disorders. Individual estimates reported for these were largely inconsistent, with few patterns of association observed. Exposure to HDP may be associated with an increase in the risk of ASD and ADHD. These findings highlight the need for greater pediatric surveillance of infants exposed to HDP to allow early intervention that may improve neurodevelopmental outcome.
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Hilderink, Henk B M; Plasmans, Marjanne H D; Snijders, Bianca E P; Boshuizen, Hendriek C; Poos, M J J C René; van Gool, Coen H
2016-01-01
Various Burden of Disease (BoD) studies do not account for multimorbidity in their BoD estimates. Ignoring multimorbidity can lead to inaccuracies in BoD estimations, particularly in ageing populations that include large proportions of persons with two or more health conditions. The objective of this study is to improve BoD estimates for the Netherlands by accounting for multimorbidity. For this purpose, we analyzed different methods for 1) estimating the prevalence of multimorbidity and 2) deriving Disability Weights (DWs) for multimorbidity by using existing data on single health conditions. We included 25 health conditions from the Dutch Burden of Disease study that have a high rate of prevalence and that make a large contribution to the total number of Years Lived with a Disability (YLD). First, we analyzed four methods for estimating the prevalence of multimorbid conditions (i.e. independent, independent age- and sex-specific, dependent, and dependent sex- and age-specific). Secondly, we analyzed three methods for calculating the Combined Disability Weights (CDWs) associated with multimorbid conditions (i.e. additive, multiplicative and maximum limit). A combination of these two approaches was used to recalculate the number of YLDs, which is a component of the Disability-Adjusted Life Years (DALY). This study shows that the YLD estimates for 25 health conditions calculated using the multiplicative method for Combined Disability Weights are 5 % lower, and 14 % lower when using the maximum limit method, than when calculated using the additive method. Adjusting for sex- and age-specific dependent co-occurrence of health conditions reduces the number of YLDs by 10 % for the multiplicative method and by 26 % for the maximum limit method. The adjustment is higher for health conditions with a higher prevalence in old age, like heart failure (up to 43 %) and coronary heart diseases (up to 33 %). Health conditions with a high prevalence in middle age, such as anxiety disorders, have a moderate adjustment (up to 13 %). We conclude that BoD calculations that do not account for multimorbidity can result in an overestimation of the actual BoD. This may affect public health policy strategies that focus on single health conditions if the underlying cost-effectiveness analysis overestimates the intended effects. The methodology used in this study could be further refined to provide greater insight into co-occurrence and the possible consequences of multimorbid conditions in terms of disability for particular combinations of health conditions.
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Cost-Effectiveness Analysis of the Introduction of HPV Vaccination of 9-Year-Old-Girls in Iran.
Yaghoubi, Mohsen; Nojomi, Marzieh; Vaezi, Atefeh; Erfani, Vida; Mahmoudi, Susan; Ezoji, Khadijeh; Zahraei, Seyed Mohsen; Chaudhri, Irtaza; Moradi-Lakeh, Maziar
2018-04-23
To estimate the cost effectiveness of introducing the quadrivalent human papillomavirus (HPV) vaccine into the national immunization program of Iran. The CERVIVAC cost-effectiveness model was used to calculate incremental cost per averted disability-adjusted life-year by vaccination compared with no vaccination from both governmental and societal perspectives. Calculations were based on epidemiologic parameters from the Iran National Cancer Registry and other national data sources as well as from literature review. We estimated all direct and indirect costs of cervical cancer treatment and vaccination program. All future costs and benefits were discounted at 3% per year and deterministic sensitivity analysis was used. During a 10-year period, HPV vaccination was estimated to avert 182 cervical cancer cases and 20 deaths at a total vaccination cost of US $23,459,897; total health service cost prevented because of HPV vaccination was estimated to be US $378,646 and US $691,741 from the governmental and societal perspective, respectively. Incremental cost per disability-adjusted life-year averted within 10 years was estimated to be US $15,205 and US $14,999 from the governmental and societal perspective, respectively, and both are higher than 3 times the gross domestic product per capita of Iran (US $14,289). Sensitivity analysis showed variation in vaccine price, and the number of doses has the greatest volatility on the incremental cost-effectiveness ratio. Using a two-dose vaccination program could be cost-effective from the societal perspective (incremental cost-effectiveness ratio = US $11,849). Introducing a three-dose HPV vaccination program is currently not cost-effective in Iran. Because vaccine supplies cost is the most important parameter in this evaluation, considering a two-dose schedule or reducing vaccine prices has an impact on final conclusions. Copyright © 2018. Published by Elsevier Inc.
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Søgaard, R; Lindholt, J S
2018-04-25
Population-based screening and intervention for abdominal aortic aneurysm, peripheral artery disease and hypertension was recently reported to reduce the relative risk of mortality among Danish men by 7 per cent. The aim of this study was to investigate the cost-effectiveness of vascular screening versus usual care (ad hoc primary care-based risk assessment) from a national health service perspective. A cost-effectiveness evaluation was conducted alongside an RCT involving all men from a region in Denmark (50 156) who were allocated to screening (25 078) or no screening (25 078) and followed for up to 5 years. Mobile nurse teams provided screening locally and, for individuals with positive test results, referrals were made to general practices or hospital-based specialized centres for vascular surgery. Intention-to-treat-based, censoring-adjusted incremental costs (2014 euros), life-years and quality-adjusted life-years (QALYs) were estimated using Lin's average estimator method. Incremental net benefit was estimated using Willan's estimator and sensitivity analyses were conducted. The cost of screening was estimated at €148 (95 per cent c.i. 126 to 169), and the effectiveness at 0·022 (95 per cent c.i. 0·006 to 0·038) life-years and 0·069 (0·054 to 0·083) QALYs, generating average costs of €6872 per life-year and €2148 per QALY. At a willingness-to-pay threshold of €40 000 per QALY, the probabilities of cost-effectiveness were 98 and 99 per cent respectively. The probability of cost-effectiveness was 71 per cent when all the sensitivity analyses were combined into one conservative scenario. Vascular screening appears to be cost-effective and compares favourably with current screening programmes. © 2018 BJS Society Ltd Published by John Wiley & Sons Ltd.
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Turner, N; Pierse, N; Bissielo, A; Huang, Qs; Radke, S; Baker, Mg; Widdowson, Ma; Kelly, H
2014-08-28
This study reports the first vaccine effectiveness (VE) estimates for the prevention of general practice visits and hospitalisations for laboratory-confirmed influenza from an urban population in Auckland, New Zealand, in the same influenza season (2013). A case test-negative design was used to estimate propensity-adjusted VE in both hospital and community settings. Patients with a severe acute respiratory infection (SARI) or influenza-like illness (ILI) were defined as requiring hospitalisation (SARI) or attending a general practice (ILI) with a history of fever or measured temperature ≥38 °C, cough and onset within the past 10 days. Those who tested positive for influenza virus were cases while those who tested negative were controls. Results were analysed to 7 days post symptom onset and adjusted for the propensity to be vaccinated and the timing during the influenza season. Influenza vaccination provided 52% (95% CI: 32 to 66) protection against laboratory-confirmed influenza hospitalisation and 56% (95% CI: 34 to 70) against presenting to general practice with influenza. VE estimates were similar for all types and subtypes. This study found moderate effectiveness of influenza vaccine against medically attended and hospitalised influenza in New Zealand, a temperate, southern hemisphere country during the 2013 winter season.
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Neugebauer, Romain; Fireman, Bruce; Roy, Jason A; Raebel, Marsha A; Nichols, Gregory A; O'Connor, Patrick J
2013-08-01
Clinical trials are unlikely to ever be launched for many comparative effectiveness research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data, but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called super learning (SL) to avoid reliance on arbitrary parametric assumptions in CER. Using the electronic health records data from adults with new-onset type 2 diabetes, we implemented MSM with inverse probability weighting (IPW) estimation to evaluate the effect of three oral antidiabetic therapies on the worsening of glomerular filtration rate. Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, that is, time-dependent measurements of hemoglobin A1c. SL was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms. Erroneous IPW inference about clinical effectiveness because of arbitrary and incorrect modeling decisions may be avoided with SL. Copyright © 2013 Elsevier Inc. All rights reserved.
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Health effects of people living close to a petrochemical industrial estate in Thailand.
Kongtip, Pornpimol; Singkaew, Panawadee; Yoosook, Witaya; Chantanakul, Suttinun; Sujiratat, Dusit
2013-12-01
An acute health effect of people living near the petrochemical industrial estate in Thailand was assessed using a panel study design. The populations in communities near the petrochemical industrial estates were recruited. The daily air pollutant concentrations, daily percentage of respiratory and other health symptoms reported were collected for 63 days. The effect of air pollutants to reported symptoms of people were estimated by adjusted odds ratios and 95% confidence interval using binary logistic regression. The significant associations were found with the adjusted odds ratios of 38.01 for wheezing, 18.63 for shortness of breath, 4.30 for eye irritation and 3.58 for dizziness for total volatile organic compounds (Total VOCs). The adjusted odds ratio for carbon monoxide (CO2) was 7.71 for cough, 4.55 for eye irritation and 3.53 for weakness and the adjusted odds ratio for ozone (O3) was 1.02 for nose congestion, sore throat and 1.05 for phlegm. The results showed that the people living near petrochemical industrial estate had acute adverse health effects, shortness of breath, eye irritation, dizziness, cough, nose congestion, sore throat, phlegm and weakness from exposure to industrial air pollutants.
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Adaptive noise reduction circuit for a sound reproduction system
NASA Technical Reports Server (NTRS)
Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)
1995-01-01
A noise reduction circuit for a hearing aid having an adaptive filter for producing a signal which estimates the noise components present in an input signal. The circuit includes a second filter for receiving the noise-estimating signal and modifying it as a function of a user's preference or as a function of an expected noise environment. The circuit also includes a gain control for adjusting the magnitude of the modified noise-estimating signal, thereby allowing for the adjustment of the magnitude of the circuit response. The circuit also includes a signal combiner for combining the input signal with the adjusted noise-estimating signal to produce a noise reduced output signal.
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Chalayer, Emilie; Bourmaud, Aurélie; Tinquaut, Fabien; Chauvin, Franck; Tardy, Bernard
2016-09-01
The aim of this study was to assess the cost-effectiveness of low molecular weight heparin versus aspirin as primary thromboprophylaxis throughout chemotherapy for newly diagnosed multiple myeloma patients treated with protocols including thalidomide from the perspective of French health care providers. We used a modeling approach combining data from the only randomized trial evaluating the efficacy of the two treatments and secondary sources for costs, and utility values. We performed a decision-tree analysis and our base case was a hypothetical cohort of 10,000 patients. A bootstrap resampling technique was used. The incremental cost-effectiveness ratio was calculated using estimated quality-adjusted life years as the efficacy outcome. Incremental costs and effectiveness were estimated for each strategy and the incremental cost-effectiveness ratio was calculated. One-way sensitivity analyses were performed. The number of quality-adjusted life years was estimated to be 0.300 with aspirin and 0.299 with heparin. The estimated gain with aspirin was therefore approximately one day. Over 6months, the mean total cost was € 1518 (SD=601) per patient in the heparin arm and € 273 (SD=1019) in the aspirin arm. This resulted in an incremental cost of € 1245 per patient treated with heparin. The incremental cost-effectiveness ratio for the aspirin versus heparin strategy was calculated to be - 687,398 € (95% CI, -13,457,369 to -225,385). Aspirin rather than heparin thromboprophylaxis, during the first six months of chemotherapy for myeloma, is associated with significant cost savings per patient and also with an unexpected slight increase in quality of life. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Rheumatoid arthritis prevalence in Quebec.
Bernatsky, Sasha; Dekis, Alaa; Hudson, Marie; Pineau, Christian A; Boire, Gilles; Fortin, Paul R; Bessette, Louis; Jean, Sonia; Chetaille, Ann L; Belisle, Patrick; Bergeron, Louise; Feldman, Debbie Ehrmann; Joseph, Lawrence
2014-12-19
To estimate rheumatoid arthritis (RA) prevalence in Quebec using administrative health data, comparing across regions. Cases of RA were ascertained from physician billing and hospitalization data, 1992-2008. We used three case definitions: 1) ≥ 2 billing diagnoses, submitted by any physician, ≥ 2 months apart, but within 2 years; 2) ≥ 1 diagnosis, by a rheumatologist; 3) ≥1 hospitalization diagnosis (all based on ICD-9 code 714, and ICD-10 code M05). We combined data across these three case definitions, using Bayesian hierarchical latent class models to estimate RA prevalence, adjusting for the imperfect sensitivity and specificity of the data. We compared urban versus rural regions. Using our case definitions and no adjustment for error, we defined 75,760 cases for an over-all RA prevalence of 9.9 per thousand residents. After adjusting for the imperfect sensitivity and specificity of our case definition algorithms, we estimated Quebec RA prevalence at 5.6 per 1000 females and 4.1 per 1000 males. The adjusted RA prevalence estimates for older females were the highest for any demographic group (9.9 cases per 1,000), and were similar in rural and urban regions. In younger males and females, and in older males, RA prevalence estimates were lower in rural versus urban areas. Without adjustment for error inherent in administrative databases, RA prevalence in Quebec was approximately 1%, while adjusted estimates are approximately half that. The lower prevalence in rural areas, seen for most demographic groups, may suggest either true regional variations in RA risk, or under-ascertainment of cases in rural Quebec.
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Defense Acquisition Research Journal. Volume 18, Number 3, Issue 59, July 2011
2011-07-01
cost estimate. Thus, it is important to adjust the original cost estimates reflected in the first SAR to account for the changes in the quan- tity...effect on the model (Figure 6). To account for this possibility, taBLE 4. oLS RESuLtS: PRoCuREMENt CoSt GRoWtH vS. aCtuaL CoNCuRRENCY Estimate Std...Kelley & Watkins, 1998). The pattern in which a relatively small proportion of programs account for virtually all of MDAP cost growth cannot be
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Assessment of spatial variation of risks in small populations.
Riggan, W B; Manton, K G; Creason, J P; Woodbury, M A; Stallard, E
1991-01-01
Often environmental hazards are assessed by examining the spatial variation of disease-specific mortality or morbidity rates. These rates, when estimated for small local populations, can have a high degree of random variation or uncertainty associated with them. If those rate estimates are used to prioritize environmental clean-up actions or to allocate resources, then those decisions may be influenced by this high degree of uncertainty. Unfortunately, the effect of this uncertainty is not to add "random noise" into the decision-making process, but to systematically bias action toward the smallest populations where uncertainty is greatest and where extreme high and low rate deviations are most likely to be manifest by chance. We present a statistical procedure for adjusting rate estimates for differences in variability due to differentials in local area population sizes. Such adjustments produce rate estimates for areas that have better properties than the unadjusted rates for use in making statistically based decisions about the entire set of areas. Examples are provided for county variation in bladder, stomach, and lung cancer mortality rates for U.S. white males for the period 1970 to 1979. PMID:1820268
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Patrick, Amanda R; Schousboe, John T; Losina, Elena; Solomon, Daniel H
2011-09-01
Adherence to osteoporosis treatment is low. Although new therapies and behavioral interventions may improve medication adherence, questions are likely to arise regarding their cost-effectiveness. Our objectives were to develop and validate a model to simulate the clinical outcomes and costs arising from various osteoporosis medication adherence patterns among women initiating bisphosphonate treatment and to estimate the cost-effectiveness of a hypothetical intervention to improve medication adherence. We constructed a computer simulation using estimates of fracture rates, bisphosphonate treatment effects, costs, and utilities for health states drawn from the published literature. Probabilities of transitioning on and off treatment were estimated from administrative claims data. Patients were women initiating bisphosphonate therapy from the general community. We evaluated a hypothetical behavioral intervention to improve medication adherence. Changes in 10-yr fracture rates and incremental cost-effectiveness ratios were evaluated. A hypothetical intervention with a one-time cost of $250 and reducing bisphosphonate discontinuation by 30% had an incremental cost-effectiveness ratio (ICER) of $29,571 per quality-adjusted life year in 65-yr-old women initiating bisphosphonates. Although the ICER depended on patient age, intervention effectiveness, and intervention cost, the ICERs were less than $50,000 per quality-adjusted life year for the majority of intervention cost and effectiveness scenarios evaluated. Results were sensitive to bisphosphonate cost and effectiveness and assumptions about the rate at which intervention and treatment effects decline over time. Our results suggests that behavioral interventions to improve osteoporosis medication adherence will likely have favorable ICERs if their efficacy can be sustained.
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Ekerstad, Niklas; Karlson, Björn W; Andersson, David; Husberg, Magnus; Carlsson, Per; Heintz, Emelie; Alwin, Jenny
2018-05-18
The objective of this study was to estimate the 3-month within-trial cost-effectiveness of comprehensive geriatric assessment (CGA) in acute medical care for frail elderly patients compared to usual medical care, by estimating health-related quality of life and costs from a societal perspective. Clinical, prospective, controlled, 1-center intervention trial with 2 parallel groups. Structured, systematic interdisciplinary CGA-based care in an acute elderly care unit. If the patient fulfilled the inclusion criteria, and there was a bed available at the CGA unit, the patient was included in the intervention group. If no bed was available at the CGA unit, the patient was included in the control group and admitted to a conventional acute medical care unit. A large county hospital in western Sweden. The trial included 408 frail elderly patients, 75 years or older, in need of acute in-hospital treatment. The patients were allocated to the intervention group (n = 206) or control group (n = 202). Mean age of the patients was 85.7 years, and 56% were female. The primary outcome was the adjusted incremental cost-effectiveness ratio associated with the intervention compared to the control at the 3-month follow-up. We undertook cost-effectiveness analysis, adjusted by regression analyses, including hospital, primary, and municipal care costs and effects. The difference in the mean adjusted quality-adjusted life years gained between groups at 3 months was 0.0252 [95% confidence interval (CI): 0.0082-0.0422]. The incremental cost, that is, the difference between the groups, was -3226 US dollars (95% CI: -6167 to -285). The results indicate that the care in a CGA unit for acutely ill frail elderly patients is likely to be cost-effective compared to conventional care after 3 months. Copyright © 2018 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.
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Enhanced Estimates of the Influenza Vaccination Effect in Preventing Mortality
Castilla, Jesús; Guevara, Marcela; Martínez-Baz, Iván; Ezpeleta, Carmen; Delfrade, Josu; Irisarri, Fátima; Moreno-Iribas, Conchi
2015-01-01
Abstract Mortality is a major end-point in the evaluation of influenza vaccine effectiveness. However, this effect is not well known, since most previous studies failed to show good control of biases. We aimed to estimate the effectiveness of influenza vaccination in preventing all-cause mortality in community-dwelling seniors. Since 2009, a population-based cohort study using healthcare databases has been conducted in Navarra, Spain. In 2 late influenza seasons, 2011/2012 and 2012/2013, all-cause mortality in the period January to May was compared between seniors (65 years or over) who received the trivalent influenza vaccine and those who were unvaccinated, adjusting for demographics, major chronic conditions, dependence, previous hospitalization, and pneumococcal vaccination. The cohort included 103,156 seniors in the 2011/2012 season and 105,140 in the 2012/2013 season (58% vaccinated). Seniors vaccinated in the previous season who discontinued vaccination (6% of the total) had excess mortality and were excluded to prevent frailty bias. The final analysis included 80,730 person-years and 2778 deaths. Vaccinated seniors had 16% less all-cause mortality than those unvaccinated (adjusted rate ratio [RR] = 0.84; 95% confidence interval 0.76–0.93). This association disappeared in the post-influenza period (adjusted RR = 0.96; 95% confidence interval 0.85–1.09). A similar comparison did not find an association in January to May of the 2009/2010 pandemic season (adjusted RR = 0.98; 95% confidence interval 0.84–1.14), when no effect of the seasonal vaccine was expected. On average, 1 death was prevented for every 328 seniors vaccinated: 1 for every 649 in the 65 to 74 year age group and 1 for every 251 among those aged 75 and over. These results suggest a moderate preventive effect and a high potential impact of the seasonal influenza vaccine against all-cause mortality. This reinforces the recommendation of annual influenza vaccination in seniors. PMID:26222861
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Tian, Yao; Sweeney, John F; Wulkan, Mark L; Heiss, Kurt F; Raval, Mehul V
2016-06-01
Hospitals are increasingly focused on demonstration of high-value care for common surgical procedures. Although sociodemographic status (SDS) factors have been tied to various surgical outcomes, the impact of SDS factors on hospital value rankings has not been well explored. Our objective was to examine effects of SDS factors on high-value surgical care at the patient level, and to illustrate the importance of SDS adjustment when evaluating hospital-level performance. Perforated appendicitis hospitalizations were identified from the 2012 Kids' Inpatient Database. The primary outcome of interest was high-value care as defined by evaluation of duration of stay and cost. SDS factors included race, health insurance type, median household income, and patient location. The impact of SDS on high-value care was estimated using regression models after accounting for hospital-level variation. Risk-adjusted value rankings were compared before and after adjustment for SDS. From 9,986 hospitalizations, 998 high-value encounters were identified. African Americans were less likely to experience high-value care compared with white patients after adjusting for all SDS variables. Although private insurance and living in nonmetro counties were associated independently with high-value care, the effects were attenuated in the fully adjusted models. For the 136 hospitals ranked according to risk-adjusted value status, 59 hospitals' rankings improved after adjustment and 53 hospitals' rankings declined. After adjustment for patient and hospital factors, SDS has a small but significant impact on risk-adjusted hospital performance ranking for pediatric appendicitis. Adjustment for SDS should be considered in future comparative performance assessment. Copyright © 2016 Elsevier Inc. All rights reserved.
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Jones-Jordan, Lisa A.; Sinnott, Loraine T.; Graham, Nicholas D.; Cotter, Susan A.; Kleinstein, Robert N.; Manny, Ruth E.; Mutti, Donald O.; Twelker, J. Daniel; Zadnik, Karla
2014-01-01
Purpose. We determined the correlation between sibling refractive errors adjusted for shared and unique environmental factors using data from the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEERE) Study. Methods. Refractive error from subjects' last study visits was used to estimate the intraclass correlation coefficient (ICC) between siblings. The correlation models used environmental factors (diopter-hours and outdoor/sports activity) assessed annually from parents by survey to adjust for shared and unique environmental exposures when estimating the heritability of refractive error (2*ICC). Results. Data from 700 families contributed to the between-sibling correlation for spherical equivalent refractive error. The mean age of the children at the last visit was 13.3 ± 0.90 years. Siblings engaged in similar amounts of near and outdoor activities (correlations ranged from 0.40–0.76). The ICC for spherical equivalent, controlling for age, sex, ethnicity, and site was 0.367 (95% confidence interval [CI] = 0.304, 0.420), with an estimated heritability of no more than 0.733. After controlling for these variables, and near and outdoor/sports activities, the resulting ICC was 0.364 (95% CI = 0.304, 0.420; estimated heritability no more than 0.728, 95% CI = 0.608, 0.850). The ICCs did not differ significantly between male–female and single sex pairs. Conclusions. Adjusting for shared family and unique, child-specific environmental factors only reduced the estimate of refractive error correlation between siblings by 0.5%. Consistent with a lack of association between myopia progression and either near work or outdoor/sports activity, substantial common environmental exposures had little effect on this correlation. Genetic effects appear to have the major role in determining the similarity of refractive error between siblings. PMID:25205866
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NASA Technical Reports Server (NTRS)
Meyer, Kerry; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin
2013-01-01
Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.
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TREATMENT SWITCHING: STATISTICAL AND DECISION-MAKING CHALLENGES AND APPROACHES.
Latimer, Nicholas R; Henshall, Chris; Siebert, Uwe; Bell, Helen
2016-01-01
Treatment switching refers to the situation in a randomized controlled trial where patients switch from their randomly assigned treatment onto an alternative. Often, switching is from the control group onto the experimental treatment. In this instance, a standard intention-to-treat analysis does not identify the true comparative effectiveness of the treatments under investigation. We aim to describe statistical methods for adjusting for treatment switching in a comprehensible way for nonstatisticians, and to summarize views on these methods expressed by stakeholders at the 2014 Adelaide International Workshop on Treatment Switching in Clinical Trials. We describe three statistical methods used to adjust for treatment switching: marginal structural models, two-stage adjustment, and rank preserving structural failure time models. We draw upon discussion heard at the Adelaide International Workshop to explore the views of stakeholders on the acceptability of these methods. Stakeholders noted that adjustment methods are based on assumptions, the validity of which may often be questionable. There was disagreement on the acceptability of adjustment methods, but consensus that when these are used, they should be justified rigorously. The utility of adjustment methods depends upon the decision being made and the processes used by the decision-maker. Treatment switching makes estimating the true comparative effect of a new treatment challenging. However, many decision-makers have reservations with adjustment methods. These, and how they affect the utility of adjustment methods, require further exploration. Further technical work is required to develop adjustment methods to meet real world needs, to enhance their acceptability to decision-makers.
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The cost-effectiveness of rotavirus vaccination in Malawi.
Berry, Stephen A; Johns, Benjamin; Shih, Chuck; Berry, Andrea A; Walker, Damian G
2010-09-01
Rotarix (GlaxoSmithKline), a newly licensed rotavirus vaccine requiring 2 doses, may have the potential to save hundreds of thousands of lives in Africa. Nations such as Malawi, where Rotarix is currently under phase III investigation, may nevertheless face difficult economic choices in considering vaccine adoption. The cost-effectiveness of implementing a Rotarix vaccine program in Malawi was estimated using published estimates of rotavirus burden, vaccine efficacy, and health care utilization and costs. With 49.5% vaccine efficacy, a Rotarix program could avert 2582 deaths annually. With GAVI Alliance cofinancing, adoption of Rotarix would be associated with a cost of $5.07 per disability-adjusted life-year averted. With market pricing, Rotarix would be associated with a base case cost of $74.73 per disability-adjusted life-year averted. Key variables influencing results were vaccine efficacy, under-2 rotavirus mortality, and program cost of administering each dose. Adopting Rotarix would likely be highly cost-effective for Malawi, particularly with GAVI support. This finding holds true across uncertainty ranges for key variables, including efficacy, for which data are becoming available.
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MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.
Hedeker, D; Gibbons, R D
1996-05-01
MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.
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Adverse effects of hurricanes are increasing as coastal populations grow and events become more severe. Hurricane exposure during pregnancy can influence fetal death rates through mechanisms related to healthcare, infrastructure disruption, nutrition, and injury. Estimation of hu...
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TEMPERATURE CORRECTION FORMULAE FOR ADJUSTING ESTIMATES OF EMISSIONS FROM AUTOMOBILES. VOLUME I
This report describes an analysis of the effects of temperature on the emissions of hydrocarbons, carbon monoxide, and oxides of nitrogen from autombiles. The analysis was conducted by Vector Research, Incorporated, (VRI) For the Environmental Protection Agency (EPA). The analysi...
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Effect of Placenta Previa on Fetal Growth
HARPER, Lorie M.; ODIBO, Anthony O.; MACONES, George A.; CRANE, James P.; CAHILL, Alison G.
2011-01-01
Objective To estimate the association between placenta previa and abnormal fetal growth. Study Design Retrospective cohort study of consecutive women undergoing ultrasound between 15–22 weeks. Groups were defined by the presence or absence of complete or partial placenta previa. The primary outcome was intrauterine growth restriction (IUGR), defined as a birth weight <10th percentile by the Alexander growth standard. Univariable, stratified and multivariable analyses were used to estimate the effect of placenta previa on fetal growth restriction. Results Of 59,149 women, 724 (1.2%) were diagnosed with a complete or partial previa. After adjusting for significant confounding factors (black race, gestational diabetes, preeclampsia, and single umbilical artery,), the risk of IUGR remained similar (adjusted odds ratio 1.1, 95% CI 0.9–1.5). The presence of bleeding did not impact the risk of growth restriction. Conclusion Placenta previa is not associated with fetal growth restriction. Serial growth ultrasounds are not indicated in patients with placenta previa. PMID:20599185
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Malekzadeh, Mohammad; Abedini Najafabadi, Hamed; Hakim, Maziar; Feilizadeh, Mehrzad; Vossoughi, Manouchehr; Rashtchian, Davood
2016-02-01
In this research, organic solvent composed of hexane and methanol was used for lipid extraction from dry and wet biomass of Chlorella vulgaris. The results indicated that lipid and fatty acid extraction yield was decreased by increasing the moisture content of biomass. However, the maximum extraction efficiency was attained by applying equivolume mixture of hexane and methanol for both dry and wet biomass. Thermodynamic modeling was employed to estimate the effect of hexane/methanol ratio and moisture content on fatty acid extraction yield. Hansen solubility parameter was used in adjusting the interaction parameters of the model, which led to decrease the number of tuning parameters from 6 to 2. The results indicated that the model can accurately estimate the fatty acid recovery with average absolute deviation percentage (AAD%) of 13.90% and 15.00% for the two cases of using 6 and 2 adjustable parameters, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.
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2011-01-01
Background Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity. Methods Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures. Results The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group. Conclusions Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself. PMID:21504612
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Kaufman, Jay S; MacLehose, Richard F; Torrone, Elizabeth A; Savitz, David A
2011-04-19
Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity. Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures. The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group. Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself.
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Coresh, Josef; Turin, Tanvir Chowdhury; Matsushita, Kunihiro; Sang, Yingying; Ballew, Shoshana H; Appel, Lawrence J; Arima, Hisatomi; Chadban, Steven J; Cirillo, Massimo; Djurdjev, Ognjenka; Green, Jamie A; Heine, Gunnar H; Inker, Lesley A; Irie, Fujiko; Ishani, Areef; Ix, Joachim H; Kovesdy, Csaba P; Marks, Angharad; Ohkubo, Takayoshi; Shalev, Varda; Shankar, Anoop; Wen, Chi Pang; de Jong, Paul E; Iseki, Kunitoshi; Stengel, Benedicte; Gansevoort, Ron T; Levey, Andrew S
2014-06-25
The established chronic kidney disease (CKD) progression end point of end-stage renal disease (ESRD) or a doubling of serum creatinine concentration (corresponding to a change in estimated glomerular filtration rate [GFR] of −57% or greater) is a late event. To characterize the association of decline in estimated GFR with subsequent progression to ESRD with implications for using lesser declines in estimated GFR as potential alternative end points for CKD progression. Because most people with CKD die before reaching ESRD, mortality risk also was investigated. Individual meta-analysis of 1.7 million participants with 12,344 ESRD events and 223,944 deaths from 35 cohorts in the CKD Prognosis Consortium with a repeated measure of serum creatinine concentration over 1 to 3 years and outcome data. Transfer of individual participant data or standardized analysis of outputs for random-effects meta-analysis conducted between July 2012 and September 2013, with baseline estimated GFR values collected from 1975 through 2012. End-stage renal disease (initiation of dialysis or transplantation) or all-cause mortality risk related to percentage change in estimated GFR over 2 years, adjusted for potential confounders and first estimated GFR. The adjusted hazard ratios (HRs) of ESRD and mortality were higher with larger estimated GFR decline. Among participants with baseline estimated GFR of less than 60 mL/min/1.73 m2, the adjusted HRs for ESRD were 32.1 (95% CI, 22.3-46.3) for changes of −57% in estimated GFR and 5.4 (95% CI, 4.5-6.4) for changes of −30%. However, changes of −30% or greater (6.9% [95% CI, 6.4%-7.4%] of the entire consortium) were more common than changes of −57% (0.79% [95% CI, 0.52%-1.06%]). This association was strong and consistent across the length of the baseline period (1 to 3 years), baseline estimated GFR, age, diabetes status, or albuminuria. Average adjusted 10-year risk of ESRD (in patients with a baseline estimated GFR of 35 mL/min/1.73 m2) was 99% (95% CI, 95%-100%) for estimated GFR change of −57%, was 83% (95% CI, 71%-93%) for estimated GFR change of −40%, and was 64% (95% CI, 52%-77%) for estimated GFR change of −30% vs 18% (95% CI, 15%-22%) for estimated GFR change of 0%. Corresponding mortality risks were 77% (95% CI, 71%-82%), 60% (95% CI, 56%-63%), and 50% (95% CI, 47%-52%) vs 32% (95% CI, 31%-33%), showing a similar but weaker pattern. Declines in estimated GFR smaller than a doubling of serum creatinine concentration occurred more commonly and were strongly and consistently associated with the risk of ESRD and mortality, supporting consideration of lesser declines in estimated GFR (such as a 30% reduction over 2 years) as an alternative end point for CKD progression.
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Yiannoutsos, Constantin T; An, Ming-Wen; Frangakis, Constantine E; Musick, Beverly S; Braitstein, Paula; Wools-Kaloustian, Kara; Ochieng, Daniel; Martin, Jeffrey N; Bacon, Melanie C; Ochieng, Vincent; Kimaiyo, Sylvester
2008-01-01
Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices. In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3-4 disease (47.5% versus 41.1%; p<0.001). Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%-2.0%), revised to 2.8% (2.3%-3.1%) when deaths discovered through outreach were added and adjusted to 9.2% (7.8%-10.6%) and 9.9% (8.4%-11.5%) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%-2.2%), 3.4% (2.9%-4.0%), 10.5% (8.7%-12.3%) and 10.7% (8.9%-12.6%) respectively. CONCLUSIONS/SIGNIFICANCE ABSTRACT: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs.
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Li, Lingling; Kulldorff, Martin; Russek-Cohen, Estelle; Kawai, Alison Tse; Hua, Wei
2015-12-01
The self-controlled risk interval design is commonly used to assess the association between an acute exposure and an adverse event of interest, implicitly adjusting for fixed, non-time-varying covariates. Explicit adjustment needs to be made for time-varying covariates, for example, age in young children. It can be performed via either a fixed or random adjustment. The random-adjustment approach can provide valid point and interval estimates but requires access to individual-level data for an unexposed baseline sample. The fixed-adjustment approach does not have this requirement and will provide a valid point estimate but may underestimate the variance. We conducted a comprehensive simulation study to evaluate their performance. We designed the simulation study using empirical data from the Food and Drug Administration-sponsored Mini-Sentinel Post-licensure Rapid Immunization Safety Monitoring Rotavirus Vaccines and Intussusception study in children 5-36.9 weeks of age. The time-varying confounder is age. We considered a variety of design parameters including sample size, relative risk, time-varying baseline risks, and risk interval length. The random-adjustment approach has very good performance in almost all considered settings. The fixed-adjustment approach can be used as a good alternative when the number of events used to estimate the time-varying baseline risks is at least the number of events used to estimate the relative risk, which is almost always the case. We successfully identified settings in which the fixed-adjustment approach can be used as a good alternative and provided guidelines on the selection and implementation of appropriate analyses for the self-controlled risk interval design. Copyright © 2015 John Wiley & Sons, Ltd.
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Regression discontinuity was a valid design for dichotomous outcomes in three randomized trials.
van Leeuwen, Nikki; Lingsma, Hester F; Mooijaart, Simon P; Nieboer, Daan; Trompet, Stella; Steyerberg, Ewout W
2018-06-01
Regression discontinuity (RD) is a quasi-experimental design that may provide valid estimates of treatment effects in case of continuous outcomes. We aimed to evaluate validity and precision in the RD design for dichotomous outcomes. We performed validation studies in three large randomized controlled trials (RCTs) (Corticosteroid Randomization After Significant Head injury [CRASH], the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries [GUSTO], and PROspective Study of Pravastatin in elderly individuals at risk of vascular disease [PROSPER]). To mimic the RD design, we selected patients above and below a cutoff (e.g., age 75 years) randomized to treatment and control, respectively. Adjusted logistic regression models using restricted cubic splines (RCS) and polynomials and local logistic regression models estimated the odds ratio (OR) for treatment, with 95% confidence intervals (CIs) to indicate precision. In CRASH, treatment increased mortality with OR 1.22 [95% CI 1.06-1.40] in the RCT. The RD estimates were 1.42 (0.94-2.16) and 1.13 (0.90-1.40) with RCS adjustment and local regression, respectively. In GUSTO, treatment reduced mortality (OR 0.83 [0.72-0.95]), with more extreme estimates in the RD analysis (OR 0.57 [0.35; 0.92] and 0.67 [0.51; 0.86]). In PROSPER, similar RCT and RD estimates were found, again with less precision in RD designs. We conclude that the RD design provides similar but substantially less precise treatment effect estimates compared with an RCT, with local regression being the preferred method of analysis. Copyright © 2018 Elsevier Inc. All rights reserved.
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Lash, Timothy L
2007-11-26
The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is likely to lead to overconfidence regarding the potential for causal associations, whereas the former safeguards against such overinterpretations. Furthermore, such analyses, once programmed, allow rapid implementation of alternative assignments of probability distributions to the bias parameters, so elevate the plane of discussion regarding study bias from characterizing studies as "valid" or "invalid" to a critical and quantitative discussion of sources of uncertainty.
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Ride, Jemimah; Lorgelly, Paula; Tran, Thach; Wynter, Karen; Rowe, Heather; Fisher, Jane
2016-11-18
Postnatal maternal mental health problems, including depression and anxiety, entail a significant burden globally, and finding cost-effective preventive solutions is a public policy priority. This paper presents a cost-effectiveness analysis of the intervention, What Were We Thinking (WWWT), for the prevention of postnatal maternal mental health problems. The economic evaluation, including cost-effectiveness and cost-utility analyses, was conducted alongside a cluster-randomised trial. 48 Maternal and Child Health Centres in Victoria, Australia. Participants were English-speaking first-time mothers attending participating Maternal and Child Health Centres. Full data were collected for 175 participants in the control arm and 184 in the intervention arm. WWWT is a psychoeducational intervention targeted at the partner relationship, management of infant behaviour and parental fatigue. The evaluation considered public sector plus participant out-of-pocket costs, while outcomes were expressed in the 30-day prevalence of depression, anxiety and adjustment disorders, and quality-adjusted life years (QALYs). Incremental costs and outcomes were estimated using regression analyses to account for relevant sociodemographic, prognostic and clinical characteristics. The intervention was estimated to cost $A118.16 per participant. The analysis showed no statistically significant difference between the intervention and control groups in costs or outcomes. The incremental cost-effectiveness ratios were $A36 451 per QALY gained and $A152 per percentage-point reduction in 30-day prevalence of depression, anxiety and adjustment disorders. The estimate lies under the unofficial cost-effectiveness threshold of $A55 000 per QALY; however, there was considerable uncertainty surrounding the results, with a 55% probability that WWWT would be considered cost-effective at that threshold. The results suggest that, although WWWT shows promise as a preventive intervention for postnatal maternal mental health problems, further research is required to reduce the uncertainty over its cost-effectiveness as there were no statistically significant differences in costs or outcomes. ACTRN12613000506796; results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
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Ride, Jemimah; Lorgelly, Paula; Tran, Thach; Wynter, Karen; Rowe, Heather; Fisher, Jane
2016-01-01
Objectives Postnatal maternal mental health problems, including depression and anxiety, entail a significant burden globally, and finding cost-effective preventive solutions is a public policy priority. This paper presents a cost-effectiveness analysis of the intervention, What Were We Thinking (WWWT), for the prevention of postnatal maternal mental health problems. Design The economic evaluation, including cost-effectiveness and cost-utility analyses, was conducted alongside a cluster-randomised trial. Setting 48 Maternal and Child Health Centres in Victoria, Australia. Participants Participants were English-speaking first-time mothers attending participating Maternal and Child Health Centres. Full data were collected for 175 participants in the control arm and 184 in the intervention arm. Intervention WWWT is a psychoeducational intervention targeted at the partner relationship, management of infant behaviour and parental fatigue. Outcome measures The evaluation considered public sector plus participant out-of-pocket costs, while outcomes were expressed in the 30-day prevalence of depression, anxiety and adjustment disorders, and quality-adjusted life years (QALYs). Incremental costs and outcomes were estimated using regression analyses to account for relevant sociodemographic, prognostic and clinical characteristics. Results The intervention was estimated to cost $A118.16 per participant. The analysis showed no statistically significant difference between the intervention and control groups in costs or outcomes. The incremental cost-effectiveness ratios were $A36 451 per QALY gained and $A152 per percentage-point reduction in 30-day prevalence of depression, anxiety and adjustment disorders. The estimate lies under the unofficial cost-effectiveness threshold of $A55 000 per QALY; however, there was considerable uncertainty surrounding the results, with a 55% probability that WWWT would be considered cost-effective at that threshold. Conclusions The results suggest that, although WWWT shows promise as a preventive intervention for postnatal maternal mental health problems, further research is required to reduce the uncertainty over its cost-effectiveness as there were no statistically significant differences in costs or outcomes. Trial registration number ACTRN12613000506796; results. PMID:27864246
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Tosteson, Tor D.; Morden, Nancy E.; Stukel, Therese A.; O'Malley, A. James
2014-01-01
The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival. PMID:25506259
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MacKenzie, Todd A; Tosteson, Tor D; Morden, Nancy E; Stukel, Therese A; O'Malley, A James
2014-06-01
The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival.
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Hade, Erinn M; Murray, David M; Pennell, Michael L; Rhoda, Dale; Paskett, Electra D; Champion, Victoria L; Crabtree, Benjamin F; Dietrich, Allen; Dignan, Mark B; Farmer, Melissa; Fenton, Joshua J; Flocke, Susan; Hiatt, Robert A; Hudson, Shawna V; Mitchell, Michael; Monahan, Patrick; Shariff-Marco, Salma; Slone, Stacey L; Stange, Kurt; Stewart, Susan L; Strickland, Pamela A Ohman
2010-01-01
Screening has become one of our best tools for early detection and prevention of cancer. The group-randomized trial is the most rigorous experimental design for evaluating multilevel interventions. However, identifying the proper sample size for a group-randomized trial requires reliable estimates of intraclass correlation (ICC) for screening outcomes, which are not available to researchers. We present crude and adjusted ICC estimates for cancer screening outcomes for various levels of aggregation (physician, clinic, and county) and provide an example of how these ICC estimates may be used in the design of a future trial. Investigators working in the area of cancer screening were contacted and asked to provide crude and adjusted ICC estimates using the analysis of variance method estimator. Of the 29 investigators identified, estimates were obtained from 10 investigators who had relevant data. ICC estimates were calculated from 13 different studies, with more than half of the studies collecting information on colorectal screening. In the majority of cases, ICC estimates could be adjusted for age, education, and other demographic characteristics, leading to a reduction in the ICC. ICC estimates varied considerably by cancer site and level of aggregation of the groups. Previously, only two articles had published ICCs for cancer screening outcomes. We have complied more than 130 crude and adjusted ICC estimates covering breast, cervical, colon, and prostate screening and have detailed them by level of aggregation, screening measure, and study characteristics. We have also demonstrated their use in planning a future trial and the need for the evaluation of the proposed interval estimator for binary outcomes under conditions typically seen in GRTs.
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Boone-Heinonen, Janne; Guilkey, David K; Evenson, Kelly R; Gordon-Larsen, Penny
2010-10-04
Built environment research is dominated by cross-sectional designs, which are particularly vulnerable to residential self-selection bias resulting from health-related attitudes, neighborhood preferences, or other unmeasured characteristics related to both neighborhood choice and health-related outcomes. We used cohort data from the National Longitudinal Study of Adolescent Health (United States; Wave I, 1994-95; Wave III, 2001-02; n = 12,701) and a time-varying geographic information system. Longitudinal relationships between moderate to vigorous physical activity (MVPA) bouts and built and socioeconomic environment measures (landcover diversity, pay and public physical activity facilities per 10,000 population, street connectivity, median household income, and crime rate) from adolescence to young adulthood were estimated using random effects models (biased by unmeasured confounders) and fixed effects models (within-person estimator, which adjusts for unmeasured confounders that are stable over time). Random effects models yielded null associations except for negative crime-MVPA associations [coefficient (95% CI): -0.056 (-0.083, -0.029) in males, -0.061 (-0.090, -0.033) in females]. After controlling for measured and time invariant unmeasured characteristics using within-person estimators, MVPA was higher with greater physical activity pay facilities in males [coefficient (95% CI): 0.024 (0.006, 0.042)], and lower with higher crime rates in males [coefficient (95% CI): -0.107 (-0.140, -0.075)] and females [coefficient (95% CI): -0.046 (-0.083, -0.009)]. Other associations were null or in the counter-intuitive direction. Comparison of within-person estimates to estimates unadjusted for unmeasured characteristics suggest that residential self-selection can bias associations toward the null, as opposed to its typical characterization as a positive confounder. Differential environment-MVPA associations by residential relocation suggest that studies examining changes following residential relocation may be vulnerable to selection bias. The authors discuss complexities of adjusting for residential self-selection and residential relocation, particularly during the adolescent to young adult transition.
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Tao, L; Wilson, E C F; Wareham, N J; Sandbæk, A; Rutten, G E H M; Lauritzen, T; Khunti, K; Davies, M J; Borch-Johnsen, K; Griffin, S J; Simmons, R K
2015-01-01
Aims To examine the short- and long-term cost-effectiveness of intensive multifactorial treatment compared with routine care among people with screen-detected Type 2 diabetes. Methods Cost–utility analysis in ADDITION-UK, a cluster-randomized controlled trial of early intensive treatment in people with screen-detected diabetes in 69 UK general practices. Unit treatment costs and utility decrement data were taken from published literature. Accumulated costs and quality-adjusted life years (QALYs) were calculated using ADDITION-UK data from 1 to 5 years (short-term analysis, n = 1024); trial data were extrapolated to 30 years using the UKPDS outcomes model (version 1.3) (long-term analysis; n = 999). All costs were transformed to the UK 2009/10 price level. Results Adjusted incremental costs to the NHS were £285, £935, £1190 and £1745 over a 1-, 5-, 10- and 30-year time horizon, respectively (discounted at 3.5%). Adjusted incremental QALYs were 0.0000, – 0.0040, 0.0140 and 0.0465 over the same time horizons. Point estimate incremental cost-effectiveness ratios (ICERs) suggested that the intervention was not cost-effective although the ratio improved over time: the ICER over 10 years was £82 250, falling to £37 500 over 30 years. The ICER fell below £30 000 only when the intervention cost was below £631 per patient: we estimated the cost at £981. Conclusion Given conventional thresholds of cost-effectiveness, the intensive treatment delivered in ADDITION was not cost-effective compared with routine care for individuals with screen-detected diabetes in the UK. The intervention may be cost-effective if it can be delivered at reduced cost. PMID:25661661
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Shuval, Kerem; Balasubramanian, Bijal A.; Kendzor, Darla E.; Radford, Nina B.; DeFina, Laura F.; Gabriel, Kelley Pettee
2016-01-01
Introduction Objective estimates, based on waist-worn accelerometers, indicate that adults spend over half their day (55%) in sedentary behaviors. Our study examined the association between sitting time and cardiometabolic risk factors after adjustment for cardiorespiratory fitness (CRF). Methods A cross-sectional analysis was conducted with 4,486 men and 1,845 women who reported daily estimated sitting time, had measures for adiposity, blood lipids, glucose, and blood pressure, and underwent maximal stress testing. We used a modeling strategy using logistic regression analysis to assess CRF as a potential effect modifier and to control for potential confounding effects of CRF. Results Men who sat almost all of the time (about 100%) were more likely to be obese whether defined by waist girth (OR, 2.61; 95% CI, 1.25–5.47) or percentage of body fat (OR, 3.33; 95% CI, 1.35–8.20) than were men who sat almost none of the time (about 0%). Sitting time was not significantly associated with other cardiometabolic risk factors after adjustment for CRF level. For women, no significant associations between sitting time and cardiometabolic risk factors were observed after adjustment for CRF and other covariates. Conclusion As health professionals struggle to find ways to combat obesity and its health effects, reducing sitting time can be an initial step in a total physical activity plan that includes strategies to reduce sedentary time through increases in physical activity among men. In addition, further research is needed to elucidate the relationships between sitting time and CRF for women as well as the underlying mechanisms involved in these relationships. PMID:28033088
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Marseille, Elliot; Jiwani, Aliya; Raut, Abhishek; Verguet, Stéphane; Walson, Judd; Kahn, James G
2014-06-26
This study estimated the health impact, cost and cost-effectiveness of an integrated prevention campaign (IPC) focused on diarrhoea, malaria and HIV in 70 countries ranked by per capita disability-adjusted life-year (DALY) burden for the three diseases. We constructed a deterministic cost-effectiveness model portraying an IPC combining counselling and testing, cotrimoxazole prophylaxis, referral to treatment and condom distribution for HIV prevention; bed nets for malaria prevention; and provision of household water filters for diarrhoea prevention. We developed a mix of empirical and modelled cost and health impact estimates applied to all 70 countries. One-way, multiway and scenario sensitivity analyses were conducted to document the strength of our findings. We used a healthcare payer's perspective, discounted costs and DALYs at 3% per year and denominated cost in 2012 US dollars. The primary outcome was cost-effectiveness expressed as net cost per DALY averted. Other outcomes included cost of the IPC; net IPC costs adjusted for averted and additional medical costs and DALYs averted. Implementation of the IPC in the 10 most cost-effective countries at 15% population coverage would cost US$583 million over 3 years (adjusted costs of US$398 million), averting 8.0 million DALYs. Extending IPC programmes to all 70 of the identified high-burden countries at 15% coverage would cost an adjusted US$51.3 billion and avert 78.7 million DALYs. Incremental cost-effectiveness ranged from US$49 per DALY averted for the 10 countries with the most favourable cost-effectiveness to US$119, US$181, US$335, US$1692 and US$8340 per DALY averted as each successive group of 10 countries is added ordered by decreasing cost-effectiveness. IPC appears cost-effective in many settings, and has the potential to substantially reduce the burden of disease in resource-poor countries. This study increases confidence that IPC can be an important new approach for enhancing global health. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Mitigation of Sri Lanka Island Effects in Colombo Sounding Data during DYNAMO
NASA Astrophysics Data System (ADS)
Ciesielski, P. E.; Johnson, R. H.; Yoneyama, K.
2013-12-01
During the Dynamics of the MJO (DYNAMO) field campaign, upper-air soundings were launched at Colombo, Sri Lanka as part of the enhanced northern sounding array (NSA) of the experiment. The Colombo soundings were affected at low-levels by diurnal heating of this large island and by flow blocking due to elevated terrain to the east of the Colombo site. Because of the large spacing between sounding sites, these small-scale effects are aliased onto the larger scale impacting analyses and atmospheric budgets over the DYNAMO NSA. To mitigate these local island effects on the large-scale budgets, a procedure was designed which uses ECMWF-analyzed fields in the vicinity of Sri Lanka to estimate open-ocean conditions (i.e, as if this island were not present). These 'unperturbed' ECMWF fields at low-levels are then merged with observed Colombo soundings. This procedure effectively mutes the blocking effects and large diurnal cycle observed in the low-level Colombo fields. In westerly flow regimes, adjusted Colombo winds increase the low-level westerlies by 2-3 m/s with a similar increase of the low-level easterlies in easterly flow regimes. In general, over the NSA the impact of the adjusted Colombo winds results in more low-level divergence (convergence), more mid-level subsidence (rising motion) and reduced (increased) rainfall during the westerly (easterly) wind regimes. In comparison to independent TRMM rainfall estimates, both the mean budget-derived rainfall and its temporal correlation are improved by using the adjusted Colombo soundings. In addition, use of the 'unperturbed' fields result in a more realistic moisture budget analyses, both in its diurnal cycle and during the build-up phase of the November MJO when a gradual deepening of apparent drying was observed. Overall, use of the adjusted Colombo soundings appears to have a beneficial impact on the NSA analyses and budgets.
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Breslow, Norman E.; Lumley, Thomas; Ballantyne, Christie M; Chambless, Lloyd E.; Kulich, Michal
2009-01-01
The case-cohort study involves two-phase sampling: simple random sampling from an infinite super-population at phase one and stratified random sampling from a finite cohort at phase two. Standard analyses of case-cohort data involve solution of inverse probability weighted (IPW) estimating equations, with weights determined by the known phase two sampling fractions. The variance of parameter estimates in (semi)parametric models, including the Cox model, is the sum of two terms: (i) the model based variance of the usual estimates that would be calculated if full data were available for the entire cohort; and (ii) the design based variance from IPW estimation of the unknown cohort total of the efficient influence function (IF) contributions. This second variance component may be reduced by adjusting the sampling weights, either by calibration to known cohort totals of auxiliary variables correlated with the IF contributions or by their estimation using these same auxiliary variables. Both adjustment methods are implemented in the R survey package. We derive the limit laws of coefficients estimated using adjusted weights. The asymptotic results suggest practical methods for construction of auxiliary variables that are evaluated by simulation of case-cohort samples from the National Wilms Tumor Study and by log-linear modeling of case-cohort data from the Atherosclerosis Risk in Communities Study. Although not semiparametric efficient, estimators based on adjusted weights may come close to achieving full efficiency within the class of augmented IPW estimators. PMID:20174455
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Log Pearson type 3 quantile estimators with regional skew information and low outlier adjustments
Griffis, V.W.; Stedinger, Jery R.; Cohn, T.A.
2004-01-01
The recently developed expected moments algorithm (EMA) [Cohn et al., 1997] does as well as maximum likelihood estimations at estimating log‐Pearson type 3 (LP3) flood quantiles using systematic and historical flood information. Needed extensions include use of a regional skewness estimator and its precision to be consistent with Bulletin 17B. Another issue addressed by Bulletin 17B is the treatment of low outliers. A Monte Carlo study compares the performance of Bulletin 17B using the entire sample with and without regional skew with estimators that use regional skew and censor low outliers, including an extended EMA estimator, the conditional probability adjustment (CPA) from Bulletin 17B, and an estimator that uses probability plot regression (PPR) to compute substitute values for low outliers. Estimators that neglect regional skew information do much worse than estimators that use an informative regional skewness estimator. For LP3 data the low outlier rejection procedure generally results in no loss of overall accuracy, and the differences between the MSEs of the estimators that used an informative regional skew are generally modest in the skewness range of real interest. Samples contaminated to model actual flood data demonstrate that estimators which give special treatment to low outliers significantly outperform estimators that make no such adjustment.
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Log Pearson type 3 quantile estimators with regional skew information and low outlier adjustments
NASA Astrophysics Data System (ADS)
Griffis, V. W.; Stedinger, J. R.; Cohn, T. A.
2004-07-01
The recently developed expected moments algorithm (EMA) [, 1997] does as well as maximum likelihood estimations at estimating log-Pearson type 3 (LP3) flood quantiles using systematic and historical flood information. Needed extensions include use of a regional skewness estimator and its precision to be consistent with Bulletin 17B. Another issue addressed by Bulletin 17B is the treatment of low outliers. A Monte Carlo study compares the performance of Bulletin 17B using the entire sample with and without regional skew with estimators that use regional skew and censor low outliers, including an extended EMA estimator, the conditional probability adjustment (CPA) from Bulletin 17B, and an estimator that uses probability plot regression (PPR) to compute substitute values for low outliers. Estimators that neglect regional skew information do much worse than estimators that use an informative regional skewness estimator. For LP3 data the low outlier rejection procedure generally results in no loss of overall accuracy, and the differences between the MSEs of the estimators that used an informative regional skew are generally modest in the skewness range of real interest. Samples contaminated to model actual flood data demonstrate that estimators which give special treatment to low outliers significantly outperform estimators that make no such adjustment.
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Meier, Petra Sylvia; Meng, Yang; Holmes, John; Baumberg, Ben; Purshouse, Robin; Hill-McManus, Daniel; Brennan, Alan
2013-01-01
Large discrepancies are typically found between per capita alcohol consumption estimated via survey data compared with sales, excise or production figures. This may lead to significant inaccuracies when calculating levels of alcohol-attributable harms. Using British data, we demonstrate an approach to adjusting survey data to give more accurate estimates of per capita alcohol consumption. First, sales and survey data are adjusted to account for potential biases (e.g. self-pouring, under-sampled populations) using evidence from external data sources. Secondly, survey and sales data are aligned using different implementations of Rehm et al.'s method [in (2010) Statistical modeling of volume of alcohol exposure for epidemiological studies of population health: the US example. Pop Health Metrics 8, 1-12]. Thirdly, the impact of our approaches is tested by using our revised survey dataset to calculate alcohol-attributable fractions (AAFs) for oral and pharyngeal cancers. British sales data under-estimate per capita consumption by 8%, primarily due to illicit alcohol. Adjustments to survey data increase per capita consumption estimates by 35%, primarily due to under-sampling of dependent drinkers and under-estimation of home-poured spirits volumes. Before aligning sales and survey data, the revised survey estimate remains 22% lower than the revised sales estimate. Revised AAFs for oral and pharyngeal cancers are substantially larger with our preferred method for aligning data sources, yielding increases in an AAF from the original survey dataset of 0.47-0.60 (males) and 0.28-0.35 (females). It is possible to use external data sources to adjust survey data to reduce the under-estimation of alcohol consumption and then account for residual under-estimation using a statistical calibration technique. These revisions lead to markedly higher estimated levels of alcohol-attributable harm.
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Berenbrock, Charles
2003-01-01
Improved flood-frequency estimates for short-term (10 or fewer years of record) streamflow-gaging stations were needed to support instream flow studies by the U.S. Forest Service, which are focused on quantifying water rights necessary to maintain or restore productive fish habitat. Because peak-flow data for short-term gaging stations can be biased by having been collected during an unusually wet, dry, or otherwise unrepresentative period of record, the data may not represent the full range of potential floods at a site. To test whether peak-flow estimates for short-term gaging stations could be improved, the two-station comparison method was used to adjust the logarithmic mean and logarithmic standard deviation of peak flows for seven short-term gaging stations in the Salmon and Clearwater River Basins, central Idaho. Correlation coefficients determined from regression of peak flows for paired short-term and long-term (more than 10 years of record) gaging stations over a concurrent period of record indicated that the mean and standard deviation of peak flows for all short-term gaging stations would be improved. Flood-frequency estimates for seven short-term gaging stations were determined using the adjusted mean and standard deviation. The original (unadjusted) flood-frequency estimates for three of the seven short-term gaging stations differed from the adjusted estimates by less than 10 percent, probably because the data were collected during periods representing the full range of peak flows. Unadjusted flood-frequency estimates for four short-term gaging stations differed from the adjusted estimates by more than 10 percent; unadjusted estimates for Little Slate Creek and Salmon River near Obsidian differed from adjusted estimates by nearly 30 percent. These large differences probably are attributable to unrepresentative periods of peak-flow data collection.
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Case mix adjusted nursing-home reimbursement: a critical review of the evidence.
Weissert, W G; Musliner, M C
1992-01-01
Nursing-home case mix adjusted payment systems typically base payments on estimates of patients' care needs, but to date the data on their effectiveness are ambiguous. Studies mainly show that access for patients most in need of care appears to improve under these systems. Case mix based payment systems have both positive and negative effects on quality of care and require compensating mechanisms for the potentially harmful incentives they can generate. On the positive side, nursing homes are paid more equitably; the negative aspect is reflected in higher costs, particularly for administration. A Health Care Financing Administration (HCFA) demonstration project may provide insights, but its limited number of predominantly small, rural, participating states, its tandem quality assurance system, and potentially confounding market variables may restrict the value of this project. We do not yet have the data to assess the impact of instituting case mix adjustment systems.
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ERIC Educational Resources Information Center
Hurwitz, Michael; Mbekeani, Preeya P.; Nipson, Margaret M.; Page, Lindsay C.
2017-01-01
Subtle policy adjustments can induce relatively large "ripple effects." We evaluate a College Board initiative that increased the number of free SAT score reports available to low-income students and changed the time horizon for using these score reports. Using a difference-in-differences analytic strategy, we estimate that targeted…
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Environmental Chemicals in Urine and Blood: Improving Methods for Creatinine and Lipid Adjustment.
O'Brien, Katie M; Upson, Kristen; Cook, Nancy R; Weinberg, Clarice R
2016-02-01
Investigators measuring exposure biomarkers in urine typically adjust for creatinine to account for dilution-dependent sample variation in urine concentrations. Similarly, it is standard to adjust for serum lipids when measuring lipophilic chemicals in serum. However, there is controversy regarding the best approach, and existing methods may not effectively correct for measurement error. We compared adjustment methods, including novel approaches, using simulated case-control data. Using a directed acyclic graph framework, we defined six causal scenarios for epidemiologic studies of environmental chemicals measured in urine or serum. The scenarios include variables known to influence creatinine (e.g., age and hydration) or serum lipid levels (e.g., body mass index and recent fat intake). Over a range of true effect sizes, we analyzed each scenario using seven adjustment approaches and estimated the corresponding bias and confidence interval coverage across 1,000 simulated studies. For urinary biomarker measurements, our novel method, which incorporates both covariate-adjusted standardization and the inclusion of creatinine as a covariate in the regression model, had low bias and possessed 95% confidence interval coverage of nearly 95% for most simulated scenarios. For serum biomarker measurements, a similar approach involving standardization plus serum lipid level adjustment generally performed well. To control measurement error bias caused by variations in serum lipids or by urinary diluteness, we recommend improved methods for standardizing exposure concentrations across individuals.
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Prakash, Priyanka; Gilman, Matthew D.; Shepard, Jo-Anne O.; Digumarthy, Subba R.
2010-01-01
Objective To assess the effects of radiation dose reduction in the chest CT using a weight-based adjustment of the automatic exposure control (AEC) technique. Materials and Methods With Institutional Review Board Approval, 60 patients (mean age, 59.1 years; M:F = 35:25) and 57 weight-matched patients (mean age, 52.3 years, M:F = 25:32) were scanned using a weight-adjusted AEC and non-weight-adjusted AEC, respectively on a 64-slice multidetector CT with a 0.984:1 pitch, 0.5 second rotation time, 40 mm table feed/rotation, and 2.5 mm section thickness. Patients were categorized into 3 weight categories; < 60 kg (n = 17), 60-90 kg (n = 52), and > 90 kg (n = 48). Patient weights, scanning parameters, CT dose index volumes (CTDIvol) and dose length product (DLP) were recorded, while effective dose (ED) was estimated. Image noise was measured in the descending thoracic aorta. Data were analyzed using a standard statistical package (SAS/STAT) (Version 9.1, SAS institute Inc, Cary, NC). Results Compared to the non-weight-adjusted AEC, the weight-adjusted AEC technique resulted in an average decrease of 29% in CTDIvol and a 27% effective dose reduction (p < 0.0001). With weight-adjusted AEC, the CTDIvol decreased to 15.8, 15.9, and 27.3 mGy for the < 60, 60-90 and > 91 kg weight groups, respectively, compared to 20.3, 27.9 and 32.8 mGy, with non-weight-adjusted AEC. No significant difference was observed for objective image noise between the chest CT acquired with the non-weight-adjusted (15.0 ± 3.1) and weight-adjusted (16.1 ± 5.6) AEC techniques (p > 0.05). Conclusion The results of this study suggest that AEC should be tailored according to patient weight. Without weight-based adjustment of AEC, patients are exposed to a 17 - 43% higher radiation-dose from a chest CT. PMID:20046494
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Prakash, Priyanka; Kalra, Mannudeep K; Gilman, Matthew D; Shepard, Jo-Anne O; Digumarthy, Subba R
2010-01-01
To assess the effects of radiation dose reduction in the chest CT using a weight-based adjustment of the automatic exposure control (AEC) technique. With Institutional Review Board Approval, 60 patients (mean age, 59.1 years; M:F = 35:25) and 57 weight-matched patients (mean age, 52.3 years, M:F = 25:32) were scanned using a weight-adjusted AEC and non-weight-adjusted AEC, respectively on a 64-slice multidetector CT with a 0.984:1 pitch, 0.5 second rotation time, 40 mm table feed/rotation, and 2.5 mm section thickness. Patients were categorized into 3 weight categories; < 60 kg (n = 17), 60-90 kg (n = 52), and > 90 kg (n = 48). Patient weights, scanning parameters, CT dose index volumes (CTDIvol) and dose length product (DLP) were recorded, while effective dose (ED) was estimated. Image noise was measured in the descending thoracic aorta. Data were analyzed using a standard statistical package (SAS/STAT) (Version 9.1, SAS institute Inc, Cary, NC). Compared to the non-weight-adjusted AEC, the weight-adjusted AEC technique resulted in an average decrease of 29% in CTDIvol and a 27% effective dose reduction (p < 0.0001). With weight-adjusted AEC, the CTDIvol decreased to 15.8, 15.9, and 27.3 mGy for the < 60, 60-90 and > 91 kg weight groups, respectively, compared to 20.3, 27.9 and 32.8 mGy, with non-weight-adjusted AEC. No significant difference was observed for objective image noise between the chest CT acquired with the non-weight-adjusted (15.0 +/- 3.1) and weight-adjusted (16.1 +/- 5.6) AEC techniques (p > 0.05). The results of this study suggest that AEC should be tailored according to patient weight. Without weight-based adjustment of AEC, patients are exposed to a 17 - 43% higher radiation-dose from a chest CT.
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Covariate Imbalance and Precision in Measuring Treatment Effects
ERIC Educational Resources Information Center
Liu, Xiaofeng Steven
2011-01-01
Covariate adjustment can increase the precision of estimates by removing unexplained variance from the error in randomized experiments, although chance covariate imbalance tends to counteract the improvement in precision. The author develops an easy measure to examine chance covariate imbalance in randomization by standardizing the average…
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10 CFR 455.63 - Cost-effectiveness testing.
Code of Federal Regulations, 2011 CFR
2011-01-01
...) The simple payback period of each energy conservation measure (except measures to shift demand, or...), by the estimated annual cost savings accruing from the measure (adjusted for demand charges), as... non-renewable fuels displaced less the annual cost of the renewable fuel, if any, and the annual cost...
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10 CFR 455.63 - Cost-effectiveness testing.
Code of Federal Regulations, 2010 CFR
2010-01-01
...) The simple payback period of each energy conservation measure (except measures to shift demand, or...), by the estimated annual cost savings accruing from the measure (adjusted for demand charges), as... non-renewable fuels displaced less the annual cost of the renewable fuel, if any, and the annual cost...
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DoD Influenza Surveillance and Vaccine Effectiveness
2014-02-28
controls – No analyses by flu subtype (over 90% of flu samples were H1N1) 21 • Adjusted Estimates of Vaccine Effectiveness – Population: Service...DoD Influenza Surveillance and Vaccine Effectiveness Armed Forces Health Surveillance Center (AFHSC) Naval Health Research Center (NHRC) United... Vaccine Effectiveness 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK
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Optimal Linking Design for Response Model Parameters
ERIC Educational Resources Information Center
Barrett, Michelle D.; van der Linden, Wim J.
2017-01-01
Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…
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Regional regression of flood characteristics employing historical information
Tasker, Gary D.; Stedinger, J.R.
1987-01-01
Streamflow gauging networks provide hydrologic information for use in estimating the parameters of regional regression models. The regional regression models can be used to estimate flood statistics, such as the 100 yr peak, at ungauged sites as functions of drainage basin characteristics. A recent innovation in regional regression is the use of a generalized least squares (GLS) estimator that accounts for unequal station record lengths and sample cross correlation among the flows. However, this technique does not account for historical flood information. A method is proposed here to adjust this generalized least squares estimator to account for possible information about historical floods available at some stations in a region. The historical information is assumed to be in the form of observations of all peaks above a threshold during a long period outside the systematic record period. A Monte Carlo simulation experiment was performed to compare the GLS estimator adjusted for historical floods with the unadjusted GLS estimator and the ordinary least squares estimator. Results indicate that using the GLS estimator adjusted for historical information significantly improves the regression model. ?? 1987.
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Pereira, Gavin; Jacoby, Peter; de Klerk, Nicholas; Stanley, Fiona J
2014-01-01
Objective To re-evaluate the causal effect of interpregnancy interval on adverse birth outcomes, on the basis that previous studies relying on between mother comparisons may have inadequately adjusted for confounding by maternal risk factors. Design Retrospective cohort study using conditional logistic regression (matching two intervals per mother so each mother acts as her own control) to model the incidence of adverse birth outcomes as a function of interpregnancy interval; additional unconditional logistic regression with adjustment for confounders enabled comparison with the unmatched design of previous studies. Setting Perth, Western Australia, 1980-2010. Participants 40 441 mothers who each delivered three liveborn singleton neonates. Main outcome measures Preterm birth (<37 weeks), small for gestational age birth (<10th centile of birth weight by sex and gestational age), and low birth weight (<2500 g). Results Within mother analysis of interpregnancy intervals indicated a much weaker effect of short intervals on the odds of preterm birth and low birth weight compared with estimates generated using a traditional between mother analysis. The traditional unmatched design estimated an adjusted odds ratio for an interpregnancy interval of 0-5 months (relative to the reference category of 18-23 months) of 1.41 (95% confidence interval 1.31 to 1.51) for preterm birth, 1.26 (1.15 to 1.37) for low birth weight, and 0.98 (0.92 to 1.06) for small for gestational age birth. In comparison, the matched design showed a much weaker effect of short interpregnancy interval on preterm birth (odds ratio 1.07, 0.86 to 1.34) and low birth weight (1.03, 0.79 to 1.34), and the effect for small for gestational age birth remained small (1.08, 0.87 to 1.34). Both the unmatched and matched models estimated a high odds of small for gestational age birth and low birth weight for long interpregnancy intervals (longer than 59 months), but the estimated effect of long interpregnancy intervals on the odds of preterm birth was much weaker in the matched model than in the unmatched model. Conclusion This study questions the causal effect of short interpregnancy intervals on adverse birth outcomes and points to the possibility of unmeasured or inadequately specified maternal factors in previous studies. PMID:25056260
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Tolbert, Davina V; McCollister, Kathryn E; LeBlanc, William G; Lee, David J; Fleming, Lora E; Muennig, Peter
2014-07-01
This study compares differences in quality-adjusted life expectancy across the eight original National Occupational Research Agenda (NORA) industry sectors. Data from the 1997 to 2012 National Health Interview Survey (NHIS) were used to estimate quality-adjusted life years (QALYs) for all workers and by NORA sector. Differences in QALYs were calculated and translated into economic values using estimates of the societal willingness-to-pay per QALY. Mean QALYs across workers was 29.17 years. Among NORA sectors, wholesale, and retail trade workers had the highest average QALYs remaining (35.88), while mining workers had the lowest QALYs (31.4). The economic value of this difference ranges from $604,843 to $1,155,287 per worker depending on the societal willingness-to-pay per QALY. The value of life lost within some industries is very high relative to others. Additional investments in occupational safety, benefits, and health promotion initiatives may reduce these losses, but experimental research is needed to assess the effectiveness of such programs. © 2014 Wiley Periodicals, Inc.
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GRAVSAT/GEOPAUSE covariance analysis including geopotential aliasing
NASA Technical Reports Server (NTRS)
Koch, D. W.
1975-01-01
A conventional covariance analysis for the GRAVSAT/GEOPAUSE mission is described in which the uncertainties of approximately 200 parameters, including the geopotential coefficients to degree and order 12, are estimated over three different tracking intervals. The estimated orbital uncertainties for both GRAVSAT and GEOPAUSE reach levels more accurate than presently available. The adjusted measurement bias errors approach the mission goal. Survey errors in the low centimeter range are achieved after ten days of tracking. The ability of the mission to obtain accuracies of geopotential terms to (12, 12) one to two orders of magnitude superior to present accuracy levels is clearly shown. A unique feature of this report is that the aliasing structure of this (12, 12) field is examined. It is shown that uncertainties for unadjusted terms to (12, 12) still exert a degrading effect upon the adjusted error of an arbitrarily selected term of lower degree and order. Finally, the distribution of the aliasing from the unestimated uncertainty of a particular high degree and order geopotential term upon the errors of all remaining adjusted terms is listed in detail.
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RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information
Di, Kaichang; Zhao, Qiang; Wan, Wenhui; Wang, Yexin; Gao, Yunjun
2016-01-01
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM is proposed based on extended bundle adjustment with integrated 2D and 3D information on the basis of a new projection model. First, the geometric relationship between the image plane coordinates and the depth values is constructed through RGB-D camera calibration. Then, 2D and 3D feature points are automatically extracted and matched between consecutive frames to build a continuous image network. Finally, extended bundle adjustment based on the new projection model, which takes both image and depth measurements into consideration, is applied to the image network for high-precision pose estimation. Field experiments show that the proposed method has a notably better performance than the traditional method, and the experimental results demonstrate the effectiveness of the proposed method in improving localization accuracy. PMID:27529256
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Statistical issues in reporting quality data: small samples and casemix variation.
Zaslavsky, A M
2001-12-01
To present two key statistical issues that arise in analysis and reporting of quality data. Casemix variation is relevant to quality reporting when the units being measured have differing distributions of patient characteristics that also affect the quality outcome. When this is the case, adjustment using stratification or regression may be appropriate. Such adjustments may be controversial when the patient characteristic does not have an obvious relationship to the outcome. Stratified reporting poses problems for sample size and reporting format, but may be useful when casemix effects vary across units. Although there are no absolute standards of reliability, high reliabilities (interunit F > or = 10 or reliability > or = 0.9) are desirable for distinguishing above- and below-average units. When small or unequal sample sizes complicate reporting, precision may be improved using indirect estimation techniques that incorporate auxiliary information, and 'shrinkage' estimation can help to summarize the strength of evidence about units with small samples. With broader understanding of casemix adjustment and methods for analyzing small samples, quality data can be analysed and reported more accurately.
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The influence of seine capture efficiency on fish abundance estimates in the upper Mississippi River
Holland Bartels, L. E.; Dewey, M.R.
1997-01-01
The effects of season, presence of vegetation, and time of day on seine capture efficiency for fish were evaluated using test enclosures in the upper Mississippi River. Overall capture efficiency of the seine haul was 49% (53% during the day and 43% at night). During daytime tests, the efficiency ranged from 39% to 74% but did not differ statistically between sites or among dates. At night, the efficiency was higher at the vegetated than at the nonvegetated site (55% vs 32%) and declined through time from 56% in May to 28% in October. Although susceptibility to capture differed among taxa, we could not predict either total catch efficiency or efficiency within a given taxon for a given sample. Adjustment of catch data with various estimates of efficiency reduced the mean absolute error for all sampling dates from 51% to 24%, but the error of the adjusted data still ranged from -58% to +54% on any given sampling date. These results indicate that it is difficult to make accurate adjustment of catch data to compensate for gear bias in studies of seasonal habitat use.
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Nunes, Baltazar; Machado, Ausenda; Guiomar, Raquel; Pechirra, Pedro; Conde, Patrícia; Cristovão, Paula; Falcão, Isabel
2014-07-31
In recent years several reports of influenza vaccine effectiveness (VE) have been made early for public health decision. The majority of these studies use the case test-negative control design (TND), which has been showed to provide, under certain conditions, unbiased estimates of influenza VE. Nevertheless, discussions have been taken on the best influenza negative control group to use. The present study aims to contribute to the knowledge on this field by comparing influenza VE estimates using three test-negative controls: all influenza negative, non-influenza respiratory virus and pan-negative. Incident ILI patients were prospectively selected and swabbed by a sample of general practitioners. Cases were ILI patients tested positive for influenza and controls ILI patients tested negative for influenza. The influenza negative control group was divided into non-influenza virus control group and pan-negative control group. Data were collected on vaccination status and confounding factors. Influenza VE was estimated as one minus the odds ratio of been vaccinated in cases versus controls adjusted for confounding effect by logistic regression. Confounder adjusted influenza VE against medically attended laboratory-confirmed influenza was 68.4% (95% CI: 20.7-87.4%) using all influenza negatives controls, 82.1% (95% CI: 47.6-93.9%) using non-influenza controls and 49.4% (95% CI: -44.7% to 82.3%) using pan-negative controls. Influenza VE estimates differed according to the influenza negative control group used. These results are in accordance with the expected under the hypothesis of differential viral interference between influenza vaccinated and unvaccinated individuals. Given the wide importance of TND study further studies should be conducted in order to clarify the observed differences. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Axelrad, Daniel A; Cohen, Jonathan
2011-01-01
The effects of chemical exposures during pregnancy on children's health have been an increasing focus of environmental health research in recent years, leading to greater interest in biomonitoring of chemicals in women of childbearing age in the general population. Measurements of mercury in blood from the National Health and Nutrition Examination Survey are frequently reported for "women of childbearing age," defined to be of ages 16-49 years. The intent is to represent prenatal chemical exposure, but blood mercury levels increase with age. Furthermore, women of different ages have different probabilities of giving birth. We evaluated options to address potential bias in biomonitoring summary statistics for women of childbearing age by accounting for age-specific probabilities of giving birth. We calculated median and 95th percentile levels of mercury, PCBs, and cotinine using these approaches: option 1: women aged 16-49 years without natality adjustment; option 2: women aged 16-39 years without natality adjustment; option 3: women aged 16-49 years, adjusted for natality by age; option 4: women aged 16-49 years, adjusted for natality by age and race/ethnicity. Among the three chemicals examined, the choice of option has the greatest impact on estimated levels of serum PCBs, which are strongly associated with age. Serum cotinine levels among Black non-Hispanic women of childbearing age are understated when age-specific natality is not considered. For characterizing in utero exposures, adjustment using age-specific natality provides a substantial improvement in estimation of biomonitoring summary statistics. Copyright © 2010 Elsevier Inc. All rights reserved.
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Developing Analogy Cost Estimates for Space Missions
NASA Technical Reports Server (NTRS)
Shishko, Robert
2004-01-01
The analogy approach in cost estimation combines actual cost data from similar existing systems, activities, or items with adjustments for a new project's technical, physical or programmatic differences to derive a cost estimate for the new system. This method is normally used early in a project cycle when there is insufficient design/cost data to use as a basis for (or insufficient time to perform) a detailed engineering cost estimate. The major limitation of this method is that it relies on the judgment and experience of the analyst/estimator. The analyst must ensure that the best analogy or analogies have been selected, and that appropriate adjustments have been made. While analogy costing is common, there is a dearth of advice in the literature on the 'adjustment methodology', especially for hardware projects. This paper discusses some potential approaches that can improve rigor and repeatability in the analogy costing process.
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42 CFR 403.750 - Estimate of expenditures and adjustments.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 42 Public Health 2 2011-10-01 2011-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
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42 CFR 403.750 - Estimate of expenditures and adjustments.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 42 Public Health 2 2014-10-01 2014-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
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42 CFR 403.750 - Estimate of expenditures and adjustments.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 42 Public Health 2 2010-10-01 2010-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
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42 CFR 403.750 - Estimate of expenditures and adjustments.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 42 Public Health 2 2012-10-01 2012-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
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42 CFR 403.750 - Estimate of expenditures and adjustments.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 42 Public Health 2 2013-10-01 2013-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
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Graduated driver licensing decal law: effect on young probationary drivers.
Curry, Allison E; Pfeiffer, Melissa R; Localio, Russell; Durbin, Dennis R
2013-01-01
Decal laws have been implemented internationally to facilitate police enforcement of graduated driver licensing (GDL) restrictions (e.g., passenger limit, nighttime curfew) but have not been evaluated. New Jersey implemented the first decal law in the U.S. on May 1, 2010. The aim of this study was to evaluate the effect of New Jersey's law on the rate of citations issued for violation of GDL restrictions and police-reported crashes among probationary drivers aged <21 years and to estimate the number of probationary drivers whose crashes were prevented by the law. New Jersey's licensing and crash databases were linked from January 1, 2008 to May 31, 2011, and each driver's license status, age, and outcome status were ascertained for each month. Monthly rates were calculated as the proportion of probationary drivers who experienced the outcome in that month. The pre-law period was defined as January 2008-January 2010 and the post-law period as May 2010-May 2011. Negative binomial regression models with robust SEs were used to determine the law's effect on crash and citation rates (adjusted for gender, seasonal trends, and overall trends) and estimate prevented crashes. Analyses were conducted in 2012. In the first year post-law, there was a 14% increase in the GDL citation rate (adjusted rate ratio 1.14 [95% CI=1.05, 1.24]); a 9% reduction in the police-reported crash rate (adjusted rate ratio 0.91 [95% CI=0.86, 0.97]), and an estimated 1624 young probationary drivers for whom a crash was prevented. Findings suggest that the law is positively affecting probationary drivers' safety. Results contribute to building the evidence base for the effectiveness of decal laws and provide valuable information to U.S. and international policymakers who are considering adding decal laws to enhance existing GDL laws. Copyright © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
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Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David
2018-04-01
Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.
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Li, Haojie; Graham, Daniel J
2016-08-01
This paper estimates the causal effect of 20mph zones on road casualties in London. Potential confounders in the key relationship of interest are included within outcome regression and propensity score models, and the models are then combined to form a doubly robust estimator. A total of 234 treated zones and 2844 potential control zones are included in the data sample. The propensity score model is used to select a viable control group which has common support in the covariate distributions. We compare the doubly robust estimates with those obtained using three other methods: inverse probability weighting, regression adjustment, and propensity score matching. The results indicate that 20mph zones have had a significant causal impact on road casualty reduction in both absolute and proportional terms. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Gillespie, Paddy; O'Shea, Eamon; O'Hara, Mary Clare; Dinneen, Sean F
2014-06-14
This study examines the cost effectiveness of group follow-up after participation in the Dose Adjustment for Normal Eating (DAFNE) structured education programme for type 1 diabetes. Economic evaluation conducted alongside a cluster randomised controlled trial involving 437 adults with type 1 diabetes in Ireland. Group follow-up involved two group education 'booster' sessions post-DAFNE. Individual follow-up involved two standard one-to-one hospital clinic visits. Incremental costs, quality-adjusted life years (QALYs) gained and cost effectiveness were estimated at 18 months. Uncertainty was explored using sensitivity analysis and by estimating cost effectiveness acceptability curves. Group follow-up was associated with a mean reduction in QALYs gained of 0.04 per patient (P value, 0.052; 95% CI, -0.08 to 0.01, intra-class correlation (ICC), 0.033) and a mean reduction in total healthcare costs of €772 (P value, 0.020; 95% CI, -1,415 to -128: ICC, 0.016) per patient. At alternative threshold values of €5,000, €15,000, €25,000, €35,000, and €45,000, the probability of group follow-up being cost effective was estimated to be 1.000, 0.762, 0.204, 0.078, and 0.033 respectively. The results do not support implementation of group follow-up as the sole means of follow-up post-DAFNE. Given the reported cost savings, future studies should explore the cost effectiveness of alternative models of group care for diabetes. Current Controlled Trials ISRCTN79759174 (assigned: 9 February 2007).
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ERIC Educational Resources Information Center
Beauducel, Andre; Herzberg, Philipp Yorck
2006-01-01
This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no…
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Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence.
Evers, Eric G; Bouwknegt, Martijn
2016-10-01
The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose-infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion. © 2016 Society for Risk Analysis.
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The effectiveness of avalanche airbags.
Haegeli, Pascal; Falk, Markus; Procter, Emily; Zweifel, Benjamin; Jarry, Frédéric; Logan, Spencer; Kronholm, Kalle; Biskupič, Marek; Brugger, Hermann
2014-09-01
Asphyxia is the primary cause of death among avalanche victims. Avalanche airbags can lower mortality by directly reducing grade of burial, the single most important factor for survival. This study aims to provide an updated perspective on the effectiveness of this safety device. A retrospective analysis of avalanche accidents involving at least one airbag user between 1994 and 2012 in Austria, Canada, France, Norway, Slovakia, Switzerland and the United States. A multivariate analysis was used to calculate adjusted absolute risk reduction and estimate the effectiveness of airbags on grade of burial and mortality. A univariate analysis was used to examine causes of non-deployment. Binomial linear regression models showed main effects for airbag use, avalanche size and injuries on critical burial, and for grade of burial, injuries and avalanche size on mortality. The adjusted risk of critical burial is 47% with non-inflated airbags and 20% with inflated airbags. The adjusted mortality is 44% for critically buried victims and 3% for non-critically buried victims. The adjusted absolute mortality reduction for inflated airbags is -11 percentage points (22% to 11%; 95% confidence interval: -4 to -18 percentage points) and adjusted risk ratio is 0.51 (95% confidence interval: 0.29 to 0.72). Overall non-inflation rate is 20%, 60% of which is attributed to deployment failure by the user. Although the impact on survival is smaller than previously reported, these results confirm the effectiveness of airbags. Non-deployment remains the most considerable limitation to effectiveness. Development of standardized data collection protocols is encouraged to facilitate further research. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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Estimating Statistical Power When Making Adjustments for Multiple Tests
ERIC Educational Resources Information Center
Porter, Kristin E.
2016-01-01
In recent years, there has been increasing focus on the issue of multiple hypotheses testing in education evaluation studies. In these studies, researchers are typically interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time or across multiple treatment groups. When…
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Reported maternal education is an important predictor of pregnancy outcomes. Like income, it is believed to allow women to locate in more favorable conditions than less educated or affluent peers. We examine the effect of reported educational attainment on term birth weight (birt...
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Genetic and Phenotypic Parameter Estimates for Feed Intake and Other Traits in Growing Beef Cattle
USDA-ARS?s Scientific Manuscript database
Intake and feed efficiency were moderately heritable; however, residual feed intake was more heritable than intake and feed efficiency. Adjusting residual feed intake and feed efficiency for carcass fatness had little effect on heritability and correlations with remaining traits. Flight speed was ...
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Determination of Cost-Effectiveness Threshold for Health Care Interventions in Malaysia.
Lim, Yen Wei; Shafie, Asrul Akmal; Chua, Gin Nie; Ahmad Hassali, Mohammed Azmi
2017-09-01
One major challenge in prioritizing health care using cost-effectiveness (CE) information is when alternatives are more expensive but more effective than existing technology. In such a situation, an external criterion in the form of a CE threshold that reflects the willingness to pay (WTP) per quality-adjusted life-year is necessary. To determine a CE threshold for health care interventions in Malaysia. A cross-sectional, contingent valuation study was conducted using a stratified multistage cluster random sampling technique in four states in Malaysia. One thousand thirteen respondents were interviewed in person for their socioeconomic background, quality of life, and WTP for a hypothetical scenario. The CE thresholds established using the nonparametric Turnbull method ranged from MYR12,810 to MYR22,840 (~US $4,000-US $7,000), whereas those estimated with the parametric interval regression model were between MYR19,929 and MYR28,470 (~US $6,200-US $8,900). Key factors that affected the CE thresholds were education level, estimated monthly household income, and the description of health state scenarios. These findings suggest that there is no single WTP value for a quality-adjusted life-year. The CE threshold estimated for Malaysia was found to be lower than the threshold value recommended by the World Health Organization. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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Weather adjustment using seemingly unrelated regression
DOE Office of Scientific and Technical Information (OSTI.GOV)
Noll, T.A.
1995-05-01
Seemingly unrelated regression (SUR) is a system estimation technique that accounts for time-contemporaneous correlation between individual equations within a system of equations. SUR is suited to weather adjustment estimations when the estimation is: (1) composed of a system of equations and (2) the system of equations represents either different weather stations, different sales sectors or a combination of different weather stations and different sales sectors. SUR utilizes the cross-equation error values to develop more accurate estimates of the system coefficients than are obtained using ordinary least-squares (OLS) estimation. SUR estimates can be generated using a variety of statistical software packagesmore » including MicroTSP and SAS.« less
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Conservative Tests under Satisficing Models of Publication Bias.
McCrary, Justin; Christensen, Garret; Fanelli, Daniele
2016-01-01
Publication bias leads consumers of research to observe a selected sample of statistical estimates calculated by producers of research. We calculate critical values for statistical significance that could help to adjust after the fact for the distortions created by this selection effect, assuming that the only source of publication bias is file drawer bias. These adjusted critical values are easy to calculate and differ from unadjusted critical values by approximately 50%-rather than rejecting a null hypothesis when the t-ratio exceeds 2, the analysis suggests rejecting a null hypothesis when the t-ratio exceeds 3. Samples of published social science research indicate that on average, across research fields, approximately 30% of published t-statistics fall between the standard and adjusted cutoffs.
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Conservative Tests under Satisficing Models of Publication Bias
McCrary, Justin; Christensen, Garret; Fanelli, Daniele
2016-01-01
Publication bias leads consumers of research to observe a selected sample of statistical estimates calculated by producers of research. We calculate critical values for statistical significance that could help to adjust after the fact for the distortions created by this selection effect, assuming that the only source of publication bias is file drawer bias. These adjusted critical values are easy to calculate and differ from unadjusted critical values by approximately 50%—rather than rejecting a null hypothesis when the t-ratio exceeds 2, the analysis suggests rejecting a null hypothesis when the t-ratio exceeds 3. Samples of published social science research indicate that on average, across research fields, approximately 30% of published t-statistics fall between the standard and adjusted cutoffs. PMID:26901834
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Cross-Sectional HIV Incidence Estimation in HIV Prevention Research
Brookmeyer, Ron; Laeyendecker, Oliver; Donnell, Deborah; Eshleman, Susan H.
2013-01-01
Accurate methods for estimating HIV incidence from cross-sectional samples would have great utility in prevention research. This report describes recent improvements in cross-sectional methods that significantly improve their accuracy. These improvements are based on the use of multiple biomarkers to identify recent HIV infections. These multi-assay algorithms (MAAs) use assays in a hierarchical approach for testing that minimizes the effort and cost of incidence estimation. These MAAs do not require mathematical adjustments for accurate estimation of the incidence rates in study populations in the year prior to sample collection. MAAs provide a practical, accurate, and cost-effective approach for cross-sectional HIV incidence estimation that can be used for HIV prevention research and global epidemic monitoring. PMID:23764641
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23 CFR 1340.9 - Computation of estimates.
Code of Federal Regulations, 2014 CFR
2014-04-01
... OBSERVATIONAL SURVEYS OF SEAT BELT USE Survey Design Requirements § 1340.9 Computation of estimates. (a) Data... design and any subsequent adjustments. (e) Sampling weight adjustments for observation sites with no... section, the nonresponse rate for the entire survey shall not exceed 10 percent for the ratio of the total...
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23 CFR 1340.9 - Computation of estimates.
Code of Federal Regulations, 2012 CFR
2012-04-01
... OBSERVATIONAL SURVEYS OF SEAT BELT USE Survey Design Requirements § 1340.9 Computation of estimates. (a) Data... design and any subsequent adjustments. (e) Sampling weight adjustments for observation sites with no... section, the nonresponse rate for the entire survey shall not exceed 10 percent for the ratio of the total...
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23 CFR 1340.9 - Computation of estimates.
Code of Federal Regulations, 2013 CFR
2013-04-01
... OBSERVATIONAL SURVEYS OF SEAT BELT USE Survey Design Requirements § 1340.9 Computation of estimates. (a) Data... design and any subsequent adjustments. (e) Sampling weight adjustments for observation sites with no... section, the nonresponse rate for the entire survey shall not exceed 10 percent for the ratio of the total...
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The Fifth Cell: Correlation Bias in U.S. Census Adjustment.
ERIC Educational Resources Information Center
Wachter, Kenneth W.; Freedman, David A.
2000-01-01
Presents a method for estimating the total national number of doubly missing people (missing from Census counts and adjusted counts as well) and their distribution by race and sex. Application to the 1990 U.S. Census yields an estimate of three million doubly-missing people. (SLD)
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28 CFR 100.19 - Adjustments to agreement estimate.
Code of Federal Regulations, 2012 CFR
2012-07-01
... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
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28 CFR 100.19 - Adjustments to agreement estimate.
Code of Federal Regulations, 2011 CFR
2011-07-01
... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
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28 CFR 100.19 - Adjustments to agreement estimate.
Code of Federal Regulations, 2013 CFR
2013-07-01
... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
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28 CFR 100.19 - Adjustments to agreement estimate.
Code of Federal Regulations, 2014 CFR
2014-07-01
... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
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Cost-effectiveness analysis of total ankle arthroplasty.
SooHoo, Nelson F; Kominski, Gerald
2004-11-01
There is renewed interest in total ankle arthroplasty as an alternative to ankle fusion in the treatment of end-stage ankle arthritis. Despite a lack of long-term data on the clinical outcomes associated with these implants, the use of ankle arthroplasty is expanding. The purpose of this cost-effectiveness analysis was to evaluate whether the currently available literature justifies the emerging use of total ankle arthroplasty. This study also identifies thresholds for the durability and function of ankle prostheses that, if met, would support more widespread dissemination of this new technology. A decision model was created for the treatment of ankle arthritis. The literature was reviewed to identify possible outcomes and their probabilities following ankle fusion and ankle arthroplasty. Each outcome was weighted for quality of life with use of a utility factor, and effectiveness was expressed in units of quality-adjusted life years. Gross costs were estimated from Medicare charge and reimbursement data for the relevant codes. The effect of the uncertainty of estimates of costs and effectiveness was assessed with sensitivity analysis. The reference case of our model assumed a ten-year duration of survival of the prosthesis, resulting in an incremental cost-effectiveness ratio for ankle arthroplasty of $18,419 per quality-adjusted life year gained. This reflects a gain of 0.52 quality-adjusted life years at a cost of $9578 when ankle arthroplasty is chosen over fusion. This ratio compares favorably with the cost-effectiveness of other medical and surgical interventions. Sensitivity analysis determined that the cost per quality-adjusted life year gained with ankle arthroplasty rises above $50,000 if the prosthesis is assumed to fail before seven years. Treatment options with ratios above $50,000 per quality-adjusted life year are commonly considered to have limited cost-effectiveness. This threshold is also crossed when the theoretical functional advantages of ankle arthroplasty are eliminated in sensitivity analysis. The currently available literature has not yet shown that total ankle arthroplasty predictably results in levels of durability and function that make it cost-effective at this time. However, the reference case of this analysis does demonstrate that total ankle arthroplasty has the potential to be a cost-effective alternative to ankle fusion. This reference case assumes that the theoretical functional advantages of ankle arthroplasty over ankle fusion will be borne out in future clinical studies. Performance of total ankle replacement will be better justified if these thresholds are met in published long-term clinical trials.
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A New Method for Assessing How Sensitivity and Specificity of Linkage Studies Affects Estimation
Moore, Cecilia L.; Amin, Janaki; Gidding, Heather F.; Law, Matthew G.
2014-01-01
Background While the importance of record linkage is widely recognised, few studies have attempted to quantify how linkage errors may have impacted on their own findings and outcomes. Even where authors of linkage studies have attempted to estimate sensitivity and specificity based on subjects with known status, the effects of false negatives and positives on event rates and estimates of effect are not often described. Methods We present quantification of the effect of sensitivity and specificity of the linkage process on event rates and incidence, as well as the resultant effect on relative risks. Formulae to estimate the true number of events and estimated relative risk adjusted for given linkage sensitivity and specificity are then derived and applied to data from a prisoner mortality study. The implications of false positive and false negative matches are also discussed. Discussion Comparisons of the effect of sensitivity and specificity on incidence and relative risks indicate that it is more important for linkages to be highly specific than sensitive, particularly if true incidence rates are low. We would recommend that, where possible, some quantitative estimates of the sensitivity and specificity of the linkage process be performed, allowing the effect of these quantities on observed results to be assessed. PMID:25068293
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Savage, Emma J; Lowndes, Catherine M; Sullivan, Ann K; Back, David J; Else, Laura J; Murphy, Gary; Gill, O Noel
2016-01-02
To assess the extent of nondisclosure of known HIV status among sexual health clinic attendees and to quantify the impact of nondisclosure on estimates of undiagnosed HIV prevalence and of the proportion of patients remaining undiagnosed on leaving the clinic. Serum samples from the unlinked anonymous survey of clinic attendees' archive were tested for antiretrovirals. Estimates of undiagnosed HIV were adjusted using the findings. Antiretrovirals were detected in 27% of samples taken from 'previously undiagnosed' attendees, who did not have an HIV test but were HIV positive as detected by unlinked anonymous testing, indicating nondisclosure; 24% of such samples from MSM had antiretrovirals present compared with 32% of heterosexual men and women. Antiretrovirals were detected in 33% of samples from London clinics and in 21% from non-London clinics. Following adjustment, the estimated prevalence of undiagnosed HIV decreased nonsignificantly from 3.04% (95% confidence interval 2.71-3.41) to 2.66% (2.35-3.01) among men who have sex with men (MSM), 0.31% (0.26-0.37) to 0.30% (0.25-0.36) in heterosexual men and 0.40% (0.35-0.46) to 0.37% (0.32-0.43) in women; 7% of MSM who do not have an HIV test at a clinic visit will be infected with HIV and remain unaware of their infection. Nondisclosure of HIV status to healthcare professionals occurs among clinic attendees. Adjustment for nondisclosure results in a small, nonsignificant decrease in the prevalence of undiagnosed HIV estimated from the unlinked anonymous survey in sexual health clinics. Testing the population of MSM not having an HIV test remains a priority as levels of undiagnosed HIV are high.
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Griffiths, Robert I.; Gleeson, Michelle L.; Mikhael, Joseph; Danese, Mark D.
2012-01-01
Rituximab improves survival in follicular lymphoma (FL), but is considerably more expensive than conventional chemotherapy. We estimated the total direct medical costs, cumulative survival, and cost-effectiveness of adding rituximab to first-line chemotherapy for FL, based on a single source of data representing routine practice in the elderly. Using surveillance, epidemiology, and end results (SEER) registry data plus Medicare claims, we identified 1,117 FL patients who received first-line CHOP (cyclophosphamide (C), doxorubicin, vincristine (V), and prednisone (P)) or CVP +/− rituximab. Multivariate regression was used to estimate adjusted cumulative cost and survival differences between the two groups over four years after beginning treatment. The median age was 73 years (minimum 66 years), 56% had stage III-IV disease, and 67% received rituximab. Adding rituximab to first-line chemotherapy was associated with higher adjusted incremental total cost ($18,695; 95% Confidence Interval (CI) $9,302–$28,643) and longer adjusted cumulative survival (0.18 years; 95% CI 0.10–0.27) over four years of followup. The expected cost-effectiveness was $102,142 (95% CI $34,531–296,337) per life-year gained. In routine clinical practice, adding rituximab to first-line chemotherapy for elderly patients with FL results in higher direct medical costs to Medicare and longer cumulative survival after four years. PMID:22969803
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Noninvasive estimation of assist pressure for direct mechanical ventricular actuation
NASA Astrophysics Data System (ADS)
An, Dawei; Yang, Ming; Gu, Xiaotong; Meng, Fan; Yang, Tianyue; Lin, Shujing
2018-02-01
Direct mechanical ventricular actuation is effective to reestablish the ventricular function with non-blood contact. Due to the energy loss within the driveline of the direct cardiac compression device, it is necessary to acquire the accurate value of assist pressure acting on the heart surface. To avoid myocardial trauma induced by invasive sensors, the noninvasive estimation method is developed and the experimental device is designed to measure the sample data for fitting the estimation models. By examining the goodness of fit numerically and graphically, the polynomial model presents the best behavior among the four alternative models. Meanwhile, to verify the effect of the noninvasive estimation, the simplified lumped parameter model is utilized to calculate the pre-support and the post-support left ventricular pressure. Furthermore, by adjusting the driving pressure beyond the range of the sample data, the assist pressure is estimated with the similar waveform and the post-support left ventricular pressure approaches the value of the adult healthy heart, indicating the good generalization ability of the noninvasive estimation method.
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Surkan, P J; Shankar, M; Katz, J; Siegel, E H; Leclerq, S C; Khatry, S K; Stoltzfus, R J; Tielsch, J M
2012-07-01
To assess the effects of micronutrient supplementation on head circumference of rural Nepali infants and children. We used a randomized controlled trial to assess the effects of micronutrient supplementation on head circumference in 569 rural Nepali infants and children aged 4-17 months. Children were randomized to: (1) zinc, (2) iron-folic acid, (3) zinc plus iron-folic acid or (4) a placebo group. Data on head circumference were collected during five visits at ∼3 month intervals over the course of a year. We calculated change in head circumference in treatment groups receiving zinc and iron comparing the first and fifth visits as well as used generalized estimating equations (GEE) to take advantage of data from all points in time. Models were adjusted for covariates unbalanced in the randomization and for baseline head circumference. Estimating differences in head circumference between baseline and visit 5, children in the zinc treatment group showed smaller decreases in head circumference z-score compared with placebo (adjusted β=0.13, 95% confidence interval (CI): 0.03 to 0.23). Using GEE, zinc treatment was associated with 0.11 (95% CI: 0.05 to 0.17) decrease in the rate of decline in head circumference z-score across visits as compared with placebo. Iron-folic acid supplementation was not associated with head circumference z-scores when comparing visits 1 with 5 or including data across all visits in adjusted models. Our results suggest that zinc supplementation confers a beneficial effect on the rate of head growth in Nepali infants.
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Wu, Zhijin; Liu, Dongmei; Sui, Yunxia
2008-02-01
The process of identifying active targets (hits) in high-throughput screening (HTS) usually involves 2 steps: first, removing or adjusting for systematic variation in the measurement process so that extreme values represent strong biological activity instead of systematic biases such as plate effect or edge effect and, second, choosing a meaningful cutoff on the calculated statistic to declare positive compounds. Both false-positive and false-negative errors are inevitable in this process. Common control or estimation of error rates is often based on an assumption of normal distribution of the noise. The error rates in hit detection, especially false-negative rates, are hard to verify because in most assays, only compounds selected in primary screening are followed up in confirmation experiments. In this article, the authors take advantage of a quantitative HTS experiment in which all compounds are tested 42 times over a wide range of 14 concentrations so true positives can be found through a dose-response curve. Using the activity status defined by dose curve, the authors analyzed the effect of various data-processing procedures on the sensitivity and specificity of hit detection, the control of error rate, and hit confirmation. A new summary score is proposed and demonstrated to perform well in hit detection and useful in confirmation rate estimation. In general, adjusting for positional effects is beneficial, but a robust test can prevent overadjustment. Error rates estimated based on normal assumption do not agree with actual error rates, for the tails of noise distribution deviate from normal distribution. However, false discovery rate based on empirically estimated null distribution is very close to observed false discovery proportion.
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Mertens, Bart J. A.; Jacobs, Wilco C. H.; Brand, Ronald; Peul, Wilco C.
2014-01-01
We consider a re-analysis of the wait-and-see (control) arm of a recent clinical trial on sciatica. While the original randomised trial was designed to evaluate the public policy effect of a conservative wait-and-see approach versus early surgery, we investigate the impact of surgery at the individual patient level in a re-analysis of the wait-and-see group data. Both marginal structural model re-weighted estimates as well as propensity score adjusted analyses are presented. Results indicate that patients with high propensity to receive surgery may have beneficial effects at 2 years from delayed disc surgery. PMID:25353633
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Pelligra, Christopher G; Parikh, Kejal; Guo, Shien; Chandler, Conor; Mouro, Jorge; Abouzaid, Safiya; Ailawadhi, Sikander
2017-10-01
Pomalidomide plus low-dose dexamethasone (POM-d), daratumumab monotherapy (DARA), and carfilzomib monotherapy (CAR) have been approved for use in the treatment of patients with heavily pretreated relapsed-refractory multiple myeloma (RRMM) in the US, based on findings from the MM-002, SIRIUS, and PX-171-003-A1 studies, respectively. The objective of this study was to assess the cost-effectiveness of POM-d, DARA, and CAR in this patient population from a US payer's perspective. A cost-effectiveness model was developed to estimate the cost and health outcomes over a 3-year time horizon in 3 health states: progression-free, post-progression, and death. The main efficacy data source was a matching-adjusted indirect comparison using data from the aforementioned studies. Direct medical costs were considered, including: treatment acquisition and administration (initial line and subsequent line), pre- and post-medication, prophylaxis treatment, adverse event management, and health care resource utilization. Sensitivity analyses were conducted. A scenario analysis that assumed equal efficacy across all 3 treatments was conducted. Costs, life-years, and quality-adjusted life-years were estimated and discounted at 3% per annum. Over 3 years, the use of POM-d was associated with similar life-years and quality-adjusted life-years gained compared with DARA and CAR (incremental: life-years, +0.02 and +0.07, respectively; quality-adjusted life-years, +0.01 and +0.05), and with a cost less than that of DARA (-$8,919) and similar to that of CAR (-$195). Sensitivity analyses illustrated that the results were sensitive to progression-free survival, treatment duration, and drug costs. An equal efficacy scenario resulted in cost-savings relative to those of both DARA and CAR (-$11,779 and -$12,595). POM-d may be a cost-effective treatment option relative to DARA or CAR in heavily pretreated patients with RRMM in the US. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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McCabe, G.J.
1989-01-01
Errors of the Thornthwaite model can be analyzed using adjusted pan evaporation as an index of potential evapotranspiration. An examination of ratios of adjusted pan evaporation to Thornthwaite potential evapotranspiration indicates that the ratios are highest in the winter and lowest during summer months. This trend suggests a parabolic pattern. In this study a parabolic function is used to adjust Thornthwaite estimates of potential evapotranspiration. Forty locations east of the Rocky Mountains are analyzed. -from Author
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Beeman, John W.; Kock, Tobias J.; Perry, Russell W.; Smith, Steven G.
2011-01-01
We performed a series of analyses of mark-recapture data from a study at The Dalles Dam during 2010 to determine if model assumptions for estimation of juvenile salmonid dam-passage survival were met and if results were similar to those using the University of Washington's newly developed ATLAS software. The study was conducted by the Pacific Northwest National Laboratory and used acoustic telemetry of yearling Chinook salmon, juvenile steelhead, and subyearling Chinook salmon released at three sites according to the new virtual/paired-release statistical model. This was the first field application of the new model, and the results were used to measure compliance with minimum survival standards set forth in a recent Biological Opinion. Our analyses indicated that most model assumptions were met. The fish groups mixed in time and space, and no euthanized tagged fish were detected. Estimates of reach-specific survival were similar in fish tagged by each of the six taggers during the spring, but not in the summer. Tagger effort was unevenly allocated temporally during tagging of subyearling Chinook salmon in the summer; the difference in survival estimates among taggers was more likely a result of a temporal trend in actual survival than of tagger effects. The reach-specific survival of fish released at the three sites was not equal in the reaches they had in common for juvenile steelhead or subyearling Chinook salmon, violating one model assumption. This violation did not affect the estimate of dam-passage survival, because data from the common reaches were not used in its calculation. Contrary to expectation, precision of survival estimates was not improved by using the most parsimonious model of recapture probabilities instead of the fully parameterized model. Adjusting survival estimates for differences in fish travel times and tag lives increased the dam-passage survival estimate for yearling Chinook salmon by 0.0001 and for juvenile steelhead by 0.0004. The estimate was unchanged for subyearling Chinook salmon. The tag-life-adjusted dam-passage survival estimates from our analyses were 0.9641 (standard error [SE] 0.0096) for yearling Chinook salmon, 0.9534 (SE 0.0097) for juvenile steelhead, and 0.9404 (SE 0.0091) for subyearling Chinook salmon. These were within 0.0001 of estimates made by the University of Washington using the ATLAS software. Contrary to the intent of the virtual/paired-release model to adjust estimates of the paired-release model downward in order to account for differential handling mortality rates between release groups, random variation in survival estimates may result in an upward adjustment of survival relative to estimates from the paired-release model. Further investigation of this property of the virtual/paired-release model likely would prove beneficial. In addition, we suggest that differential selective pressures near release sites of the two control groups could bias estimates of dam-passage survival from the virtual/paired-release model.
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More, S J; Clegg, T A; Lynch, P J; O'Grady, L
2013-06-01
Somatic cell count (SCC) limits are a key component of national and international regulation for milk quality. As yet, very limited work has been published on SCC regulatory standards, including on the effect of different approaches to SCC data adjustment and interpretation. This study examines the effect of SCC data adjustment and interpretation, as outlined in current European Union (EU) legislation, on herd eligibility to supply raw milk for processing of dairy products for human consumption, using Irish data for illustration. The study used Irish milk-recording data as a proxy for bulk tank SCC (BTSCC) data, to calculate an unadjusted monthly SCC value for each herd during each month of participation. Subsequently, 4 data adjustments were applied, as outlined in EU and national legislation: seasonal adjustment; 3-mo rolling geometric average, without accounting for a break in the supply; 3-mo rolling geometric average, after accounting for a break in the supply; and seasonal adjustment and 3-mo rolling geometric average combined, after accounting for a break in the supply. Analyses were conducted to examine the effect, during the period from 2004 to 2010, of data adjustment on the percentage of herds with herd SCC >400,000 cells/mL. In all, 4 interpretation scenarios, incorporating different data adjustment combinations, were used to estimate herd eligibility (compliant, under warning, or suspended, as defined by legislation) to supply raw milk for processing. The 4 methods of data adjustment each led to a sizable reduction (6.7, 5.0, 5.3, and 11.1 percentage points, respectively, compared with the unadjusted data) in the percentage of herds exceeding a herd SCC of 400,000 cells/mL. Herd eligibility varied by interpretation scenarios, in particular those incorporating seasonal adjustment. The study provides new perspectives on the effect of data adjustment on herd SCC and of interpretation scenarios on herd eligibility. The results provide an illustrative, rather than definitive, picture of this effect, as national authorities use BTSCC data when determining herd eligibility, whereas this study was conducted using milk-recording data as a proxy. Some aspects of the primary EU legislation are unclear, which may lead to differences in interpretation and application. The potential impact of data adjustment and milk purchaser pricing on farm-level mastitis control in Ireland is considered. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Radar QPE for hydrological design: Intensity-Duration-Frequency curves
NASA Astrophysics Data System (ADS)
Marra, Francesco; Morin, Efrat
2015-04-01
Intensity-duration-frequency (IDF) curves are widely used in flood risk management since they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. They are estimated analyzing the extreme values of rainfall records, usually basing on raingauge data. This point-based approach raises two issues: first, hydrological design applications generally need IDF information for the entire catchment rather than a point, second, the representativeness of point measurements decreases with the distance from measure location, especially in regions characterized by steep climatological gradients. Weather radar, providing high resolution distributed rainfall estimates over wide areas, has the potential to overcome these issues. Two objections usually restrain this approach: (i) the short length of data records and (ii) the reliability of quantitative precipitation estimation (QPE) of the extremes. This work explores the potential use of weather radar estimates for the identification of IDF curves by means of a long length radar archive and a combined physical- and quantitative- adjustment of radar estimates. Shacham weather radar, located in the eastern Mediterranean area (Tel Aviv, Israel), archives data since 1990 providing rainfall estimates for 23 years over a region characterized by strong climatological gradients. Radar QPE is obtained correcting the effects of pointing errors, ground echoes, beam blockage, attenuation and vertical variations of reflectivity. Quantitative accuracy is then ensured with a range-dependent bias adjustment technique and reliability of radar QPE is assessed by comparison with gauge measurements. IDF curves are derived from the radar data using the annual extremes method and compared with gauge-based curves. Results from 14 study cases will be presented focusing on the effects of record length and QPE accuracy, exploring the potential application of radar IDF curves for ungauged locations and providing insights on the use of radar QPE for hydrological design studies.
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Ash reduction system using electrically heated particulate matter filter
Gonze, Eugene V [Pinckney, MI; Paratore, Jr., Michael J; He, Yongsheng [Sterling Heights, MI
2011-08-16
A control system for reducing ash comprises a temperature estimator module that estimates a temperature of an electrically heated particulate matter (PM) filter. A temperature and position estimator module estimates a position and temperature of an oxidation wave within the electrically heated PM filter. An ash reduction control module adjusts at least one of exhaust flow, fuel and oxygen levels in the electrically heated PM filter to adjust a position of the oxidation wave within the electrically heated PM filter based on the oxidation wave temperature and position.
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Yanagawa, T; Tokudome, S
1990-01-01
We developed methods to assess the cancer risks by screening tests. These methods estimate the size of the high risk group adjusted for the characteristics of screening tests and estimate the incidence rates of cancer among the high risk group adjusted for the characteristics of the tests. A method was also developed for selecting the cut-off point of a screening test. Finally, the methods were applied to estimate the risk of the adult T-cell leukemia/lymphoma. PMID:2269244
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Sun, Yanqing; Sun, Liuquan; Zhou, Jie
2013-07-01
This paper studies the generalized semiparametric regression model for longitudinal data where the covariate effects are constant for some and time-varying for others. Different link functions can be used to allow more flexible modelling of longitudinal data. The nonparametric components of the model are estimated using a local linear estimating equation and the parametric components are estimated through a profile estimating function. The method automatically adjusts for heterogeneity of sampling times, allowing the sampling strategy to depend on the past sampling history as well as possibly time-dependent covariates without specifically model such dependence. A [Formula: see text]-fold cross-validation bandwidth selection is proposed as a working tool for locating an appropriate bandwidth. A criteria for selecting the link function is proposed to provide better fit of the data. Large sample properties of the proposed estimators are investigated. Large sample pointwise and simultaneous confidence intervals for the regression coefficients are constructed. Formal hypothesis testing procedures are proposed to check for the covariate effects and whether the effects are time-varying. A simulation study is conducted to examine the finite sample performances of the proposed estimation and hypothesis testing procedures. The methods are illustrated with a data example.
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Bastos, Francisco I; Bastos, Leonardo Soares; Coutinho, Carolina; Toledo, Lidiane; Mota, Jurema Corrêa; Velasco-de-Castro, Carlos Augusto; Sperandei, Sandro; Brignol, Sandra; Travassos, Tamiris Severino; Dos Santos, Camila Mattos; Malta, Monica Siqueira
2018-05-01
Different sampling strategies, analytic alternatives, and estimators have been proposed to better assess the characteristics of different hard-to-reach populations and their respective infection rates (as well as their sociodemographic characteristics, associated harms, and needs) in the context of studies based on respondent-driven sampling (RDS). Despite several methodological advances and hundreds of empirical studies implemented worldwide, some inchoate findings and methodological challenges remain. The in-depth assessment of the local structure of networks and the performance of the available estimators are particularly relevant when the target populations are sparse and highly stigmatized. In such populations, bottlenecks as well as other sources of biases (for instance, due to homophily and/or too sparse or fragmented groups of individuals) may be frequent, affecting the estimates.In the present study, data were derived from a cross-sectional, multicity RDS study, carried out in 12 Brazilian cities with transgender women (TGW). Overall, infection rates for HIV and syphilis were very high, with some variation between different cities. Notwithstanding, findings are of great concern, considering the fact that female TGW are not only very hard-to-reach but also face deeply-entrenched prejudice and have been out of the reach of most therapeutic and preventive programs and projects.We cross-compared findings adjusted using 2 estimators (the classic estimator usually known as estimator II, originally proposed by Volz and Heckathorn) and a brand new strategy to adjust data generated by RDS, partially based on Bayesian statistics, called for the sake of this paper, the RDS-B estimator. Adjusted prevalence was cross-compared with estimates generated by non-weighted analyses, using what has been called by us a naïve estimator or rough estimates.
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Aging, mobility impairments and subjective wellbeing.
Freedman, Vicki A; Carr, Deborah; Cornman, Jennifer C; Lucas, Richard E
2017-10-01
Wellbeing is often described as U-shaped over the life course, suggesting an apparent paradox that wellbeing remains high at older ages despite increases in impairments. We explore associations among age, lower body impairments-one of the most common late-life impairments-and three measures of wellbeing: life satisfaction, emotional wellbeing and somatic wellbeing. We hypothesize that age effects are positive, become stronger once lower body impairments are controlled, and are concentrated among those who have maintained their mobility. Net of confounding factors, we hypothesize that lower body impairments are associated with worse wellbeing and these effects diminish with advancing age. We analyze the 2013 Disability and Use of Time supplement to the Panel Study of Income Dynamics (N = 1607 adults ages 60 and older). We estimate nested regression models that include age, severity of lower body impairments and confounding demographic, psychological, and socioeconomic factors and activities; test age-impairment interactions; and estimate age- and impairment-stratified models. Positive age effects were observed after controlling for lower body impairments for life satisfaction (β = 0.90; p < 0.05), although statistical significance weakened (p = 0.07) in fully adjusted models. For emotional wellbeing, adjusted age effects were negative (β = -0.05; p < 0.05) and were concentrated among those with limitations (β = -0.14; p < 0.01). For all three outcomes, severity of impairments reduced wellbeing in adjusted models. These effects were strongest for somatic wellbeing, especially for 65-74 year olds. Our study challenges the notion that wellbeing is U-shaped throughout the life course and underscores the critical role of mobility across wellbeing domains in later life. Copyright © 2017 Elsevier Inc. All rights reserved.
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Cost effectiveness of lung-volume-reduction surgery for patients with severe emphysema.
Ramsey, Scott D; Berry, Kristin; Etzioni, Ruth; Kaplan, Robert M; Sullivan, Sean D; Wood, Douglas E
2003-05-22
The National Emphysema Treatment Trial, a randomized clinical trial comparing lung-volume-reduction surgery with medical therapy for severe emphysema, included a prospective economic analysis. After pulmonary rehabilitation, 1218 patients at 17 medical centers were randomly assigned to lung-volume-reduction surgery or continued medical treatment. Costs for the use of medical care, medications, transportation, and time spent receiving treatment were derived from Medicare claims and data from the trial. Cost effectiveness was calculated over the duration of the trial and was estimated for 10 years of follow-up with the use of modeling based on observed trends in survival, cost, and quality of life. Interim analyses identified a group of patients with excess mortality and little chance of improved functional status after surgery. When these patients were excluded, the cost-effectiveness ratio for lung-volume-reduction surgery as compared with medical therapy was 190,000 dollars per quality-adjusted life-year gained at 3 years and 53,000 dollars per quality-adjusted life-year gained at 10 years. Subgroup analyses identified patients with predominantly upper-lobe emphysema and low exercise capacity after pulmonary rehabilitation who had lower mortality and better functional status than patients who received medical therapy. The cost-effectiveness ratio in this subgroup was 98,000 dollars per quality-adjusted life-year gained at 3 years and 21,000 dollars at 10 years. Bootstrap analysis revealed substantial uncertainty for the subgroup and 10-year estimates. Given its cost and benefits over three years of follow-up, lung-volume-reduction surgery is costly relative to medical therapy. Although the predictions are subject to substantial uncertainty, the procedure may be cost effective if benefits can be maintained over time. Copyright 2003 Massachusetts Medical Society
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Chan, Siew Foong; Deeks, Jonathan J; Macaskill, Petra; Irwig, Les
2008-01-01
To compare three predictive models based on logistic regression to estimate adjusted likelihood ratios allowing for interdependency between diagnostic variables (tests). This study was a review of the theoretical basis, assumptions, and limitations of published models; and a statistical extension of methods and application to a case study of the diagnosis of obstructive airways disease based on history and clinical examination. Albert's method includes an offset term to estimate an adjusted likelihood ratio for combinations of tests. Spiegelhalter and Knill-Jones method uses the unadjusted likelihood ratio for each test as a predictor and computes shrinkage factors to allow for interdependence. Knottnerus' method differs from the other methods because it requires sequencing of tests, which limits its application to situations where there are few tests and substantial data. Although parameter estimates differed between the models, predicted "posttest" probabilities were generally similar. Construction of predictive models using logistic regression is preferred to the independence Bayes' approach when it is important to adjust for dependency of tests errors. Methods to estimate adjusted likelihood ratios from predictive models should be considered in preference to a standard logistic regression model to facilitate ease of interpretation and application. Albert's method provides the most straightforward approach.
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Pedroza, Claudia; Truong, Van Thi Thanh
2017-11-02
Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios. We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions. All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs. For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors.
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Harris-Adamson, Carisa; Eisen, Ellen A; Neophytou, Andreas; Kapellusch, Jay; Garg, Arun; Hegmann, Kurt T; Thiese, Matthew S; Dale, Ann Marie; Evanoff, Bradley; Bao, Stephen; Silverstein, Barbara; Gerr, Fred; Burt, Susan; Rempel, David
2016-11-01
Between 2001 and 2010, six research groups conducted coordinated prospective studies of carpal tunnel syndrome (CTS) incidence among US workers from various industries to estimate exposure-response relationships. This analysis examined the presence and magnitude of confounding between biomechanical and workplace psychosocial factors and incidence of dominant-hand CTS. 1605 participants, without CTS at enrolment, were followed for up to 3.5 years (2471 person-years). Demographic information, medical history and workplace psychosocial stress measures were collected at baseline. Individual workplace biomechanical exposures were collected for each task and combined across the workweek using time-weighted averaging (TWA). CTS case criteria were based on symptoms and results of electrophysiological testing. HRs were estimated with Cox proportional hazard models. Confounding was assessed using causal diagrams and an empirical criterion of 10% or greater change in effect estimate magnitude. There were 109 incident CTS cases (IR=4.41/100 person-years; 6.7% cumulative incidence). The relationships between CTS and forceful repetition rate, % time forceful hand exertion and the Threshold Limit Value for Hand Activity Level (TLV-HAL) were slightly confounded by decision latitude with effect estimates being attenuated towards the null (10-14% change) after adjustment. The risk of CTS among participants reporting high job strain was attenuated towards the null by 14% after adjusting for the HAL Scale or the % time forceful hand exertions. Although attenuation of the relationships between CTS and some biomechanical and work psychosocial exposures was observed after adjusting for confounding, the magnitudes were small and confirmed biomechanical and work psychosocial exposures as independent risk factors for incident CTS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
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Subgroup Economic Evaluation of Radiotherapy for Breast Cancer After Mastectomy.
Wan, Xiaomin; Peng, Liubao; Ma, Jinan; Chen, Gannong; Li, Yuanjian
2015-11-01
A recent meta-analysis by the Early Breast Cancer Trialists' Collaborative Group found significant improvements achieved by postmastectomy radiotherapy (PMRT) for patients with breast cancer with 1 to 3 positive nodes (pN1-3). It is unclear whether PMRT is cost-effective for subgroups of patients with positive nodes. To determine the cost-effectiveness of PMRT for subgroups of patients with breast cancer with positive nodes. A semi-Markov model was constructed to estimate the expected lifetime costs, life expectancy, and quality-adjusted life-years for patients receiving or not receiving radiation therapy. Clinical and health utilities data were from meta-analyses by the Early Breast Cancer Trialists' Collaborative Group or randomized clinical trials. Costs were estimated from the perspective of the Chinese society. One-way and probabilistic sensitivity analyses were performed. The incremental cost-effective ratio was estimated as $7984, $4043, $3572, and $19,021 per quality-adjusted life-year for patients with positive nodes (pN+), patients with pN1-3, patients with pN1-3 who received systemic therapy, and patients with >4 positive nodes (pN4+), respectively. According to World Health Organization recommendations, these incremental cost-effective ratios were judged as cost-effective. However, the results of one-way sensitivity analyses suggested that the results were highly sensitive to the relative effectiveness of PMRT (rate ratio). We determined that the results were highly sensitive to the rate ratio. However, the addition of PMRT for patients with pN1-3 in China has a reasonable chance to be cost-effective and may be judged as an efficient deployment of limited health resource, and the risk and uncertainty of PMRT are relatively greater for patients with pN4+. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.
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Supersensitive ancilla-based adaptive quantum phase estimation
NASA Astrophysics Data System (ADS)
Larson, Walker; Saleh, Bahaa E. A.
2017-10-01
The supersensitivity attained in quantum phase estimation is known to be compromised in the presence of decoherence. This is particularly patent at blind spots—phase values at which sensitivity is totally lost. One remedy is to use a precisely known reference phase to shift the operation point to a less vulnerable phase value. Since this is not always feasible, we present here an alternative approach based on combining the probe with an ancillary degree of freedom containing adjustable parameters to create an entangled quantum state of higher dimension. We validate this concept by simulating a configuration of a Mach-Zehnder interferometer with a two-photon probe and a polarization ancilla of adjustable parameters, entangled at a polarizing beam splitter. At the interferometer output, the photons are measured after an adjustable unitary transformation in the polarization subspace. Through calculation of the Fisher information and simulation of an estimation procedure, we show that optimizing the adjustable polarization parameters using an adaptive measurement process provides globally supersensitive unbiased phase estimates for a range of decoherence levels, without prior information or a reference phase.
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A framework for the meta-analysis of Bland-Altman studies based on a limits of agreement approach.
Tipton, Elizabeth; Shuster, Jonathan
2017-10-15
Bland-Altman method comparison studies are common in the medical sciences and are used to compare a new measure to a gold-standard (often costlier or more invasive) measure. The distribution of these differences is summarized by two statistics, the 'bias' and standard deviation, and these measures are combined to provide estimates of the limits of agreement (LoA). When these LoA are within the bounds of clinically insignificant differences, the new non-invasive measure is preferred. Very often, multiple Bland-Altman studies have been conducted comparing the same two measures, and random-effects meta-analysis provides a means to pool these estimates. We provide a framework for the meta-analysis of Bland-Altman studies, including methods for estimating the LoA and measures of uncertainty (i.e., confidence intervals). Importantly, these LoA are likely to be wider than those typically reported in Bland-Altman meta-analyses. Frequently, Bland-Altman studies report results based on repeated measures designs but do not properly adjust for this design in the analysis. Meta-analyses of Bland-Altman studies frequently exclude these studies for this reason. We provide a meta-analytic approach that allows inclusion of estimates from these studies. This includes adjustments to the estimate of the standard deviation and a method for pooling the estimates based upon robust variance estimation. An example is included based on a previously published meta-analysis. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
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Halsteinli, Vidar; Kittelsen, Sverre A; Magnussen, Jon
2010-02-01
The performance of health service providers may be monitored by measuring productivity. However, the policy value of such measures may depend crucially on the accuracy of input and output measures. In particular, an important question is how to adjust adequately for case-mix in the production of health care. In this study, we assess productivity growth in Norwegian outpatient child and adolescent mental health service units (CAMHS) over a period characterized by governmental utilization of simple productivity indices, a substantial increase in capacity and a concurrent change in case-mix. We analyze the sensitivity of the productivity growth estimates using different specifications of output to adjust for case-mix differences. Case-mix adjustment is achieved by distributing patients into eight groups depending on reason for referral, age and gender, as well as correcting for the number of consultations. We utilize the nonparametric Data Envelopment Analysis (DEA) method to implicitly calculate weights that maximize each unit's efficiency. Malmquist indices of technical productivity growth are estimated and bootstrap procedures are performed to calculate confidence intervals and to test alternative specifications of outputs. The dataset consist of an unbalanced panel of 48-60 CAMHS in the period 1998-2006. The mean productivity growth estimate from a simple unadjusted patient model (one single output) is 35%; adjusting for case-mix (eight outputs) reduces the growth estimate to 15%. Adding consultations increases the estimate to 28%. The latter reflects an increase in number of consultations per patient. We find that the governmental productivity indices strongly tend to overestimate productivity growth. Case-mix adjustment is of major importance and governmental utilization of performance indicators necessitates careful considerations of output specifications. Copyright 2009 Elsevier Ltd. All rights reserved.
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Effect of the Smoke-Free Illinois Act on casino admissions and revenue.
Tauras, John A; Chaloupka, Frank J; Moor, Gregg; Henderson, Patricia Nez; Leischow, Scott J
2018-01-19
As part of the Smoke-Free Illinois Act, smoking on the gambling floors of all commercial casinos in Illinois became prohibited. This study examined the effects of the Smoke-Free Illinois Act on casino admissions per-capita and real per-capita adjusted gross receipts using 18 years of data (10 years before and 8 years after the Illinois law went into effect). We employed a difference-in-difference regression technique using monthly data for the states of Illinois, Indiana, Iowa and Missouri and control for numerous determinants expected to affect casino admissions and revenue. The Smoke-free Illinois Act was found not to be a statistically significant determinant of per-capita casino admissions and of real per-capita gross adjusted receipts in all the models we estimated. The estimates from this study clearly indicated that the Illinois law that banned smoking in casinos has had no significant negative economic consequences for casinos in terms of per-capita admissions or revenues. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Vardarajan, Badri N; Schaid, Daniel J; Reitz, Christiane; Lantigua, Rafael; Medrano, Martin; Jiménez-Velázquez, Ivonne Z; Lee, Joseph H; Ghani, Mahdi; Rogaeva, Ekaterina; St George-Hyslop, Peter; Mayeux, Richard P
2015-08-01
Inbreeding can be associated with a modification of disease risk due to excess homozygosity of recessive alleles affecting a wide range of phenotypes. We estimated the inbreeding coefficient in Caribbean Hispanics and examined its effects on risk of late-onset Alzheimer disease. The inbreeding coefficient was calculated in 3,392 subjects (1,451 late-onset Alzheimer disease patients and 1,941 age-matched healthy controls) of Caribbean Hispanic ancestry using 177,997 nearly independent single-nucleotide polymorphisms from genome-wide array. The inbreeding coefficient was estimated using the excess homozygosity method with and without adjusting for admixture. The average inbreeding coefficient in Caribbean Hispanics without accounting for admixture was F = 0.018 (±0.048), suggesting a mating equivalent to that of second cousins or second cousins once removed. Adjusting for admixture from three parent populations, the average inbreeding coefficient was found to be 0.0034 (±0.019) or close to third-cousin mating. Inbreeding coefficient was a significant predictor of Alzheimer disease when age, sex, and APOE genotype were used as adjusting covariates (P = 0.03). The average inbreeding coefficient of this population is significantly higher than that of the general Caucasian populations in North America. The high rate of inbreeding resulting in increased frequency of recessive variants is advantageous for the identification of rare variants associated with late-onset Alzheimer disease.Genet Med 17 8, 639-643.
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Zaccardi, Francesco; O'Donovan, Gary; Webb, David R; Yates, Thomas; Kurl, Sudhir; Khunti, Kamlesh; Davies, Melanie J; Laukkanen, Jari A
2015-11-01
To investigate the association between cardiorespiratory fitness (CRF) and type 2 diabetes mellitus (T2DM) in a cohort of middle-age Finnish men and to summarise the current evidence in a meta-analysis of prospective studies. CRF was measured at baseline in a random population-based sample of 2520 subjects by assessing oxygen uptake during maximal exercise. Cox regression analysis was used to estimate the association between CRF, expressed as metabolic equivalents (METs), and the risk of T2DM adjusted for potential confounders; this estimate was then pooled with the results of other prospective studies in a meta-analysis. Mean (SD) baseline age and CRF were 53 (5) years and 8.7 (2.1) METs, respectively. During 23 years of follow-up, 153 (6.1%) participants developed T2DM. The hazard ratio per 1-MET higher CRF, adjusted for age, body mass index, systolic blood pressure, serum HDL-cholesterol, and family history of T2DM, was 0.93 (95% confidence interval (CI): 0.84, 1.02; p = 0.109); further adjustment for smoking, education, and socioeconomic status did not materially change the estimate. In a random-effects meta-analysis of eight studies (92,992 participants and 8564 T2DM cases) combining maximally adjusted estimates, the pooled risk ratio of T2DM per 1-MET higher CRF level was 0.95 (95% CI: 0.93, 0.98; p = 0.003; I(2) = 81%), corresponding to 23 fewer cases per 100,000 person-years based on the assumption of a causal link between CRF and T2DM. These data suggest that there is an inverse relationship between CRF and T2DM that is largely independent of other risk factors. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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Meteorological adjustment of yearly mean values for air pollutant concentration comparison
NASA Technical Reports Server (NTRS)
Sidik, S. M.; Neustadter, H. E.
1976-01-01
Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.
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Keall, Michael; Frith, William
2004-12-01
It is well established that older drivers' fragility is an important factor associated with higher levels of fatal crash involvement for older drivers. There has been less research on age-related fragility with respect to the sort of minor injuries that are more common in injury crashes. This study estimates a quantity that is related to injury fragility: the probability that a driver or a passenger of that driver will be injured in crashes involving two cars. The effects of other factors apart from drivers' fragility are included in this measure, including the fragility of the passengers, the crashworthiness of cars driven, seatbelt use by the occupants, and characteristics of crashes (including configuration and impact speed). The car occupant injury liability estimates appropriately includes these factors to adjust risk curves by age, gender, and speed limit accounting for overrepresentation in crashes associated with fragility and these other factors.
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Uhlig, Benjamin Langsæter; Sand, Trond; Odegård, Siv Steinsmo; Hagen, Knut
2014-06-01
Many studies have assessed the prevalence of insomnia, but the influence of non-participants has largely been ignored. The objective of the present study was to estimate the prevalence and associated factors of insomnia in a large adult population using DSM-V (diagnostic and statistical manual of mental disorders, 5th ed.) criteria, also taking non-participants into account. This cross-sectional study used data from a questionnaire in The Nord-Trøndelag Health Study (HUNT 3) performed in 2006-2008, and a subsequent non-participant study. The total adult population (n=93,860 aged > or =20 years) of Nord-Trøndelag County, Norway, was invited. Of these, 40,535 responded to the insomnia questionnaire. Among 42,024 eligible non-participants, 6918 (17%) responded to two insomnia questions. Insomnia was diagnosed by applying modified DSM-V criteria. The age-adjusted insomnia prevalence was estimated using the age distribution of all adult inhabitants of Nord-Trøndelag. Supplementary prevalence data were estimated by extrapolating data from the non-participant study. Additionally, the association between insomnia and self-reported health was estimated, adjusting for known confounders. The total age-adjusted prevalence of insomnia was 7.1% (95% confidence interval [CI], 6.9-7.4) (8.6% for women, 5.5% for men). Adjusting for non-participants, the prevalence estimate changed to 7.9% (95% CI, 7.3-8.6) (9.4% for women, 6.4% for men). Insomnia was more than eight times more likely (OR, 8.3; 95% CI, 6.2-11.1) among individuals with very poor versus very good self-reported health, adjusting for age, gender, employment status, chronic musculoskeletal complaints, anxiety and depression. The adjusted insomnia prevalence estimate in Nord-Trøndelag was 7.9%. Insomnia was strongly associated with poor self-reported health. Copyright © 2014 Elsevier B.V. All rights reserved.
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McKenzie, Fiona; Biessy, Carine; Ferrari, Pietro; Freisling, Heinz; Rinaldi, Sabina; Chajès, Veronique; Dahm, Christina C; Overvad, Kim; Dossus, Laure; Lagiou, Pagona; Trichopoulos, Dimitrios; Trichopoulou, Antonia; Bueno-de-Mesquita, H Bas; May, Anne; Peeters, Petra H; Weiderpass, Elisabete; Sanchez, Maria-Jose; Navarro, Carmen; Ardanaz, Eva; Ericson, Ulrika; Wirfält, Elisabet; Travis, Ruth C; Romieu, Isabelle
2016-04-01
It has been estimated that at least a third of the most common cancers are related to lifestyle and as such are preventable. Key modifiable lifestyle factors have been individually associated with cancer risk; however, less is known about the combined effects of these factors. This study generated a healthy lifestyle index score (HLIS) to investigate the joint effect of modifiable factors on the risk of overall cancers, alcohol-related cancers, tobacco-related cancers, obesity-related cancers, and reproductive-related cancers. The study included 391,608 men and women from the multinational European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The HLIS was constructed from 5 factors assessed at baseline (diet, physical activity, smoking, alcohol consumption, and anthropometry) by assigning scores of 0 to 4 to categories of each factor, for which higher values indicate healthier behaviors. Hazard ratios (HR) were estimated by Cox proportional regression and population attributable fractions (PAFs) estimated from the adjusted models. There was a 5% lower risk (adjusted HR 0.952, 95% confidence interval (CI): 0.946, 0.958) of all cancers per point score of the index for men and 4% (adjusted HR 0.961, 95% CI: 0.956, 0.966) for women. The fourth versus the second category of the HLIS was associated with a 28% and 24% lower risk for men and women respectively across all cancers, 41% and 33% for alcohol-related, 49% and 46% for tobacco-related, 41% and 26% for obesity-related, and 21% for female reproductive cancers. Findings suggest simple behavior modifications could have a sizeable impact on cancer prevention, especially for men.
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The uterine leiomyoma and placenta previa: a meta-analysis.
Jenabi, Ensiyeh; Fereidooni, Bita
2017-11-21
Some epidemiological studies have reported that uterine leiomyoma may increase the risk of placenta previa. To date, the meta-analysis has not been carried out for assessing the relationship between uterine leiomyoma and placenta previa. This meta-analysis was carried out to estimate the association between uterine leiomyoma and the risk of placenta previa. A systematic search was conducted out in major databases PubMed, Web of Science, and Scopus from the earliest possible year to June 2017. The heterogeneity across studies was explored by Q-test and I 2 statistic. The publication bias was assessed by Begg's and Egger's tests. The results were showed using odds ratio (OR) estimate with its 95% confidence intervals (CI) using a random-effects model. The literature search included 1218 articles until to June 2017 with 255,886 women. Based on OR estimates obtained from case-control and cohort studies, there was significant association between uterine leiomyoma and placenta previa in studies adjusted (2.21; 95%CI: 1.48, 2.94). We showed based on reports in observational studies that uterine leiomyoma is a risk factor for placenta previa in studies adjusted.
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Matching with Multiple Control Groups with Adjustment for Group Differences
ERIC Educational Resources Information Center
Stuart, Elizabeth A.; Rubin, Donald B.
2008-01-01
When estimating causal effects from observational data, it is desirable to approximate a randomized experiment as closely as possible. This goal can often be achieved by choosing a subsample from the original control group that matches the treatment group on the distribution of the observed covariates. However, sometimes the original control group…
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Potential lost productivity resulting from the global burden of uncorrected refractive error.
Smith, T S T; Frick, K D; Holden, B A; Fricke, T R; Naidoo, K S
2009-06-01
To estimate the potential global economic productivity loss associated with the existing burden of visual impairment from uncorrected refractive error (URE). Conservative assumptions and national population, epidemiological and economic data were used to estimate the purchasing power parity-adjusted gross domestic product (PPP-adjusted GDP) loss for all individuals with impaired vision and blindness, and for individuals with normal sight who provide them with informal care. An estimated 158.1 million cases of visual impairment resulted from uncorrected or undercorrected refractive error in 2007; of these, 8.7 million were blind. We estimated the global economic productivity loss in international dollars (I$) associated with this burden at I$ 427.7 billion before, and I$ 268.8 billion after, adjustment for country-specific labour force participation and employment rates. With the same adjustment, but assuming no economic productivity for individuals aged > 50 years, we estimated the potential productivity loss at I$ 121.4 billion. Even under the most conservative assumptions, the total estimated productivity loss, in $I, associated with visual impairment from URE is approximately a thousand times greater than the global number of cases. The cost of scaling up existing refractive services to meet this burden is unknown, but if each affected individual were to be provided with appropriate eyeglasses for less than I$ 1000, a net economic gain may be attainable.
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Potential lost productivity resulting from the global burden of uncorrected refractive error
Frick, KD; Holden, BA; Fricke, TR; Naidoo, KS
2009-01-01
Abstract Objective To estimate the potential global economic productivity loss associated with the existing burden of visual impairment from uncorrected refractive error (URE). Methods Conservative assumptions and national population, epidemiological and economic data were used to estimate the purchasing power parity-adjusted gross domestic product (PPP-adjusted GDP) loss for all individuals with impaired vision and blindness, and for individuals with normal sight who provide them with informal care. Findings An estimated 158.1 million cases of visual impairment resulted from uncorrected or undercorrected refractive error in 2007; of these, 8.7 million were blind. We estimated the global economic productivity loss in international dollars (I$) associated with this burden at I$ 427.7 billion before, and I$ 268.8 billion after, adjustment for country-specific labour force participation and employment rates. With the same adjustment, but assuming no economic productivity for individuals aged ≥ 50 years, we estimated the potential productivity loss at I$ 121.4 billion. Conclusion Even under the most conservative assumptions, the total estimated productivity loss, in $I, associated with visual impairment from URE is approximately a thousand times greater than the global number of cases. The cost of scaling up existing refractive services to meet this burden is unknown, but if each affected individual were to be provided with appropriate eyeglasses for less than I$ 1000, a net economic gain may be attainable. PMID:19565121
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Roobol, Monique J; Kerkhof, Melissa; Schröder, Fritz H; Cuzick, Jack; Sasieni, Peter; Hakama, Matti; Stenman, Ulf Hakan; Ciatto, Stefano; Nelen, Vera; Kwiatkowski, Maciej; Lujan, Marcos; Lilja, Hans; Zappa, Marco; Denis, Louis; Recker, Franz; Berenguer, Antonio; Ruutu, Mirja; Kujala, Paula; Bangma, Chris H; Aus, Gunnar; Tammela, Teuvo L J; Villers, Arnauld; Rebillard, Xavier; Moss, Sue M; de Koning, Harry J; Hugosson, Jonas; Auvinen, Anssi
2009-10-01
Prostate-specific antigen (PSA) based screening for prostate cancer (PCa) has been shown to reduce prostate specific mortality by 20% in an intention to screen (ITS) analysis in a randomised trial (European Randomised Study of Screening for Prostate Cancer [ERSPC]). This effect may be diluted by nonattendance in men randomised to the screening arm and contamination in men randomised to the control arm. To assess the magnitude of the PCa-specific mortality reduction after adjustment for nonattendance and contamination. We analysed the occurrence of PCa deaths during an average follow-up of 9 yr in 162,243 men 55-69 yr of age randomised in seven participating centres of the ERSPC. Centres were also grouped according to the type of randomisation (ie, before or after informed written consent). Nonattendance was defined as nonattending the initial screening round in ERSPC. The estimate of contamination was based on PSA use in controls in ERSPC Rotterdam. Relative risks (RRs) with 95% confidence intervals (CIs) were compared between an ITS analysis and analyses adjusting for nonattendance and contamination using a statistical method developed for this purpose. In the ITS analysis, the RR of PCa death in men allocated to the intervention arm relative to the control arm was 0.80 (95% CI, 0.68-0.96). Adjustment for nonattendance resulted in a RR of 0.73 (95% CI, 0.58-0.93), and additional adjustment for contamination using two different estimates led to estimated reductions of 0.69 (95% CI, 0.51-0.92) to 0.71 (95% CI, 0.55-0.93), respectively. Contamination data were obtained through extrapolation of single-centre data. No heterogeneity was found between the groups of centres. PSA screening reduces the risk of dying of PCa by up to 31% in men actually screened. This benefit should be weighed against a degree of overdiagnosis and overtreatment inherent in PCa screening.
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Prevalence of Individuals Experiencing the Effects of Stroke in Canada: Trends and Projections.
Krueger, Hans; Koot, Jacqueline; Hall, Ruth E; O'Callaghan, Christina; Bayley, Mark; Corbett, Dale
2015-08-01
Previous estimates of the number and prevalence of individuals experiencing the effects of stroke in Canada are out of date and exclude critical population groups. It is essential to have complete data that report on stroke disability for monitoring and planning purposes. The objective was to provide an updated estimate of the number of individuals experiencing the effects of stroke in Canada (and its regions), trending since 2000 and forecasted prevalence to 2038. The prevalence, trends, and projected number of individuals experiencing the effects of stroke were estimated using region-specific survey data and adjusted to account for children aged <12 years and individuals living in homes for the aged. In 2013, we estimate that there were 405 000 individuals experiencing the effects of stroke in Canada, yielding a prevalence of 1.15%. This value is expected to increase to between 654 000 and 726 000 by 2038. Trends in stroke data between 2000 and 2012 suggest a nonsignificant decrease in stroke prevalence, but a substantial and rising increase in the number of individuals experiencing the effects of stroke. Stroke prevalence varied considerably between regions. Previous estimates of stroke prevalence have underestimated the true number of individuals experiencing the effects of stroke in Canada. Furthermore, the projected increases that will result from population growth and demographic changes highlight the importance of maintaining up-to-date estimates. © 2015 American Heart Association, Inc.
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Haloacetic acids in drinking water and risk for stillbirth.
King, W D; Dodds, L; Allen, A C; Armson, B A; Fell, D; Nimrod, C
2005-02-01
Trihalomethanes (THMs) occurring in public drinking water sources have been investigated in several epidemiological studies of fetal death and results support a modest association. Other classes of disinfection by-products found in drinking water have not been investigated. To investigate the effects of haloacetic acid (HAA) compounds in drinking water on stillbirth risk. A population based case-control study was conducted in Nova Scotia and Eastern Ontario, Canada. Estimates of daily exposure to total and specific HAAs were based on household water samples and questionnaire information on water consumption at home and work. The analysis included 112 stillbirth cases and 398 live birth controls. In analysis without adjustment for total THM exposure, a relative risk greater than 2 was observed for an intermediate exposure category for total HAA and dichloroacetic acid measures. After adjustment for total THM exposure, the risk estimates for intermediate exposure categories were diminished, the relative risk associated with the highest category was in the direction of a protective effect, and all confidence intervals included the null value. No association was observed between HAA exposures and stillbirth risk after controlling for THM exposures.
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Cost-utility analysis of stenting versus endarterectomy in the International Carotid Stenting Study.
Morris, Stephen; Patel, Nishma V; Dobson, Joanna; Featherstone, Roland L; Richards, Toby; Luengo-Fernandez, Ramon; Rothwell, Peter M; Brown, Martin M
2016-06-01
The International Carotid Stenting Study was a multicenter randomized trial in which patients with symptomatic carotid artery stenosis were randomly allocated to treatment by carotid stenting or endarterectomy. Economic evidence comparing these treatments is limited and inconsistent. We compared the cost-effectiveness of stenting versus endarterectomy using International Carotid Stenting Study data. We performed a cost-utility analysis estimating mean costs and quality-adjusted life years per patient for both treatments over a five-year time horizon based on resource use data and utility values collected in the trial. Costs of managing stroke events were estimated using individual patient data from a UK population-based study (Oxford Vascular Study). Mean costs per patient (95% CI) were US$10,477 ($9669 to $11,285) in the stenting group (N = 853) and $9669 ($8835 to $10,504) in the endarterectomy group (N = 857). There were no differences in mean quality-adjusted life years per patient (3.247 (3.160 to 3.333) and 3.228 (3.150 to 3.306), respectively). There were no differences in adjusted costs between groups (mean incremental costs for stenting versus endarterectomy $736 (95% CI -$353 to $1826)) or adjusted outcomes (mean quality-adjusted life years gained -0.010 (95% CI -0.117 to 0.097)). The incremental net monetary benefit for stenting versus endarterectomy was not significantly different from zero at the maximum willingness to pay for a quality-adjusted life year commonly used in the UK. Sensitivity analyses showed little uncertainty in these findings. Economic considerations should not affect whether patients with symptomatic carotid stenosis undergo stenting or endarterectomy. © 2016 World Stroke Organization.
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A metabolomic study of low estimated GFR in non-proteinuric type 2 diabetes mellitus.
Ng, D P K; Salim, A; Liu, Y; Zou, L; Xu, F G; Huang, S; Leong, H; Ong, C N
2012-02-01
We carried out a urinary metabolomic study to gain insight into low estimated GFR (eGFR) in patients with non-proteinuric type 2 diabetes. Patients were identified as being non-proteinuric using multiple urinalyses. Cases (n = 44) with low eGFR and controls (n = 46) had eGFR values <60 and ≥60 ml min(-1) 1.73 m(-2), respectively, as calculated using the Modification of Diet in Renal Disease formula. Urine samples were analysed by liquid chromatography/mass spectrometry (LC/MS) and GC/MS. False discovery rates were used to adjust for multiple hypotheses testing, and selection of metabolites that best predicted low eGFR status was achieved using least absolute shrinkage and selection operator logistic regression. Eleven GC/MS metabolites were strongly associated with low eGFR after correction for multiple hypotheses testing (smallest adjusted p value = 2.62 × 10(-14), largest adjusted p value = 3.84 × 10(-2)). In regression analysis, octanol, oxalic acid, phosphoric acid, benzamide, creatinine, 3,5-dimethoxymandelic amide and N-acetylglutamine were selected as the best subset for prediction and allowed excellent classification of low eGFR (AUC = 0.996). In LC/MS, 19 metabolites remained significant after multiple hypotheses testing had been taken into account (smallest adjusted p value = 2.04 × 10(-4), largest adjusted p value = 4.48 × 10(-2)), and several metabolites showed stronger evidence of association relative to the uraemic toxin, indoxyl sulphate (adjusted p value = 3.03 × 10(-2)). The potential effect of confounding on the association between metabolites was excluded. Our study has yielded substantial new insight into low eGFR and provided a collection of potential urinary biomarkers for its detection.
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Legros, S.; Mialet-Serra, I.; Caliman, J.-P.; Siregar, F. A.; Clement-Vidal, A.; Fabre, D.; Dingkuhn, M.
2009-01-01
Background and Aims Despite its simple architecture and small phenotypic plasticity, oil palm has complex phenology and source–sink interactions. Phytomers appear in regular succession but their development takes years, involving long lag periods between environmental influences and their effects on sinks. Plant adjustments to resulting source–sink imbalances are poorly understood. This study investigated oil palm adjustments to imbalances caused by severe fruit pruning. Methods An experiment with two treatments (control and complete fruit pruning) during 22 months in 2006–2008) and six replications per treatment was conducted in Indonesia. Phenology, growth of above-ground vegetative and reproductive organs, leaf morphology, inflorescence sex differentiation, dynamics of non-structural carbohydrate reserves and light-saturated net photosynthesis (Amax) were monitored. Key Results Artificial sink limitation by complete fruit pruning accelerated development rate, resulting in higher phytomer, leaf and inflorescence numbers. Leaf size and morphology remained unchanged. Complete fruit pruning also suppressed the abortion of male inflorescences, estimated to be triggered at about 16 months before bunch maturity. The number of female inflorescences increased after an estimated lag of 24–26 months, corresponding to time from sex differentiation to bunch maturity. The most important adjustment process was increased assimilate storage in the stem, attaining nearly 50 % of dry weight in the stem top, mainly as starch, whereas glucose, which in controls was the most abundant non-structural carbohydrate stored in oil palm, decreased. Conclusions The development rate of oil palm is in part controlled by source–sink relationships. Although increased rate of development and proportion of female inflorescences constituted observed adjustments to sink limitation, the low plasticity of plant architecture (constant leaf size, absence of branching) limited compensatory growth. Non-structural carbohydrate storage was thus the main adjustment process. PMID:19748908
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NASA Astrophysics Data System (ADS)
Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.
2017-12-01
Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.
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Gage, Suzanne H.; Hickman, Matthew; Heron, Jon; Munafò, Marcus R.; Lewis, Glyn; Macleod, John; Zammit, Stanley
2015-01-01
Introduction Substance use is associated with common mental health disorders, but the causal effect of specific substances is uncertain. We investigate whether adolescent cannabis and cigarette use is associated with incident depression and anxiety, while attempting to account for confounding and reverse causation. Methods We used data from ALSPAC, a UK birth cohort study, to investigate associations between cannabis or cigarettes (measured at age 16) and depression or anxiety (measured at age 18), before and after adjustment for pre-birth, childhood and adolescent confounders. Our imputed sample size was 4561 participants. Results Both cannabis (unadjusted OR 1.50, 95% CI 1.26, 1.80) and cigarette use (OR 1.37, 95% CI 1.16, 1.61) increased the odds of developing depression. Adjustment for pre-birth and childhood confounders partly attenuated these relationships though strong evidence of association persisted for cannabis use. There was weak evidence of association for cannabis (fully adjusted OR 1.30, 95% CI 0.98, 1.72) and insufficient evidence for association for cigarette use (fully adjusted OR = 0.97, 95% CI 0.75, 1.24) after mutually adjusting for each other, or for alcohol or other substance use. Neither cannabis nor cigarette use were associated with anxiety after adjustment for pre-birth and childhood confounders. Conclusions Whilst evidence of association between cannabis use and depression persisted after adjusting for pre-term and childhood confounders, our results highlight the difficulties in trying to estimate and interpret independent effects of cannabis and tobacco on psychopathology. Complementary methods are required to robustly examine effects of cannabis and tobacco on psychopathology. PMID:25875443
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Leung, William; Roberts, Vaughan; Gordon, Louisa G; Bullen, Christopher; McRobbie, Hayden; Prapavessis, Harry; Jiang, Yannan; Maddison, Ralph
2017-01-01
In the Fit2Quit randomised controlled trial, insufficiently-active adult cigarette smokers who contacted Quitline for support to quit smoking were randomised to usual Quitline support or to also receive ≤10 face-to-face and telephone exercise-support sessions delivered by trained exercise facilitators over the 24-week trial. This paper aims to determine the cost-effectiveness of an exercise-counselling intervention added to Quitline compared to Quitline alone in the Fit2Quit trial. Within-trial and lifetime cost-effectiveness were assessed. A published Markov model was adapted, with smokers facing increased risks of lung cancer and cardiovascular disease. Over 24 weeks, the incremental programme cost per participant in the intervention was NZ$428 (US$289 or €226; purchasing power parity-adjusted [PPP]). The incremental cost-effectiveness ratio (ICER) for seven-day point prevalence measured at 24-week follow-up was NZ$31,733 (US$21,432 or €16,737 PPP-adjusted) per smoker abstaining. However, for the 52% who adhered to the intervention (≥7 contacts), the ICER for point prevalence was NZ$3,991 (US$2,695 or €2,105 PPP-adjusted). In this adherent subgroup, the Markov model estimated 0.057 and 0.068 discounted quality-adjusted life-year gains over the lifetime of 40-year-old males (ICER: NZ$4,431; US$2,993 or €2,337 PPP-adjusted) and females (ICER: NZ$2,909; US$1,965 or €1,534 PPP-adjusted). The exercise-counselling intervention will only be cost-effective if adherence is a minimum of ≥7 intervention calls, which in turn leads to a sufficient number of quitters for health gains. Australasian Clinical Trials Registry Number ACTRN12609000637246.
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Kamitani, Satoru; Nishimura, Kunihiro; Nakamura, Fumiaki; Kada, Akiko; Nakagawara, Jyoji; Toyoda, Kazunori; Ogasawara, Kuniaki; Ono, Junichi; Shiokawa, Yoshiaki; Aruga, Toru; Miyachi, Shigeru; Nagata, Izumi; Matsuda, Shinya; Miyamoto, Yoshihiro; Iwata, Michiaki; Suzuki, Akifumi; Ishikawa, Koichi B.; Kataoka, Hiroharu; Morita, Kenichi; Kobayashi, Yasuki; Iihara, Koji
2014-01-01
Background Poor outcomes have been reported for stroke patients admitted outside of regular working hours. However, few studies have adjusted for case severity. In this nationwide assessment, we examined relationships between hospital admission time and disabilities at discharge while considering case severity. Methods and Results We analyzed 35 685 acute stroke patients admitted to 262 hospitals between April 2010 and May 2011 for ischemic stroke (IS), intracerebral hemorrhage (ICH), or subarachnoid hemorrhage (SAH). The proportion of disabilities/death at discharge as measured by the modified Rankin Scale (mRS) was quantified. We constructed 2 hierarchical logistic regression models to estimate the effect of admission time, one adjusted for age, sex, comorbidities, and number of beds; and the second adjusted for the effect of consciousness levels and the above variables at admission. The percentage of severe disabilities/death at discharge increased for patients admitted outside of regular hours (22.8%, 27.2%, and 28.2% for working‐hour, off‐hour, and nighttime; P<0.001). These tendencies were significant in the bivariate and multivariable models without adjusting for consciousness level. However, the effects of off‐hour or nighttime admissions were negated when adjusted for consciousness levels at admission (adjusted OR, 1.00 and 0.99; 95% CI, 1.00 to 1.13 and 0.89 to 1.10; P=0.067 and 0.851 for off‐hour and nighttime, respectively, versus working‐hour). The same trend was observed when each stroke subtype was stratified. Conclusions The well‐known off‐hour effect might be attributed to the severely ill patient population. Thus, sustained stroke care that is sufficient to treat severely ill patients during off‐hours is important. PMID:25336463
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Missing continuous outcomes under covariate dependent missingness in cluster randomised trials
Diaz-Ordaz, Karla; Bartlett, Jonathan W
2016-01-01
Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885
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Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.
Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W
2017-06-01
Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.
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An Energy-Aware Runtime Management of Multi-Core Sensory Swarms.
Kim, Sungchan; Yang, Hoeseok
2017-08-24
In sensory swarms, minimizing energy consumption under performance constraint is one of the key objectives. One possible approach to this problem is to monitor application workload that is subject to change at runtime, and to adjust system configuration adaptively to satisfy the performance goal. As today's sensory swarms are usually implemented using multi-core processors with adjustable clock frequency, we propose to monitor the CPU workload periodically and adjust the task-to-core allocation or clock frequency in an energy-efficient way in response to the workload variations. In doing so, we present an online heuristic that determines the most energy-efficient adjustment that satisfies the performance requirement. The proposed method is based on a simple yet effective energy model that is built upon performance prediction using IPC (instructions per cycle) measured online and power equation derived empirically. The use of IPC accounts for memory intensities of a given workload, enabling the accurate prediction of execution time. Hence, the model allows us to rapidly and accurately estimate the effect of the two control knobs, clock frequency adjustment and core allocation. The experiments show that the proposed technique delivers considerable energy saving of up to 45%compared to the state-of-the-art multi-core energy management technique.
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An Energy-Aware Runtime Management of Multi-Core Sensory Swarms
Kim, Sungchan
2017-01-01
In sensory swarms, minimizing energy consumption under performance constraint is one of the key objectives. One possible approach to this problem is to monitor application workload that is subject to change at runtime, and to adjust system configuration adaptively to satisfy the performance goal. As today’s sensory swarms are usually implemented using multi-core processors with adjustable clock frequency, we propose to monitor the CPU workload periodically and adjust the task-to-core allocation or clock frequency in an energy-efficient way in response to the workload variations. In doing so, we present an online heuristic that determines the most energy-efficient adjustment that satisfies the performance requirement. The proposed method is based on a simple yet effective energy model that is built upon performance prediction using IPC (instructions per cycle) measured online and power equation derived empirically. The use of IPC accounts for memory intensities of a given workload, enabling the accurate prediction of execution time. Hence, the model allows us to rapidly and accurately estimate the effect of the two control knobs, clock frequency adjustment and core allocation. The experiments show that the proposed technique delivers considerable energy saving of up to 45%compared to the state-of-the-art multi-core energy management technique. PMID:28837094
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Bennett, G L; Shackelford, S D; Wheeler, T L; King, D A; Casas, E; Smith, T P L
2013-02-01
Genetic markers in casein (CSN1S1) and thyroglobulin (TG) genes have previously been associated with fat distribution in cattle. Determining the nature of these genetic associations (additive, recessive, or dominant) has been difficult, because both markers have small minor allele frequencies in most beef cattle populations. This results in few animals homozygous for the minor alleles. selection to increase the frequencies of the minor alleles for 2 SNP markers in these genes was undertaken in a composite population. The objective was to obtain better estimates of genetic effects associated with these markers and determine if there were epistatic interactions. Selection increased the frequencies of minor alleles for both SNP from <0.30 to 0.45. Bulls (n = 24) heterozygous for both SNP were used in 3 yr to produce 204 steer progeny harvested at an average age of 474 d. The combined effect of the 9 CSN1S1 × TG genotypes was associated with carcass-adjusted fat thickness (P < 0.06) and meat tenderness predicted at the abattoir by visible and near-infrared reflectance spectroscopy (P < 0.04). Genotype did not affect BW from birth through harvest, ribeye area, marbling score, slice shear force, or image-based yield grade (P > 0.10). Additive, dominance, and epistatic SNP association effects were estimated from genotypic effects for adjusted fat thickness and predicted meat tenderness. Adjusted fat thickness showed a dominance association with TG SNP (P < 0.06) and an epistatic additive CSN1S1 × additive TG association (P < 0.03). For predicted meat tenderness, heterozygous TG meat was more tender than meat from either homozygote (P < 0.002). Dominance and epistatic associations can result in different SNP allele substitution effects in populations where SNP have the same linkage disequilibrium with causal mutations but have different frequencies. Although the complex associations estimated in this study would contribute little to within-population selection response, they could be important for marker-assisted management or reciprocal selection schemes.
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Quantifying Overdiagnosis in Cancer Screening: A Systematic Review to Evaluate the Methodology.
Ripping, Theodora M; Ten Haaf, Kevin; Verbeek, André L M; van Ravesteyn, Nicolien T; Broeders, Mireille J M
2017-10-01
Overdiagnosis is the main harm of cancer screening programs but is difficult to quantify. This review aims to evaluate existing approaches to estimate the magnitude of overdiagnosis in cancer screening in order to gain insight into the strengths and limitations of these approaches and to provide researchers with guidance to obtain reliable estimates of overdiagnosis in cancer screening. A systematic review was done of primary research studies in PubMed that were published before January 1, 2016, and quantified overdiagnosis in breast cancer screening. The studies meeting inclusion criteria were then categorized by their methods to adjust for lead time and to obtain an unscreened reference population. For each approach, we provide an overview of the data required, assumptions made, limitations, and strengths. A total of 442 studies were identified in the initial search. Forty studies met the inclusion criteria for the qualitative review. We grouped the approaches to adjust for lead time in two main categories: the lead time approach and the excess incidence approach. The lead time approach was further subdivided into the mean lead time approach, lead time distribution approach, and natural history modeling. The excess incidence approach was subdivided into the cumulative incidence approach and early vs late-stage cancer approach. The approaches used to obtain an unscreened reference population were grouped into the following categories: control group of a randomized controlled trial, nonattenders, control region, extrapolation of a prescreening trend, uninvited groups, adjustment for the effect of screening, and natural history modeling. Each approach to adjust for lead time and obtain an unscreened reference population has its own strengths and limitations, which should be taken into consideration when estimating overdiagnosis. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Monthly stumpage prices for the Pacific Northwest.
Richard W. Haynes
1991-01-01
Seasonal variation is found in monthly stumpage price data. Seasonal adjustments indicate that monthly adjustments improve the utility of estimates of monthly stumpage prices. Comparisons of adjusted and unadjusted prices suggest that the unadjusted price series are reasonably robust.
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Ezoe, Satoshi; Morooka, Takeo; Noda, Tatsuya; Sabin, Miriam Lewis; Koike, Soichi
2012-01-01
Men who have sex with men (MSM) are one of the groups most at risk for HIV infection in Japan. However, size estimates of MSM populations have not been conducted with sufficient frequency and rigor because of the difficulty, high cost and stigma associated with reaching such populations. This study examined an innovative and simple method for estimating the size of the MSM population in Japan. We combined an internet survey with the network scale-up method, a social network method for estimating the size of hard-to-reach populations, for the first time in Japan. An internet survey was conducted among 1,500 internet users who registered with a nationwide internet-research agency. The survey participants were asked how many members of particular groups with known population sizes (firepersons, police officers, and military personnel) they knew as acquaintances. The participants were also asked to identify the number of their acquaintances whom they understood to be MSM. Using these survey results with the network scale-up method, the personal network size and MSM population size were estimated. The personal network size was estimated to be 363.5 regardless of the sex of the acquaintances and 174.0 for only male acquaintances. The estimated MSM prevalence among the total male population in Japan was 0.0402% without adjustment, and 2.87% after adjusting for the transmission error of MSM. The estimated personal network size and MSM prevalence seen in this study were comparable to those from previous survey results based on the direct-estimation method. Estimating population sizes through combining an internet survey with the network scale-up method appeared to be an effective method from the perspectives of rapidity, simplicity, and low cost as compared with more-conventional methods.
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Health effects of metropolitan traffic-related air pollutants on street vendors
NASA Astrophysics Data System (ADS)
Kongtip, P.; Thongsuk, W.; Yoosook, W.; Chantanakul, S.
Traffic-related air pollutants are a commonly important source of air pollution. Research on the effects of multiple traffic-related air pollutants on street vendors is scarce. This study evaluated the health effect of traffic-related air pollutants in street vendors. It was designed as a panel study, covering 61 d of data collection, on the daily concentration of air pollutants and daily percentage of respiratory and other health symptoms reported. An adjusted odds ratio was used to estimate the risk of developing respiratory and other adverse health symptoms for street vendors exposed to multiple air pollutants, fine particulate (PM 2.5), nitrogen dioxide (NO 2), ozone (O 3), carbon monoxide (CO) and total volatile organic chemicals (VOCs), after controlling for confounding factors. In the first model, significant associations were found with the adjusted odds ratios of 1.022 and 1.027 for eye irritation and dizziness for PM 2.5 respectively. The adjusted odds ratio of total VOCs was 1.381 for phlegm, 4.840 for chest tightness and 1.429 for upper respiratory symptoms, and the adjusted odds ratio for CO was 1.748 for a sore throat and 1.880 for a cold and 1.655 for a cough. In the second model, the effect of PM 2.5, total VOCs and CO gave a slightly lower effect with the symptoms. The results clearly show the health effects of traffic-related air pollutants on street vendors, and imply suggestions about how to reduce exposure of street vendors.
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Estimation of the transmissivity of thin leaky-confined aquifers from single-well pumping tests
NASA Astrophysics Data System (ADS)
Worthington, Paul F.
1981-01-01
Data from the quasi-equilibrium phases of a step-drawdown test are used to evaluate the coefficient of non-linear head losses subject to the assumption of a constant effective well radius. After applying a well-loss correction to the observed drawdowns of the first step, an approximation method is used to estimate a pseudo-transmissivity of the aquifer from a single value of time-variant drawdown. The pseudo-transmissivities computed for each of a sequence of values of time pass through a minimum when there is least manifestation of casing-storage and leakage effects, phenomena to which pumping-test data of this kind are particularly susceptible. This minimum pseudo-transmissivity, adjusted for partial penetration effects where appropriate, constitutes the best possible estimate of aquifer transmissivity. The ease of application of the overall procedure is illustrated by a practical example.
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ERIC Educational Resources Information Center
Green, Leonard; Myerson, Joel; Shah, Anuj K.; Estle, Sara J.; Holt, Daniel D.
2007-01-01
The current experiment examined whether adjusting-amount and adjusting-delay procedures provide equivalent measures of discounting. Pigeons' discounting on the two procedures was compared using a within-subject yoking technique in which the indifference point (number of pellets or time until reinforcement) obtained with one procedure determined…
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Hashimoto, Tomomi; Takase, Hiroyuki; Okado, Tateo; Sugiura, Tomonori; Yamashita, Sumiyo; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki
2016-08-01
The close association between dietary salt and hypertension is well established. However, previous studies generally assessed salt intake without adjustment for body weight. Herein, we investigated the significance of body weight-adjusted salt intake in the general population. The present cross-sectional study included 7629 participants from our yearly physical checkup program, and their salt intake was assessed using a spot urine test to estimate 24-hour urinary salt excretion. Total salt intake increased with increasing body weight. Body weight-adjusted salt intake was greater in participants with hypertension than in those without hypertension. Systolic blood pressure, estimated glomerular filtration rate, and urinary albumin were independently correlated with body weight-adjusted salt intake after adjustment for possible cardiovascular risk factors. Excessive body weight-adjusted salt intake could be related to an increase in blood pressure and hypertensive organ damage. Adjustment for body weight might therefore provide clinically important information when assessing individual salt intake. Copyright © 2016 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.
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Kang, Leni; Zhang, Shaokai; Zhao, Fanghui; Qiao, Youlin
2014-03-01
To evaluate and adjust the verification bias existed in the screening or diagnostic tests. Inverse-probability weighting method was used to adjust the sensitivity and specificity of the diagnostic tests, with an example of cervical cancer screening used to introduce the Compare Tests package in R software which could be implemented. Sensitivity and specificity calculated from the traditional method and maximum likelihood estimation method were compared to the results from Inverse-probability weighting method in the random-sampled example. The true sensitivity and specificity of the HPV self-sampling test were 83.53% (95%CI:74.23-89.93)and 85.86% (95%CI: 84.23-87.36). In the analysis of data with randomly missing verification by gold standard, the sensitivity and specificity calculated by traditional method were 90.48% (95%CI:80.74-95.56)and 71.96% (95%CI:68.71-75.00), respectively. The adjusted sensitivity and specificity under the use of Inverse-probability weighting method were 82.25% (95% CI:63.11-92.62) and 85.80% (95% CI: 85.09-86.47), respectively, whereas they were 80.13% (95%CI:66.81-93.46)and 85.80% (95%CI: 84.20-87.41) under the maximum likelihood estimation method. The inverse-probability weighting method could effectively adjust the sensitivity and specificity of a diagnostic test when verification bias existed, especially when complex sampling appeared.
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Aune, Dagfinn; Sen, Abhijit; Vatten, Lars J
2017-04-07
A history of hypertension has been associated with increased risk of endometrial cancer in several studies, but the results have not been consistent. We conducted a systematic review and meta-analysis of case-control and cohort studies to clarify the association between hypertension and endometrial cancer risk. PubMed and Embase databases were searched up to 27 th of February 2016. Prospective and case-control studies which reported adjusted relative risk estimates and 95% confidence intervals of endometrial cancer associated with a hypertension diagnosis were included. Summary relative risks were estimated using a random effects model. Nineteen case-control studies and 6 cohort studies were included. The summary RR was 1.61 (95% CI: 1.41-1.85, I 2 = 86%) for all studies, 1.73 (95% CI: 1.45-2.06, I 2 = 89%) for case-control studies and 1.32 (95% CI: 1.12-1.56, I 2 = 47%) for cohort studies. The association between hypertension and endometrial cancer was weaker, but still significant, among studies with adjustment for smoking, BMI, oral contraceptive use, and parity, compared to studies without such adjustment. This meta-analysis suggest an increased risk of endometrial cancer among patients with hypertension, however, further studies with more comprehensive adjustments for confounders are warranted to clarify the association.
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2014-01-01
Background This study examines the cost effectiveness of group follow-up after participation in the Dose Adjustment for Normal Eating (DAFNE) structured education programme for type 1 diabetes. Methods Economic evaluation conducted alongside a cluster randomised controlled trial involving 437 adults with type 1 diabetes in Ireland. Group follow-up involved two group education ‘booster’ sessions post-DAFNE. Individual follow-up involved two standard one-to-one hospital clinic visits. Incremental costs, quality-adjusted life years (QALYs) gained and cost effectiveness were estimated at 18 months. Uncertainty was explored using sensitivity analysis and by estimating cost effectiveness acceptability curves. Results Group follow-up was associated with a mean reduction in QALYs gained of 0.04 per patient (P value, 0.052; 95% CI, −0.08 to 0.01, intra-class correlation (ICC), 0.033) and a mean reduction in total healthcare costs of €772 (P value, 0.020; 95% CI, −1,415 to −128: ICC, 0.016) per patient. At alternative threshold values of €5,000, €15,000, €25,000, €35,000, and €45,000, the probability of group follow-up being cost effective was estimated to be 1.000, 0.762, 0.204, 0.078, and 0.033 respectively. Conclusions The results do not support implementation of group follow-up as the sole means of follow-up post-DAFNE. Given the reported cost savings, future studies should explore the cost effectiveness of alternative models of group care for diabetes. Trial registration Current Controlled Trials ISRCTN79759174 (assigned: 9 February 2007). PMID:24927851
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Harrison, Mark; Marra, Carlo; Shojania, Kam; Bansback, Nick
2015-10-01
There is a concern that cost-effectiveness analysis using quality-adjusted life years does not capture all valuable benefits of treatments. The objective of this study was to determine the value society places on aspects of RA treatment to inform policymaking. A discrete choice experiment was administered to a representative sample of the Canadian general population. The discrete choice experiment, developed using focus groups, had seven attributes (route and frequency of administration, chance of benefit, chance of serious and minor side effects, confidence in evidence and life expectancy). A conditional logit regression model was used to estimate the significance and relative importance of attributes in influencing preferences on the quality-adjusted life years scale. Responses from 733 respondents who provided rational responses were analysed. Six attribute levels within four attributes significantly influenced preferences for treatments: a willingness to trade a year of life expectancy over a 10-year period to increase the probability of benefiting from treatment, or two-thirds of a year to reduce minor or serious side effects to the lowest level or improve the confidence in benefit/side-effect estimates. There was also some evidence of a preference for oral drug delivery, though a subgroup analysis suggested this preference was restricted to injection-naive respondents. Our results suggest society values the degree of confidence in the estimates of risks and benefits of RA treatments and the route of administration, as well as benefits and side effects. This study provides important evidence to policymakers determining the cost-effectiveness of treatments in arthritis. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Saunders, James E; Barrs, David M; Gong, Wenfeng; Wilson, Blake S; Mojica, Karen; Tucci, Debara L
2015-09-01
Cochlear implantation (CI) is a common intervention for severe-to-profound hearing loss in high-income countries, but is not commonly available to children in low resource environments. Owing in part to the device costs, CI has been assumed to be less economical than deaf education for low resource countries. The purpose of this study is to compare the cost effectiveness of the two interventions for children with severe-to-profound sensorineural hearing loss (SNHL) in a model using disability adjusted life years (DALYs). Cost estimates were derived from published data, expert opinion, and known costs of services in Nicaragua. Individual costs and lifetime DALY estimates with a 3% discounting rate were applied to both two interventions. Sensitivity analysis was implemented to evaluate the effect on the discounted cost of five key components: implant cost, audiology salary, speech therapy salary, number of children implanted per year, and device failure probability. The costs per DALY averted are $5,898 and $5,529 for CI and deaf education, respectively. Using standards set by the WHO, both interventions are cost effective. Sensitivity analysis shows that when all costs set to maximum estimates, CI is still cost effective. Using a conservative DALY analysis, both CI and deaf education are cost-effective treatment alternatives for severe-to-profound SNHL. CI intervention costs are not only influenced by the initial surgery and device costs but also by rehabilitation costs and the lifetime maintenance, device replacement, and battery costs. The major CI cost differences in this low resource setting were increased initial training and infrastructure costs, but lower medical personnel and surgery costs.
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Tzivian, Lilian; Jokisch, Martha; Winkler, Angela; Weimar, Christian; Hennig, Frauke; Sugiri, Dorothea; Soppa, Vanessa J; Dragano, Nico; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Hoffmann, Barbara
2017-06-01
Adverse effects of traffic-related air pollution (AP) and noise on cognitive functions have been proposed, but little is known about their interactions and the combined effect of co-exposure. Cognitive assessment was completed by 4086 participants of the population-based Heinz Nixdorf Recall cohort study using five neuropsychological subtests and an additively calculated global cognitive score (GCS). We assessed long-term residential concentrations for size-fractioned particulate matter (PM) and nitrogen oxides with land use regression. Road traffic noise (weighted 24-h (L DEN ) and night-time (L NIGHT ) means) was assessed according to the EU directive 2002/49/EC. Linear regression models adjusted for individual-level characteristics were calculated to estimate effect modification of associations between AP and noise with cognitive function. We used multiplicative interaction terms and categories of single or double high exposure, dichotomizing the potential effect modifier at the median (AP) or at an a priori defined threshold (road traffic noise). In fully adjusted models, high noise exposure increased the association of AP with cognitive function. For example, for an interquartile range increase of PM 2.5 (IQR 1.43), association s with GCS were: estimate (β)=-0.16 [95% confidence interval: -0.33; 0.01] and β=-0.48 [-0.72; -0.23] for low and high L DEN , respectively. The association of noise with GCS was restricted to highly AP-exposed participants. We observed stronger negative associations in those participants with double exposure compared to the addition of effect estimates of each single exposure. Our study suggests that AP and road traffic noise might act synergistically on cognitive function in adults. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Herring, William; Pearson, Isobel; Purser, Molly; Nakhaipour, Hamid Reza; Haiderali, Amin; Wolowacz, Sorrel; Jayasundara, Kavisha
2016-01-01
Our objective was to estimate the cost effectiveness of ofatumumab plus chlorambucil (OChl) versus chlorambucil in patients with chronic lymphocytic leukaemia for whom fludarabine-based therapies are considered inappropriate from the perspective of the publicly funded healthcare system in Canada. A semi-Markov model (3-month cycle length) used survival curves to govern progression-free survival (PFS) and overall survival (OS). Efficacy and safety data and health-state utility values were estimated from the COMPLEMENT-1 trial. Post-progression treatment patterns were based on clinical guidelines, Canadian treatment practices and published literature. Total and incremental expected lifetime costs (in Canadian dollars [$Can], year 2013 values), life-years and quality-adjusted life-years (QALYs) were computed. Uncertainty was assessed via deterministic and probabilistic sensitivity analyses. The discounted lifetime health and economic outcomes estimated by the model showed that, compared with chlorambucil, first-line treatment with OChl led to an increase in QALYs (0.41) and total costs ($Can27,866) and to an incremental cost-effectiveness ratio (ICER) of $Can68,647 per QALY gained. In deterministic sensitivity analyses, the ICER was most sensitive to the modelling time horizon and to the extrapolation of OS treatment effects beyond the trial duration. In probabilistic sensitivity analysis, the probability of cost effectiveness at a willingness-to-pay threshold of $Can100,000 per QALY gained was 59 %. Base-case results indicated that improved overall response and PFS for OChl compared with chlorambucil translated to improved quality-adjusted life expectancy. Sensitivity analysis suggested that OChl is likely to be cost effective subject to uncertainty associated with the presence of any long-term OS benefit and the model time horizon.
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Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-22
... estimated cost of the case exceeds the adjusted outlier threshold. We calculate the adjusted outlier... to 80 percent of the difference between the estimated cost of the case and the outlier threshold. In... Federal Prospective Payment Rates VI. Update to Payments for High-Cost Outliers under the IRF PPS A...
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Consistency between satellite-derived and modeled estimates of the direct aerosol effect.
Myhre, Gunnar
2009-07-10
In the Intergovernmental Panel on Climate Change Fourth Assessment Report, the direct aerosol effect is reported to have a radiative forcing estimate of -0.5 Watt per square meter (W m(-2)), offsetting the warming from CO2 by almost one-third. The uncertainty, however, ranges from -0.9 to -0.1 W m(-2), which is largely due to differences between estimates from global aerosol models and observation-based estimates, with the latter tending to have stronger (more negative) radiative forcing. This study demonstrates consistency between a global aerosol model and adjustment to an observation-based method, producing a global and annual mean radiative forcing that is weaker than -0.5 W m(-2), with a best estimate of -0.3 W m(-2). The physical explanation for the earlier discrepancy is that the relative increase in anthropogenic black carbon (absorbing aerosols) is much larger than the overall increase in the anthropogenic abundance of aerosols.
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Neilson, Heather K; Farris, Megan S; Stone, Chelsea R; Vaska, Marcus M; Brenner, Darren R; Friedenreich, Christine M
2017-03-01
Physical inactivity increases postmenopausal and possibly premenopausal breast cancer risk, although different biologic mechanisms are proposed. Our primary objective was to estimate breast cancer risk associated with high versus low levels of moderate-vigorous recreational activity, separately for premenopausal and postmenopausal women. We conducted a systematic review of literature published to July 2015. Included reports were cohort or case-control studies relating moderate-vigorous recreational physical activity (metabolic equivalent ≥3.0) to breast cancer incidence, exclusively (≥90%) in premenopausal or postmenopausal women. We appraised study quality and performed meta-analyses using random effects modeling. Subgroup meta-analyses were based on tumor subtype, race, body mass index, parity, hormone therapy use, family history of cancer, and statistical adjustment for body fatness. Dose-response relations were examined. Pooled relative risks (RRs, 95% CI) for women with higher versus lower levels of moderate-vigorous recreational activity were RR = 0.80 (0.74-0.87) and RR = 0.79 (0.74-0.84) for premenopausal (43 studies) and postmenopausal (58 studies) breast cancer, respectively, with high heterogeneity. Inverse associations were weaker among postmenopausal cohort studies (RR = 0.90 [0.85-0.95]) and studies that statistically adjusted for nonrecreational (eg, occupational, household) activity (RR = 0.91 [0.77-1.06] premenopausal, RR = 0.96 [0.86-1.08] postmenopausal). Risk estimates with versus without body fatness adjustment did not vary by menopause status, although other subgroup effects were menopause-dependent. Among studies of overweight/obese women, there was an inverse association with postmenopausal but not premenopausal breast cancer (RR = 0.88 [0.82-0.95] and RR = 0.99 [0.98-1.00], respectively). Dose-response curves were generally nonlinear. Although risk estimates may be similar for premenopausal and postmenopausal breast cancer, subgroup effects may be menopause-dependent.
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Deger, Leylâ; Plante, Céline; Jacques, Louis; Goudreau, Sophie; Perron, Stéphane; Hicks, John; Kosatsky, Tom; Smargiassi, Audrey
2012-01-01
BACKGROUND: Little attention has been devoted to the effects on children’s respiratory health of exposure to sulphur dioxide (SO2) in ambient air from local industrial emissions. Most studies on the effects of SO2 have assessed its impact as part of the regional ambient air pollutant mix. OBJECTIVE: To examine the association between exposure to stack emissions of SO2 from petroleum refineries located in Montreal’s (Quebec) east-end industrial complex and the prevalence of active asthma and poor asthma control among children living nearby. METHODS: The present cross-sectional study used data from a respiratory health survey of Montreal children six months to 12 years of age conducted in 2006. Of 7964 eligible households that completed the survey, 842 children between six months and 12 years of age lived in an area impacted by refinery emissions. Ambient SO2 exposure levels were estimated using dispersion modelling. Log-binomial regression models were used to estimate crude and adjusted prevalence ratios (PRs) and 95% CIs for the association between yearly school and residential SO2 exposure estimates and asthma outcomes. Adjustments were made for child’s age, sex, parental history of atopy and tobacco smoke exposure at home. RESULTS: The adjusted PR for the association between active asthma and SO2 levels was 1.14 (95% CI 0.94 to 1.39) per interquartile range increase in modelled annual SO2. The effect on poor asthma control was greater (PR=1.39 per interquartile range increase in modelled SO2 [95% CI 1.00 to 1.94]). CONCLUSIONS: Results of the present study suggest a relationship between exposure to refinery stack emissions of SO2 and the prevalence of active and poor asthma control in children who live and attend school in proximity to refineries. PMID:22536578
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Phantom-derived estimation of effective dose equivalent from X rays with and without a lead apron.
Mateya, C F; Claycamp, H G
1997-06-01
Organ dose equivalents were measured in a humanoid phantom in order to estimate effective dose equivalent (H(E)) and effective dose (E) from low-energy x rays and in the presence or absence of a protective lead apron. Plane-parallel irradiation conditions were approximated using direct x-ray beams of 76 and 104 kVp and resulting dosimetry data was adjusted to model exposures conditions in fluoroscopy settings. Values of H(E) and E estimated under-shielded conditions were compared to the results of several recent studies that used combinations of measured and calculated dosimetry to model exposures to radiologists. While the estimates of H(E) and E without the lead apron were within 0.2 to 20% of expected values, estimates based on personal monitors worn at the (phantom) waist (underneath the apron) underestimated either H(E) or E while monitors placed at the neck (above the apron) significantly overestimated both quantities. Also, the experimentally determined H(E) and E were 1.4 to 3.3 times greater than might be estimated using recently reported "two-monitor" algorithms for the estimation of effective dose quantities. The results suggest that accurate estimation of either H(E) or E from personal monitors under conditions of partial body exposures remains problematic and is likely to require the use of multiple monitors.
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Estimating a Change from TRICARE to Commercial Insurance Plans.
Murray, Carla T; Schmit, Matthew
2018-03-14
We estimate the effect on health care spending of an option to change TRICARE. Under the option, which is based on a proposal made by the Military Compensation and Retirement Modernization Commission (MCRMC), most beneficiaries could choose from a range of commercial health networks instead of the current TRICARE plans. Military treatment facilities would become network providers under the commercial plans. We used data from the Department of Defense (DoD) to estimate the cost of providing the current health care benefit to working-age retirees and their dependents and survivors, and active duty family members. We then adjusted those data to estimate what the private insurance premiums would be for those groups. Greater details about the methodology can be found in earlier work by the Congressional Budget Office. Because payments by TRICARE to physicians and hospitals are tied to payments made by Medicare, we used the information from studies that compare Medicare payment rates to rates paid to doctors and hospitals by private insurance to estimate what it would cost private insurers to provide approximately the same level of care, with adjustments to account for the higher out-of-pocket costs that beneficiaries would pay under the option. We also made adjustments to account for the possibility that many beneficiaries would decrease their use of the MTFs in favor of private providers, which could increase the overall costs of DoD. We then estimated that increasing the cost sharing to a level found in popular civilian plans would lower overall demand for services by about 10% for military retiree households and about 18% for active duty family members. We estimated that DoD would pay subsidies to retain about half of the excess capacity created by beneficiaries switching their care from MTFs to the private sector. Evaluated at the midpoint of the ranges, the net effect on DoD's budget would be approximately $0, we estimate, but costs could fall in a likely range from about $3 billion in annual savings to about $3 billion in annual costs. Thus, the MCRMC estimate of $3.2 billion implicitly assumed that no excess capacity would be retained by MTFs. In 2031, under current law, the average retiree family is expected to cost the federal government about $24,100 (in 2017 dollars) and that family's out-of-pocket costs are expected to amount to about $1,900. The option would reduce the government's costs for the average retiree family to $23,500, but retiree families could see their out-of-pocket costs rise to $7,500 per year. This article outlined a method of identifying two particular sources of that uncertainty: the extent to which people will receive care outside of MTFs and the extent to which the MTFs can adjust to reductions in demand. For one particular option, we demonstrate that the potential savings from changing the system depends on increasing the share of costs paid by beneficiaries - particularly working-age retirees - and on DoD's ability to reduce excess capacity in the system.
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Howland, Renata E; Angley, Meghan; Won, Sang Hee; Wilcox, Wendy; Searing, Hannah; Tsao, Tsu-Yu
2018-02-01
To quantify the average and total hospital delivery costs associated with severe maternal morbidity in excess of nonsevere maternal morbidity deliveries over a 5-year period in New York City adjusting for other sociodemographic and clinical factors. We conducted a population-based cross-sectional study using linked birth certificates and hospital discharge data for New York City deliveries from 2008 to 2012. Severe maternal morbidity was defined using a published algorithm of International Classification of Diseases, 9 Revision, Clinical Modification disease and procedure codes. Hospital costs were estimated by converting hospital charges using factors specific to each year and hospital and to each diagnosis. These estimates approximate what it costs the hospital to provide services (excluding professional fees) and were used in all subsequent analyses. To estimate adjusted mean costs associated with severe maternal morbidity, we used multivariable regression models with a log link, gamma distribution, robust standard errors, and hospital fixed effects, controlling for age, race and ethnicity, neighborhood poverty, primary payer, number of deliveries, method of delivery, comorbidities, and year. We used the adjusted mean cost to determine the average and total hospital delivery costs associated with severe maternal morbidity in excess of nonsevere maternal morbidity deliveries from 2008 to 2012. Approximately 2.3% (n=13,502) of all New York City delivery hospitalizations were complicated by severe maternal morbidity. Compared with nonsevere maternal morbidity deliveries, these hospitalizations were clinically complicated, required more and intensive clinical services, and had a longer stay in the hospital. The average cost of delivery with severe maternal morbidity was $14,442 (95% CI $14,128-14,756), compared with $7,289 (95% CI $7,276-7,302) among deliveries without severe maternal morbidity. After adjusting for other factors, the difference between deliveries with and without severe maternal morbidity remained high ($6,126). Over 5 years, this difference resulted in approximately $83 million in total excess costs (13,502×$6,126). Severe maternal morbidity nearly doubled the cost of delivery above and beyond other drivers of cost, resulting in tens of millions of excess dollars spent in the health care system in New York City. These findings can be used to demonstrate the burden of severe maternal morbidity and evaluate the cost-effectiveness of interventions to improve maternal health.
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Hagel, B E; Romanow, N T R; Morgunov, N; Embree, T; Couperthwaite, A B; Voaklander, D; Rowe, B H
2014-04-01
Little is known about the effectiveness of visibility aids (VAs; e.g., reflectors, lights, fluorescent clothing) in reducing the risk of a bicyclist-motor-vehicle (MV) collision. To determine if VAs reduce the risk of a bicyclist-MV collision. Cases were bicyclists struck by a MV and assessed at Calgary and Edmonton, Alberta, Canada, emergency departments (EDs) from May 2008 to October 2010. Controls were bicyclists with non-MV injuries. Participants were interviewed about their personal and injury characteristics, including use of VAs. Injury information was collected from charts. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for VAs during daylight and dark conditions, and adjusted for confounders using logistic regression. Missing values were imputed using chained equations and adjusted OR estimates from the imputed data were calculated. There were 2403 injured bicyclists including 278 cases. After adjusting for age, sex, type of bicycling (commuting vs. recreational) and bicyclist speed, white compared with black (OR 0.52; 95% CI 0.28, 0.95), and bicyclist self-reported light compared with dark coloured (OR 0.67; 95% CI 0.49, 0.92) upper body clothing reduced the odds of a MV collision during daylight. After imputing missing values, white compared with black (OR 0.57; 95% CI: 0.32, 0.99) and bicyclist self-reported light compared with dark coloured (OR 0.71; 95% CI 0.52, 0.97) upper body clothing remained protective against MV collision in daylight conditions. During dark conditions, crude estimates indicated that reflective clothing or other items, red/orange/yellow front upper body clothing compared with black, fluorescent clothing, headlights and tail lights were estimated to increase the odds of a MV collision. An imputed adjusted analysis revealed that red/orange/yellow front upper body clothing colour (OR 4.11; 95% CI 1.06, 15.99) and tail lights (OR 2.54; 95% CI: 1.06, 6.07) remained the only significant risk factors for MV collisions. One or more visibility aids reduced the odds of a bicyclist MV collision resulting in hospitalization. Bicyclist clothing choice may be important in reducing the risk of MV collision. The protective effect of visibility aids varies based on light conditions, and non-bicyclist risk factors also need to be considered. Copyright © 2014 Elsevier Ltd. All rights reserved.
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The cost-effectiveness of multi-purpose HIV and pregnancy prevention technologies in South Africa.
Quaife, Matthew; Terris-Prestholt, Fern; Eakle, Robyn; Cabrera Escobar, Maria A; Kilbourne-Brook, Maggie; Mvundura, Mercy; Meyer-Rath, Gesine; Delany-Moretlwe, Sinead; Vickerman, Peter
2018-03-01
A number of antiretroviral HIV prevention products are efficacious in preventing HIV infection. However, the sexual and reproductive health needs of many women extend beyond HIV prevention, and research is ongoing to develop multi-purpose prevention technologies (MPTs) that offer dual HIV and pregnancy protection. We do not yet know if these products will be an efficient use of constrained health resources. In this paper, we estimate the cost-effectiveness of combinations of candidate multi-purpose prevention technologies (MPTs), in South Africa among general population women and female sex workers (FSWs). We combined a cost model with a static model of product impact based on incidence data in South Africa to estimate the cost-effectiveness of five candidate co-formulated or co-provided MPTs: oral PrEP, intravaginal ring, injectable ARV, microbicide gel and SILCS diaphragm used in concert with gel. We accounted for the preferences of end-users by predicting uptake using a discrete choice experiment (DCE). Product availability and protection were systematically varied in five potential rollout scenarios. The impact model estimated the number of infections averted through decreased incidence due to product use over one year. The comparator for each scenario was current levels of male condom use, while a health system perspective was used to estimate discounted lifetime treatment costs averted per HIV infection. Product benefit was estimated in disability-adjusted life years (DALYs) averted. Benefits from contraception were incorporated through adjusting the uptake of these products based on the DCE and through estimating the costs averted from avoiding unwanted pregnancies. We explore the additional impact of STI protection through increased uptake in a sensitivity analysis. At central incidence rates, all single- and multi-purpose scenarios modelled were cost-effective among FSWs and women aged 16-24, at a governmental willingness-to-pay threshold of $1175/DALY averted (range: $214-$810/DALY averted among non-dominant scenarios), however, none were cost-effective among women aged 25-49 (minimum $1706/DALY averted). The cost-effectiveness of products improved with additional protection from pregnancy. Estimates were sensitive to variation in incidence assumptions, but robust to other parameters. To the best of our knowledge, this is the first study to estimate the cost-effectiveness of a range of potential MPTs; suggesting that MPTs will be cost-effective among higher incidence FSWs or young women, but not among lower incidence older women. More work is needed to make attractive MPTs available to potential users who could use them effectively. © 2018 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.
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Chin, Ho Jun; Kim, Dong Ki; Park, Jung Hwan; Shin, Sung Joon; Lee, Sang Ho; Choi, Bum Soon; Kim, Suhnggwon; Lim, Chun Soo
2015-01-01
The aim of this study was to determine the role of protein intake on proteinuria in chronic kidney disease (CKD), as it is presently not conclusive. This is a subanalysis of data from an open-label, case-controlled, randomized clinical trial on education about low-salt diets (NCT01552954). We estimated the urine excretion rate of parameters in a day, adjusted by using the equation for estimating urine creatinine excretion, and analyzed the effect of urine urea nitrogen (UUN), as well as estimating protein intake on the level of albuminuria in hypertensive patients with chronic kidney disease. Among 174 participants from whom complete 24-h urine specimens were collected, the estimates from the Tanaka equation resulted in the highest accuracy for the urinary excretion rate of creatinine, sodium, albumin, and UUN. Among 227 participants, the baseline value of estimated urine albumin excretion (eUalb) was positively correlated with the estimated UUN (eUUN) or protein intake according to eUUN (P = 0.012 and P = 0.038, respectively). We were able to calculate the ratios of eUalb and eUUN in 221 participants and grouped them according to the ratio of eUUN during 16-wk trial period. The proportion of patients that achieved a decrement of eUalb ≥25% during 16 wk with an angiotensin II type I receptor blocker (ARB) medication was 80% (24 of 30) in group 1, with eUUN ratio ≤-25%; 82.2% (111 of 135) in group 2, with eUUN ratio between -25% and 25%; and 66.1% (37 and 56) in group 3, with eUUN ratio ≥25% (P = 0.048). The probability of a decrease in albuminuria with ARB treatment was lower in patients with an increase of eUUN or protein intake during the 16 wk of ARB treatment, as observed in multiple logistic regression analysis as well. The estimated urine urea excretion rate showed a positive association with the level of albuminuria in hypertensive patients with chronic kidney disease. The increase of eUUN excretion ameliorated the antiproteinuric effect of ARB. Copyright © 2015 Elsevier Inc. All rights reserved.
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Instrumental variables as bias amplifiers with general outcome and confounding.
Ding, P; VanderWeele, T J; Robins, J M
2017-06-01
Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is unconfounded conditional on the observed covariates. It is often believed that the more covariates we condition on, the more plausible this unconfoundedness assumption is. This belief has had a huge impact on practical causal inference, suggesting that we should adjust for all pretreatment covariates. However, when there is unmeasured confounding between the treatment and outcome, estimators adjusting for some pretreatment covariate might have greater bias than estimators without adjusting for this covariate. This kind of covariate is called a bias amplifier, and includes instrumental variables that are independent of the confounder, and affect the outcome only through the treatment. Previously, theoretical results for this phenomenon have been established only for linear models. We fill in this gap in the literature by providing a general theory, showing that this phenomenon happens under a wide class of models satisfying certain monotonicity assumptions. We further show that when the treatment follows an additive or multiplicative model conditional on the instrumental variable and the confounder, these monotonicity assumptions can be interpreted as the signs of the arrows of the causal diagrams.
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Incorporating Neighborhood Choice in a Model of Neighborhood Effects on Income.
van Ham, Maarten; Boschman, Sanne; Vogel, Matt
2018-05-09
Studies of neighborhood effects often attempt to identify causal effects of neighborhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research, and it has been argued that estimates of neighborhood effects are biased because people nonrandomly select into neighborhoods based on their preferences, income, and the availability of alternative housing. We propose a two-step framework to disentangle selection processes in the relationship between neighborhood deprivation and earnings. We model neighborhood selection using a conditional logit model, from which we derive correction terms. Driven by the recognition that most households prefer certain types of neighborhoods rather than specific areas, we employ a principle components analysis to reduce these terms into eight correction components. We use these to adjust parameter estimates from a model of subsequent neighborhood effects on individual income for the unequal probability that a household chooses to live in a particular type of neighborhood. We apply this technique to administrative data from the Netherlands. After we adjust for the differential sorting of households into certain types of neighborhoods, the effect of neighborhood income on individual income diminishes but remains significant. These results further emphasize that researchers need to be attuned to the role of selection bias when assessing the role of neighborhood effects on individual outcomes. Perhaps more importantly, the persistent effect of neighborhood deprivation on subsequent earnings suggests that neighborhood effects reflect more than the shared characteristics of neighborhood residents: place of residence partially determines economic well-being.
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ESTIMATING TREATMENT EFFECTS ON HEALTHCARE COSTS UNDER EXOGENEITY: IS THERE A ‘MAGIC BULLET’?
Polsky, Daniel; Manning, Willard G.
2011-01-01
Methods for estimating average treatment effects, under the assumption of no unmeasured confounders, include regression models; propensity score adjustments using stratification, weighting, or matching; and doubly robust estimators (a combination of both). Researchers continue to debate about the best estimator for outcomes such as health care cost data, as they are usually characterized by an asymmetric distribution and heterogeneous treatment effects,. Challenges in finding the right specifications for regression models are well documented in the literature. Propensity score estimators are proposed as alternatives to overcoming these challenges. Using simulations, we find that in moderate size samples (n= 5000), balancing on propensity scores that are estimated from saturated specifications can balance the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates. Therefore, unlike regression model, even if a formal model for outcomes is not required, propensity score estimators can be inefficient at best and biased at worst for health care cost data. Our simulation study, designed to take a ‘proof by contradiction’ approach, proves that no one estimator can be considered the best under all data generating processes for outcomes such as costs. The inverse-propensity weighted estimator is most likely to be unbiased under alternate data generating processes but is prone to bias under misspecification of the propensity score model and is inefficient compared to an unbiased regression estimator. Our results show that there are no ‘magic bullets’ when it comes to estimating treatment effects in health care costs. Care should be taken before naively applying any one estimator to estimate average treatment effects in these data. We illustrate the performance of alternative methods in a cost dataset on breast cancer treatment. PMID:22199462
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Birnbaum; Zimmermann
1998-05-01
Judges evaluated buying and selling prices of hypothetical investments, based on the previous price of each investment and estimates of the investment's future value given by advisors of varied expertise. Effect of a source's estimate varied in proportion to the source's expertise, and it varied inversely with the number and expertise of other sources. There was also a configural effect in which the effect of a source's estimate was affected by the rank order of that source's estimate, in relation to other estimates of the same investment. These interactions were fit with a configural weight averaging model in which buyers and sellers place different weights on estimates of different ranks. This model implies that one can design a new experiment in which there will be different violations of joint independence in different viewpoints. Experiment 2 confirmed patterns of violations of joint independence predicted from the model fit in Experiment 1. Experiment 2 also showed that preference reversals between viewpoints can be predicted by the model of Experiment 1. Configural weighting provides a better account of buying and selling prices than either of two models of loss aversion or the theory of anchoring and insufficient adjustment. Copyright 1998 Academic Press.
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2000-12-01
To investigate the effect of cataract on visual function and the role of cataract in explaining a race-treatment interaction in outcomes of glaucoma surgery. The Advanced Glaucoma Intervention Study (AGIS) enrolled 332 black patients (451 eyes) and 249 white patients (325 eyes) with advanced glaucoma. Eyes were randomly assigned to an argon laser trabeculoplasty (ALT)-trabeculectomy-trabeculectomy sequence or a trabeculectomy-ALT-trabeculectomy sequence. From the AGIS experience with cataract surgery during follow-up, we estimated the expected change in visual function scores from before cataract surgery to after cataract surgery. Then, for eyes with cataract not removed, we used these estimates of expected change to adjust visual function scores for the presumed effects of cataract. In turn, we used the adjusted scores to obtain cataract-adjusted main outcome measures. Average percent of eyes with decrease of visual field (APDVF) and average percent of eyes with decrease of visual acuity (APDVA). Within the 2 months before cataract surgery, visual acuity was better in eyes of white patients than of black patients by an average of approximately 2 lines on the visual acuity test chart. Cataract surgery improved visual acuity and visual field defect scores, with the amounts of improvement greater when preoperative visual acuity was lower. Adjustments for cataract brought about the following relative reductions: for APDVF, a relative reduction of 5% to 11% in black patients and 9% to 11% in white patients; for APDVA, a relative reduction of 45% to 49% in black patients and 31% to 38% in white patients; and for the APDVF and APDVA race-treatment interactions, relative reductions of 25% and 45%, respectively. On average, visual function scores improved after cataract surgery. The findings of reduced race-treatment interactions after adjustment for cataract do not alter our earlier conclusion that the AGIS 7-year results support use of the ALT-trabeculectomy-trabeculectomy sequence for black patients and of the trabeculectomy-ALT-trabeculectomy sequence for white patients without life-threatening health problems. The choice of treatment should take into account individual patient characteristics and needs.
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Collinearity and Causal Diagrams: A Lesson on the Importance of Model Specification.
Schisterman, Enrique F; Perkins, Neil J; Mumford, Sunni L; Ahrens, Katherine A; Mitchell, Emily M
2017-01-01
Correlated data are ubiquitous in epidemiologic research, particularly in nutritional and environmental epidemiology where mixtures of factors are often studied. Our objectives are to demonstrate how highly correlated data arise in epidemiologic research and provide guidance, using a directed acyclic graph approach, on how to proceed analytically when faced with highly correlated data. We identified three fundamental structural scenarios in which high correlation between a given variable and the exposure can arise: intermediates, confounders, and colliders. For each of these scenarios, we evaluated the consequences of increasing correlation between the given variable and the exposure on the bias and variance for the total effect of the exposure on the outcome using unadjusted and adjusted models. We derived closed-form solutions for continuous outcomes using linear regression and empirically present our findings for binary outcomes using logistic regression. For models properly specified, total effect estimates remained unbiased even when there was almost perfect correlation between the exposure and a given intermediate, confounder, or collider. In general, as the correlation increased, the variance of the parameter estimate for the exposure in the adjusted models increased, while in the unadjusted models, the variance increased to a lesser extent or decreased. Our findings highlight the importance of considering the causal framework under study when specifying regression models. Strategies that do not take into consideration the causal structure may lead to biased effect estimation for the original question of interest, even under high correlation.
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Morales-Suárez-Varela, Maria; Nohr, Ellen A; Bech, Bodil H; Wu, Chunsen; Olsen, Jørn
2016-10-01
The aim of this paper was to estimate the effect of maternal and paternal smoking on foetal death (miscarriage and stillbirth) and to estimate potential interactions with physical exercise and pre-pregnancy body mass index. We selected 87,930 pregnancies from the population-based Danish National Birth Cohort. Information about lifestyle, occupational, medical and obstetric factors was obtained from a telephone interview and data on pregnancy outcomes came from the Danish population based registries. Cox regression was used to estimate the hazard ratios (adjusted for potential confounders) for predominantly late foetal death (miscarriage and stillbirth). An interaction contrast ratio was used to assess potential effect measure modification of smoking by physical exercise and body mass index. The adjusted hazard ratio of foetal death was 1.22 (95 % CI 1.02-1.46) for couples where both parents smoked compared to non-smoking parents (miscarriage: 1.18, 95 % CI 0.96-1.44; stillbirth: 1.32, 95 % CI 0.93-1.89). On the additive scale, we detected a small positive interaction for stillbirth between smoking and body mass index (overweight women). In conclusion, smoking during pregnancy was associated with a slightly higher hazard ratio for foetal death if both parents smoked. This study suggests that smoking may increase the negative effect of a high BMI on foetal death, but results were not statistically significant for the interaction between smoking and physical exercise.
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Nygaard, Vegard; Rødland, Einar Andreas; Hovig, Eivind
2016-01-01
Removal of, or adjustment for, batch effects or center differences is generally required when such effects are present in data. In particular, when preparing microarray gene expression data from multiple cohorts, array platforms, or batches for later analyses, batch effects can have confounding effects, inducing spurious differences between study groups. Many methods and tools exist for removing batch effects from data. However, when study groups are not evenly distributed across batches, actual group differences may induce apparent batch differences, in which case batch adjustments may bias, usually deflate, group differences. Some tools therefore have the option of preserving the difference between study groups, e.g. using a two-way ANOVA model to simultaneously estimate both group and batch effects. Unfortunately, this approach may systematically induce incorrect group differences in downstream analyses when groups are distributed between the batches in an unbalanced manner. The scientific community seems to be largely unaware of how this approach may lead to false discoveries. PMID:26272994
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Reactivation of Herpes Simplex Virus Type 2 After Initiation of Antiretroviral Therapy
Tobian, Aaron A. R.; Grabowski, Mary K.; Serwadda, David; Newell, Kevin; Ssebbowa, Paschal; Franco, Veronica; Nalugoda, Fred; Wawer, Maria J.; Gray, Ronald H.; Quinn, Thomas C.; Reynolds, Steven J.
2013-01-01
Background. The association between initiation of antiretroviral therapy (ART) for human immunodeficiency virus (HIV) infection and possible herpes simplex virus type 2 (HSV-2) shedding and genital ulcer disease (GUD) has not been evaluated. Methods. GUD and vaginal HSV-2 shedding were evaluated among women coinfected with HIV and HSV-2 (n = 440 for GUD and n = 96 for HSV-2 shedding) who began ART while enrolled in a placebo-controlled trial of HSV-2 suppression with acyclovir in Rakai, Uganda. Monthly vaginal swabs were tested for HSV-2 shedding, using a real-time quantitative polymerase chain reaction assay. Prevalence risk ratios (PRRs) of GUD were estimated using log binomial regression. Random effects logistic regression was used to estimate odds ratios (ORs) of HSV-2 shedding. Results. Compared with pre-ART values, GUD prevalence increased significantly within the first 3 months after ART initiation (adjusted PRR, 1.94; 95% confidence interval [CI], 1.04–3.62) and returned to baseline after 6 months of ART (adjusted PRR, 0.80; 95% CI, .35–1.80). Detection of HSV-2 shedding was highest in the first 3 months after ART initiation (adjusted OR, 2.58; 95% CI, 1.48–4.49). HSV-2 shedding was significantly less common among women receiving acyclovir (adjusted OR, 0.13; 95% CI, .04–.41). Conclusions. The prevalence of HSV-2 shedding and GUD increased significantly after ART initiation, possibly because of immune reconstitution inflammatory syndrome. Acyclovir significantly reduced both GUD and HSV-2 shedding and should be considered to mitigate these effects following ART initiation. PMID:23812240
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Heijkenskjöld-Rentzhog, Charlotte; Alving, Kjell; Kalm-Stephens, Pia; Lundberg, Jon O; Nordvall, Lennart; Malinovschi, Andrei
2012-10-01
This study investigated the oral contribution to exhaled NO in young people with asthma and its potential effects on estimated alveolar NO (Calv(NO) ), a proposed marker of inflammation in peripheral airways. Secondary aims were to investigate the effects of various exhalation flow-rates and the feasibility of different proposed adjustments of (Calv(NO) ) for trumpet model and axial diffusion (TMAD). Exhaled NO at flow rates of 50-300 ml/sec, and salivary nitrite was measured before and after antibacterial mouthwash in 29 healthy young people (10-20 years) and 29 with asthma (10-19 years). Calv(NO) was calculated using the slope-intercept model with and without TMAD adjustment. Exhaled NO at 50 ml/sec decreased significantly after mouthwash, to a similar degree in asthmatic and healthy subjects (8.8% vs. 9.8%, P = 0.49). The two groups had similar salivary nitrite levels (56.4 vs. 78.4 µM, P = 0.25). Calv(NO) was not significantly decreased by mouthwash. Calv(NO) levels were similar when flow-rates between 50-200 or 100-300 ml/sec were used (P = 0.34 in asthmatics and P = 0.90 in healthy subjects). A positive association was found between bronchial and alveolar NO in asthmatic subjects and this disappeared after the TMAD-adjustment. Negative TMAD-adjusted Calv(NO) values were found in a minority of the subjects. Young people with and without asthma have similar salivary nitrite levels and oral contributions to exhaled NO and therefore no antibacterial mouthwash is necessary in routine use. TMAD corrections of alveolar NO could be successfully applied in young people with asthma and yielded negative results only in a minority of subjects. Copyright © 2012 Wiley Periodicals, Inc.
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Kent, David M; Dahabreh, Issa J; Ruthazer, Robin; Furlan, Anthony J; Weimar, Christian; Serena, Joaquín; Meier, Bernhard; Mattle, Heinrich P; Di Angelantonio, Emanuele; Paciaroni, Maurizio; Schuchlenz, Herwig; Homma, Shunichi; Lutz, Jennifer S; Thaler, David E
2015-09-14
The preferred antithrombotic strategy for secondary prevention in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO) is unknown. We pooled multiple observational studies and used propensity score-based methods to estimate the comparative effectiveness of oral anticoagulation (OAC) compared with antiplatelet therapy (APT). Individual participant data from 12 databases of medically treated patients with CS and PFO were analysed with Cox regression models, to estimate database-specific hazard ratios (HRs) comparing OAC with APT, for both the primary composite outcome [recurrent stroke, transient ischaemic attack (TIA), or death] and stroke alone. Propensity scores were applied via inverse probability of treatment weighting to control for confounding. We synthesized database-specific HRs using random-effects meta-analysis models. This analysis included 2385 (OAC = 804 and APT = 1581) patients with 227 composite endpoints (stroke/TIA/death). The difference between OAC and APT was not statistically significant for the primary composite outcome [adjusted HR = 0.76, 95% confidence interval (CI) 0.52-1.12] or for the secondary outcome of stroke alone (adjusted HR = 0.75, 95% CI 0.44-1.27). Results were consistent in analyses applying alternative weighting schemes, with the exception that OAC had a statistically significant beneficial effect on the composite outcome in analyses standardized to the patient population who actually received APT (adjusted HR = 0.64, 95% CI 0.42-0.99). Subgroup analyses did not detect statistically significant heterogeneity of treatment effects across clinically important patient groups. We did not find a statistically significant difference comparing OAC with APT; our results justify randomized trials comparing different antithrombotic approaches in these patients. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.
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On-demand Reporting of Risk-adjusted and Smoothed Rates for Quality Profiling in ACS NSQIP.
Cohen, Mark E; Liu, Yaoming; Huffman, Kristopher M; Ko, Clifford Y; Hall, Bruce L
2016-12-01
Surgical quality improvement depends on hospitals having accurate and timely information about comparative performance. Profiling accuracy is improved by risk adjustment and shrinkage adjustment to stabilize estimates. These adjustments are included in ACS NSQIP reports, where hospital odds ratios (OR) are estimated using hierarchical models built on contemporaneous data. However, the timeliness of feedback remains an issue. We describe an alternative, nonhierarchical approach, which yields risk- and shrinkage-adjusted rates. In contrast to our "Traditional" NSQIP method, this approach uses preexisting equations, built on historical data, which permits hospitals to have near immediate access to profiling results. We compared our traditional method to this new "on-demand" approach with respect to outlier determinations, kappa statistics, and correlations between logged OR and standardized rates, for 12 models (4 surgical groups by 3 outcomes). When both methods used the same contemporaneous data, there were similar numbers of hospital outliers and correlations between logged OR and standardized rates were high. However, larger differences were observed when the effect of contemporaneous versus historical data was added to differences in statistical methodology. The on-demand, nonhierarchical approach provides results similar to the traditional hierarchical method and offers immediacy, an "over-time" perspective, application to a broader range of models and data subsets, and reporting of more easily understood rates. Although the nonhierarchical method results are now available "on-demand" in a web-based application, the hierarchical approach has advantages, which support its continued periodic publication as the gold standard for hospital profiling in the program.
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Warren-Gash, Charlotte; Blackburn, Ruth; Whitaker, Heather; McMenamin, Jim; Hayward, Andrew C
2018-03-01
While acute respiratory tract infections can trigger cardiovascular events, the differential effect of specific organisms is unknown. This is important to guide vaccine policy.Using national infection surveillance data linked to the Scottish Morbidity Record, we identified adults with a first myocardial infarction or stroke from January 1, 2004 to December 31, 2014 and a record of laboratory-confirmed respiratory infection during this period. Using self-controlled case series analysis, we generated age- and season-adjusted incidence ratios (IRs) for myocardial infarction (n=1227) or stroke (n=762) after infections compared with baseline time.We found substantially increased myocardial infarction rates in the week after Streptococcus pneumoniae and influenza virus infection: adjusted IRs for days 1-3 were 5.98 (95% CI 2.47-14.4) and 9.80 (95% CI 2.37-40.5), respectively. Rates of stroke after infection were similarly high and remained elevated to 28 days: day 1-3 adjusted IRs 12.3 (95% CI 5.48-27.7) and 7.82 (95% CI 1.07-56.9) for S. pneumoniae and influenza virus, respectively. Although other respiratory viruses were associated with raised point estimates for both outcomes, only the day 4-7 estimate for stroke reached statistical significance.We showed a marked cardiovascular triggering effect of S. pneumoniae and influenza virus, which highlights the need for adequate pneumococcal and influenza vaccine uptake. Further research is needed into vascular effects of noninfluenza respiratory viruses. Copyright ©ERS 2018.
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Granato, Gregory E.; Smith, Kirk P.
1999-01-01
Discrete or composite samples of highway runoff may not adequately represent in-storm water-quality fluctuations because continuous records of water stage, specific conductance, pH, and temperature of the runoff indicate that these properties fluctuate substantially during a storm. Continuous records of water-quality properties can be used to maximize the information obtained about the stormwater runoff system being studied and can provide the context needed to interpret analyses of water samples. Concentrations of the road-salt constituents calcium, sodium, and chloride in highway runoff were estimated from theoretical and empirical relations between specific conductance and the concentrations of these ions. These relations were examined using the analysis of 233 highwayrunoff samples collected from August 1988 through March 1995 at four highway-drainage monitoring stations along State Route 25 in southeastern Massachusetts. Theoretically, the specific conductance of a water sample is the sum of the individual conductances attributed to each ionic species in solution-the product of the concentrations of each ion in milliequivalents per liter (meq/L) multiplied by the equivalent ionic conductance at infinite dilution-thereby establishing the principle of superposition. Superposition provides an estimate of actual specific conductance that is within measurement error throughout the conductance range of many natural waters, with errors of less than ?5 percent below 1,000 microsiemens per centimeter (?S/cm) and ?10 percent between 1,000 and 4,000 ?S/cm if all major ionic constituents are accounted for. A semi-empirical method (adjusted superposition) was used to adjust for concentration effects-superposition-method prediction errors at high and low concentrations-and to relate measured specific conductance to that calculated using superposition. The adjusted superposition method, which was developed to interpret the State Route 25 highway-runoff records, accounts for contributions of constituents other than calcium, sodium, and chloride in dilute waters. The adjusted superposition method also accounts for the attenuation of each constituent's contribution to conductance as ionic strength increases. Use of the adjusted superposition method generally reduced predictive error to within measurement error throughout the range of specific conductance (from 37 to 51,500 ?S/cm) in the highway runoff samples. The effects of pH, temperature, and organic constituents on the relation between concentrations of dissolved constituents and measured specific conductance were examined but these properties did not substantially affect interpretation of the Route 25 data set. Predictive abilities of the adjusted superposition method were similar to results obtained by standard regression techniques, but the adjusted superposition method has several advantages. Adjusted superposition can be applied using available published data about the constituents in precipitation, highway runoff, and the deicing chemicals applied to a highway. This semi-empirical method can be used as a predictive and diagnostic tool before a substantial number of samples are collected, but the power of the regression method is based upon a large number of water-quality analyses that may be affected by a bias in the data.
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Akumu, Angela Oloo; English, Mike; Scott, J Anthony G; Griffiths, Ulla K
2007-07-01
Haemophilus influenzae type b (Hib) vaccine was introduced into routine immunization services in Kenya in 2001. We aimed to estimate the cost-effectiveness of Hib vaccine delivery. A model was developed to follow the Kenyan 2004 birth cohort until death, with and without Hib vaccine. Incidence of invasive Hib disease was estimated at Kilifi District Hospital and in the surrounding demographic surveillance system in coastal Kenya. National Hib disease incidence was estimated by adjusting incidence observed by passive hospital surveillance using assumptions about access to care. Case fatality rates were also assumed dependent on access to care. A price of US$ 3.65 per dose of pentavalent diphtheria-tetanus-pertussis-hep B-Hib vaccine was used. Multivariate Monte Carlo simulations were performed in order to assess the impact on the cost-effectiveness ratios of uncertainty in parameter values. The introduction of Hib vaccine reduced the estimated incidence of Hib meningitis per 100,000 children aged < 5 years from 71 to 8; of Hib non-meningitic invasive disease from 61 to 7; and of non-bacteraemic Hib pneumonia from 296 to 34. The costs per discounted disability adjusted life year (DALY) and per discounted death averted were US$ 38 (95% confidence interval, CI: 26-63) and US$ 1197 (95% CI: 814-2021) respectively. Most of the uncertainty in the results was due to uncertain access to care parameters. The break-even pentavalent vaccine price--where incremental Hib vaccination costs equal treatment costs averted from Hib disease--was US$ 1.82 per dose. Hib vaccine is a highly cost-effective intervention in Kenya. It would be cost-saving if the vaccine price was below half of its present level.
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Impact and quantification of the sources of error in DNA pooling designs.
Jawaid, A; Sham, P
2009-01-01
The analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies.
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Estimating parameters of hidden Markov models based on marked individuals: use of robust design data
Kendall, William L.; White, Gary C.; Hines, James E.; Langtimm, Catherine A.; Yoshizaki, Jun
2012-01-01
Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).
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The costs and benefits of water fluoridation in NZ.
Moore, David; Poynton, Matthew; Broadbent, Jonathan M; Thomson, W Murray
2017-11-28
Implementing community water fluoridation involves costs, but these need to be considered against the likely benefits. We aimed to assess the cost-benefit and cost-effectiveness of water fluoridation in New Zealand (NZ) in terms of expenditure and quality-adjusted life years. Based on published studies, we determined the risk reduction effects of fluoridation, we quantified its health benefits using standardised dental indexes, and we calculated financial savings from averted treatment. We analysed NZ water supplies to estimate the financial costs of fluoridation. We devised a method to represent dental caries experience in quality-adjusted life years. Over 20 years, the net discounted saving from adding fluoride to reticulated water supplies supplying populations over 500 would be NZ$1401 million, a nine times pay-off. Between 8800 and 13,700 quality-adjusted life years would be gained. While fluoridating reticulated water supplies for large communities is cost-effective, it is unlikely to be so with populations smaller than 500. Community water fluoridation remains highly cost-effective for all but very small communities. The health benefits-while (on average) small per person-add up to a substantial reduction in the national disease burden across all ethnic and socioeconomic groups.
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Miners, Alec; Harris, Jody; Felix, Lambert; Murray, Elizabeth; Michie, Susan; Edwards, Phil
2012-07-07
The prevalence of obesity is over 25 % in many developed countries. Obesity is strongly associated with an increased risk of fatal and chronic conditions such as cardiovascular disease and type 2 diabetes. Therefore it has become a major public health concern for many economies. E-learning devices are a relatively novel approach to promoting dietary change. The new generation of devices are 'adaptive' and use interactive electronic media to facilitate teaching and learning. E-Learning has grown out of recent developments in information and communication technology, such as the Internet, interactive computer programmes, interactive television and mobile phones. The aim of this study is to assess the cost-effectiveness of e-learning devices as a method of promoting weight loss via dietary change. An economic evaluation was performed using decision modelling techniques. Outcomes were expressed in terms of Quality-Adjusted Life-Years (QALYs) and costs were estimated from a health services perspective. All parameter estimates were derived from the literature. A systematic review was undertaken to derive the estimate of relative treatment effect. The base case results from the e-Learning Economic Evaluation Model (e-LEEM) suggested that the incremental cost-effectiveness ratio was approximately £102,000 per Quality-Adjusted Life-Year (QALY) compared to conventional care. This finding was robust to most alternative assumptions, except a much lower fixed cost of providing e-learning devices. Expected value of perfect information (EVPI) analysis showed that while the individual level EVPI was arguably negligible, the population level value was between £37 M and £170 M at a willingness to pay between £20,000 to £30,000 per additional QALY. The current economic evidence base suggests that e-learning devices for managing the weight of obese individuals are unlikely to be cost-effective unless their fixed costs are much lower than estimated or future devices prove to be much more effective.
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Cost of chronic disease in California: estimates at the county level.
Brown, Paul M; Gonzalez, Mariaelena; Dhaul, Ritem Sandhu
2015-01-01
An estimated 39% of people in California suffer from at least one chronic condition or disease. While the increased coverage provided by the Affordable Care Act will result in greater access to primary health care, coordinated strategies are needed to prevent chronic conditions. To identify cost-effective strategies, local health departments and other agencies need accurate information on the costs of chronic conditions in their region. To present a methodology for estimating the cost of chronic conditions for counties. Estimates of the attributable cost of 6 chronic conditions-arthritis, asthma, cancer, cardiovascular disease, diabetes, and depression-from the Centers for Disease Control and Prevention's Chronic Disease Cost Calculator were combined with prevalence rates from the various sources and census data for California counties to estimate the number of cases and costs of each condition. The estimates were adjusted for differences in prices using Medicare geographical adjusters. An estimated $98 billion is currently spent on treating chronic conditions in California. There is significant variation between counties in the percentage of total health care expenditure due to chronic conditions and county size, ranging from a low 32% to a high of 63%. The variations between counties result from differing rates of chronic conditions across age, ethnicity, and gender. Information on the cost of chronic conditions is important for planning prevention and control efforts. This study demonstrates a method for providing local health departments with estimates of the scope of the problems in their region. Combining the cost estimates with information on current prevention strategies can identify gaps in prevention activities and the prevention measures that promise the greatest return on investment for each county.
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Hammerslough, C R
1992-01-01
An integrated approach to estimate the total number of pregnancies that begin in a population during one calendar year and the probability of spontaneous abortion is described. This includes an indirect estimate of the number of pregnancies that result in spontaneous abortions. The method simultaneously takes into account the proportion of induced abortions that are censored by spontaneous abortions and vice versa in order to estimate the true annual number of spontaneous and induced abortions for a population. It also estimates the proportion of pregnancies that women intended to allow to continue to a live birth. The proposed indirect approach derives adjustment factors to make indirect estimates by combining vital statistics information on gestational age at induced abortion (from the 12 States that report to the National Center for Health Statistics) with a life table of spontaneous abortion probabilities. The adjustment factors are applied to data on induced abortions from the Alan Guttmacher Institute Abortion Provider Survey and data on births from U.S. vital statistics. For the United States in 1980 the probability of a spontaneous abortion is 19 percent, given the presence of induced abortion. Once the effects of spontaneous abortion are discounted, women in 1980 intended to allow 73 percent of their pregnancies to proceed to a live birth. One medical benefit to a population practicing induced abortion is that induced abortions avert some spontaneous abortions, leading to a lower mean gestational duration at the time of spontaneous abortion. PMID:1594736
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[Morbidity Differences by Health Insurance Status in Old Age].
Hajek, A; Bock, J-O; Saum, K-U; Schöttker, B; Brenner, H; Heider, D; König, H-H
2018-06-01
Morbidity differences between older members of private and statutory health insurance Germany have rarely been examined. Thus, we aimed at determining these differences in old age. This study used data from 2 follow-up waves with a 3-year interval from a population-based prospective cohort study (ESTHER study) in Saarland, Germany. Morbidity was assessed by participants' GPs using a generic instrument (Cumulative Illness Rating Scale for Geriatrics). The between estimator was used which exclusively quantifies inter-individual variation. Adjusting for sex and age, we investigated the association between health insurance and morbidity in the main model. In additional models, we adjusted incrementally for the effect of education, family status and income. Regression models not adjusting for income showed that members of private health insurance had a lower morbidity score than members of statutory health insurance. This effect is considerably lower in models adjusting for income, but remained statistically significant (except for men). Observed differences in morbidity between older members of private and statutory health insurance can partly be explained by income differences. Thus, our findings highlight the role of model specification in determining the relation between morbidity and health insurance. © Georg Thieme Verlag KG Stuttgart · New York.
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Bergh, Daniel
2015-01-01
Chi-square statistics are commonly used for tests of fit of measurement models. Chi-square is also sensitive to sample size, which is why several approaches to handle large samples in test of fit analysis have been developed. One strategy to handle the sample size problem may be to adjust the sample size in the analysis of fit. An alternative is to adopt a random sample approach. The purpose of this study was to analyze and to compare these two strategies using simulated data. Given an original sample size of 21,000, for reductions of sample sizes down to the order of 5,000 the adjusted sample size function works as good as the random sample approach. In contrast, when applying adjustments to sample sizes of lower order the adjustment function is less effective at approximating the chi-square value for an actual random sample of the relevant size. Hence, the fit is exaggerated and misfit under-estimated using the adjusted sample size function. Although there are big differences in chi-square values between the two approaches at lower sample sizes, the inferences based on the p-values may be the same.
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O'Neill, Marie S; Hajat, Shakoor; Zanobetti, Antonella; Ramirez-Aguilar, Matiana; Schwartz, Joel
2005-11-01
We assessed the influence of control for air pollution and respiratory epidemics on associations between apparent temperature (AT) and daily mortality in Mexico City and Monterrey. Poisson regressions were fit to mortality among all ages, children (ages 0-14 years) and the elderly (ages >or=65 years). Predictors included mean daily AT, season, day of week and public holidays for the base model. Respiratory epidemics and air pollution (particulate matter <10 microm in aerodynamic diameter and O3) were added singly and then jointly for a fully adjusted model. Percent changes in mortality were calculated for days of relatively extreme temperatures [cold (10-11 degrees C) for both cities and heat (35-36 degrees C) for Monterrey], compared to days at the overall mean temperature in each city (15 degrees C in Mexico City, 25 degrees C in Monterrey). In Mexico City, total mortality increased 12.4% [95% confidence interval (CI) 10.5%, 14.5%] on cold days (fully adjusted). Among children, the adjusted association was similar [10.9% (95% CI: 5.4%, 16.7%)], but without control for pollution and epidemics, was nearly twice as large [19.7% (95% CI: 13.9%, 25.9)]. In Monterrey, the fully adjusted heat effect for all deaths was 18.7% (95% CI: 11.7%, 26.1%), a third lower than the unadjusted estimate; the heat effect was lower among children [5.5% (95% CI: -10.1%, 23.8%)]. Cold had a similar effect on all-age mortality as in Mexico City [11.7% (95% CI: 3.7%, 20.3%)]. Responses of the elderly differed little from all-ages responses in both cities. Associations between weather and health persisted even with control for air pollution and respiratory epidemics in two Mexican cities, but risk assessments and climate change adaptation programs are best informed by analyses that account for these potential confounders.
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NASA Astrophysics Data System (ADS)
O'Neill, Marie S.; Hajat, Shakoor; Zanobetti, Antonella; Ramirez-Aguilar, Matiana; Schwartz, Joel
2005-11-01
We assessed the influence of control for air pollution and respiratory epidemics on associations between apparent temperature (AT) and daily mortality in Mexico City and Monterrey. Poisson regressions were fit to mortality among all ages, children (ages 0 14 years) and the elderly (ages ≥65 years). Predictors included mean daily AT, season, day of week and public holidays for the base model. Respiratory epidemics and air pollution (particulate matter <10 μm in aerodynamic diameter and O3) were added singly and then jointly for a fully adjusted model. Percent changes in mortality were calculated for days of relatively extreme temperatures [cold (10 11°C) for both cities and heat (35 36°C) for Monterrey], compared to days at the overall mean temperature in each city (15°C in Mexico City, 25°C in Monterrey). In Mexico City, total mortality increased 12.4% [95% confidence interval (CI) 10.5%, 14.5%] on cold days (fully adjusted). Among children, the adjusted association was similar [10.9% (95% CI: 5.4%, 16.7%)], but without control for pollution and epidemics, was nearly twice as large [19.7% (95% CI: 13.9%, 25.9)]. In Monterrey, the fully adjusted heat effect for all deaths was 18.7% (95% CI: 11.7%, 26.1%), a third lower than the unadjusted estimate; the heat effect was lower among children [5.5% (95% CI: -10.1%, 23.8%)]. Cold had a similar effect on all-age mortality as in Mexico City [11.7% (95% CI: 3.7%, 20.3%)]. Responses of the elderly differed little from all-ages responses in both cities. Associations between weather and health persisted even with control for air pollution and respiratory epidemics in two Mexican cities, but risk assessments and climate change adaptation programs are best informed by analyses that account for these potential confounders.
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Cost-effectiveness analysis of early point-of-care lactate testing in the emergency department.
Ward, Michael J; Self, Wesley H; Singer, Adam; Lazar, Danielle; Pines, Jesse M
2016-12-01
To determine the cost-effectiveness of implementing a point-of-care (POC) Lactate Program in the emergency department (ED) for patients with suspected sepsis to identify patients who can benefit from early resuscitation. We constructed a cost-effectiveness model to examine an ED with 30 000 patients annually. We evaluated a POC lactate program screening patients with suspected sepsis for an elevated lactate ≥4 mmol/L. Those with elevated lactate levels are resuscitated and their lactate clearance is evaluated by serial POC lactate measurements. The POC Lactate Program was compared with a Usual Care Strategy in which all patients with sepsis and an elevated lactate are admitted to the intensive care unit. Costs were estimated from the 2014 Medicare Inpatient and National Physician Fee schedules, and hospital and industry estimates. In the base-case, the POC Lactate Program cost $39.53/patient whereas the Usual Care Strategy cost $33.20/patient. The screened patients in the POC arm resulted in 1.07 quality-adjusted life years for an incremental cost-effectiveness ratio of $31 590 per quality-adjusted life year gained, well below accepted willingness-to-pay-thresholds. Implementing a POC Lactate Program for screening ED patients with suspected sepsis is a cost-effective intervention to identify patients responsive to early resuscitation. Copyright © 2016 Elsevier Inc. All rights reserved.
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Kupek, Emil; Viertel, Ilse
2018-05-14
To evaluate cost effectiveness of 10-valent pneumococcal conjugate vaccine in the routine immunization program for children younger than 5 years in Brazil by a postintroduction study. Ecological study of prevaccine (2006-2009) versus postvaccine (2011-2014) period related the changes in mortality rate and hospitalization rate to direct cost of pneumonia treatment from the payer's perspective to estimate the cost effectiveness regarding lives saved, life-years gained, and disability-adjusted life-year for children younger than 5 years in the southern Brazilian state of Santa Catarina. All-cause pneumonia (ICD-10 J12-J18) deaths, hospital admissions, and associated costs were retrieved from the Brazilian Ministry of Health official Web site. Life expectancy at birth, population, ambulatory costs, cost savings, and plausible range of these parameters were used from published sources. Computer simulations with sensitivity analysis were performed to obtain the cost-effectiveness estimates. About 27 lives were saved and 2573 hospitalizations averted by the 10-valent pneumococcal conjugate vaccine vaccination in the 2011 to 2014 period at the cost of US $24,348 per life-year gained and US $27,748 per disability-adjusted life-year. The latter cost is 81% of Brazilian gross domestic product per capita over the same period. The vaccine was very cost-effective according to the World Health Organization criterion. Copyright © 2018. Published by Elsevier Inc.
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Richards, Toby; Musallam, Khaled M.; Nassif, Joseph; Ghazeeri, Ghina; Seoud, Muhieddine; Gurusamy, Kurinchi S.; Jamali, Faek R.
2015-01-01
Objective To evaluate the effect of preoperative anaemia and blood transfusion on 30-day postoperative morbidity and mortality in patients undergoing gynecological surgery. Study Design Data were analyzed from 12,836 women undergoing operation in the American College of Surgeons National Surgical Quality Improvement Program. Outcomes measured were; 30-day postoperative mortality, composite and specific morbidities (cardiac, respiratory, central nervous system, renal, wound, sepsis, venous thrombosis, or major bleeding). Multivariate logistic regression models were performed using adjusted odds ratios (ORadj) to assess the independent effects of preoperative anaemia (hematocrit <36.0%) on outcomes, effect estimates were performed before and after adjustment for perioperative transfusion requirement. Results The prevalence of preoperative anaemia was 23.9% (95%CI: 23.2–24.7). Adjusted for confounders by multivariate logistic regression; preoperative anaemia was independently and significantly associated with increased odds of 30-day mortality (OR: 2.40, 95%CI: 1.06–5.44) and composite morbidity (OR: 1.80, 95%CI: 1.45–2.24). This was reflected by significantly higher adjusted odds of almost all specific morbidities including; respiratory, central nervous system, renal, wound, sepsis, and venous thrombosis. Blood Transfusion increased the effect of preoperative anaemia on outcomes (61% of the effect on mortality and 16% of the composite morbidity). Conclusions Preoperative anaemia is associated with adverse post-operative outcomes in women undergoing gynecological surgery. This risk associated with preoperative anaemia did not appear to be corrected by use of perioperative transfusion. PMID:26147954
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10 CFR 70.25 - Financial assurance and recordkeeping for decommissioning.
Code of Federal Regulations, 2010 CFR
2010-01-01
... renewal. (3) Each holder of a specific license issued before July 27, 1990, and of a type described in... periodically over the life of the facility. Cost estimates must be adjusted at intervals not to exceed 3 years... surety method or insurance must remain in effect until the Commission has terminated the license. (3) An...
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An Analysis of the Individual Effects of Sex Bias.
ERIC Educational Resources Information Center
Smith, Richard M.
Most attempts to correct for the presence of biased test items in a measurement instrument have been either to remove the items or to adjust the scores to correct for the bias. Using the Rasch Dichotomous Response Model and the independent ability estimates derived from three sets of items, those which favor females, those which favor males, and…
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USDA-ARS?s Scientific Manuscript database
Soil properties and weather conditions are known to affect soil nitrogen (N) availability and plant N uptake. However, studies examining N response as affected by soil and weather sometimes give conflicting results. Meta-analysis is a statistical method for estimating treatment effects in a series o...
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A Statistical Model for Misreported Binary Outcomes in Clustered RCTs of Education Interventions
ERIC Educational Resources Information Center
Schochet, Peter Z.
2013-01-01
In education randomized control trials (RCTs), the misreporting of student outcome data could lead to biased estimates of average treatment effects (ATEs) and their standard errors. This article discusses a statistical model that adjusts for misreported binary outcomes for two-level, school-based RCTs, where it is assumed that misreporting could…
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Adjustment of regional regression equations for urban storm-runoff quality using at-site data
Barks, C.S.
1996-01-01
Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.
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Lake, Robin J; Horn, Beverley J; Dunn, Alex H; Parris, Ruth; Green, F Terri; McNickle, Don C
2013-07-01
An analysis of the cost-effectiveness of interventions to control Campylobacter in the New Zealand poultry supply examined a series of interventions. Effectiveness was evaluated in terms of reduced health burden measured by disability-adjusted life years (DALYs). Costs of implementation were estimated from the value of cost elements, determined by discussions with industry. Benefits were estimated by changing the inputs to a poultry food chain quantitative risk model. Proportional reductions in the number of predicted Campylobacter infections were converted into reductions in the burden of disease measured in DALYs. Cost-effectiveness ratios were calculated for each intervention, as cost per DALY reduction and the ratios compared. The results suggest that the most cost-effective interventions (lowest ratios) are at the primary processing stage. Potential phage-based controls in broiler houses were also highly cost-effective. This study is limited by the ability to quantify costs of implementation and assumptions required to estimate health benefits, but it supports the implementation of interventions at the primary processing stage as providing the greatest quantum of benefit and lowest cost-effectiveness ratios.
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Morris, S; Ridley, S; Munro, V; Christensen, M C
2007-01-01
The aim of this study was to assess the lifetime cost effectiveness of recombinant activated factor VII vs placebo as adjunctive therapy for control of bleeding in patients with severe blunt trauma in the UK. We developed a cost-effectiveness model based on patient level data from a 30-day international, randomised, placebo-controlled Phase II trial. The data were supplemented with secondary data from UK sources to estimate lifetime costs and benefits. The model produced a baseline estimate of the incremental cost per life year gained with recombinant activated factor VII relative to placebo of 12 613 UK pounds. The incremental cost per quality adjusted life year gained was 18 825 UK pounds. These estimates are sensitive to the choice of discount rate and health state utility values used. Preliminary results suggest that relative to placebo, recombinant activated factor VII may be a cost-effective therapy to the UK National Health Service.
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Lee, Mee-Ri; Lim, Youn-Hee; Lee, Bo-Eun; Hong, Yun-Chul
2017-03-04
Mercury is a toxic heavy metal and is known to affect many diseases. However, few studies have examined the effects of mercury exposure on liver function in the general population. We examined the association between blood mercury concentrations and liver enzyme levels in the elderly. We included 560 elderly participants (60 years or older) who were recruited from 2008 to 2010 and followed up to 2014. Subjects visited a community welfare center and underwent a medical examination and measurement of mercury levels up to five times. Analyses using generalized estimating equations model were performed after adjusting for age, sex, education, overweight, alcohol consumption, smoking, regular exercise, high-density lipoproteins cholesterol, and total calorie intake. Additionally, we estimated interaction effects of alcohol consumption with mercury and mediation effect of oxidative stress in the relationship between mercury levels and liver function. The geometric mean (95% confidence interval (CI)) of blood mercury concentrations was 2.81 μg/L (2.73, 2.89). Significant relationships were observed between blood mercury concentrations and the level of liver enzymes, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma glutamyl transferase (GGT), after adjusting for potential confounders (P < 0.05). The odds ratios of having abnormal ALT levels were statistically significant in the highest mercury quartile compared to those with the lowest quartile. Particularly, regular alcohol drinkers showed greater effect estimates of mercury on the liver function than non-drinkers groups. There was no mediation effect of oxidative stress in the relationship between blood mercury concentrations and liver function. Our results suggest that blood mercury levels are associated with elevated liver enzymes and interact with alcohol consumption for the association in the elderly.
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Byrnes, Joshua; Carrington, Melinda; Chan, Yih-Kai; Pollicino, Christine; Dubrowin, Natalie; Stewart, Simon; Scuffham, Paul A.
2015-01-01
The aim of this study is to consider the cost-effectiveness of a nurse-led, home-based intervention (HBI) in cardiac patients with private health insurance compared to usual post-discharge care. A within trial analysis of the Young @ Heart multicentre, randomized controlled trial along with a micro-simulation decision analytical model was conducted to estimate the incremental costs and quality adjusted life years associated with the home based intervention compared to usual care. For the micro-simulation model, future costs, from the perspective of the funder, and effects are estimated over a twenty-year time horizon. An Incremental Cost-Effectiveness Ratio, along with Incremental Net Monetary Benefit, is evaluated using a willingness to pay threshold of $50,000 per quality adjusted life year. Sub-group analyses are conducted for men and women across three age groups separately. Costs and benefits that arise in the future are discounted at five percent per annum. Overall, home based intervention for secondary prevention in patients with chronic heart disease identified in the Australian private health care sector is not cost-effective. The estimated within trial incremental net monetary benefit is -$3,116 [95%CI: -11,145, $4,914]; indicating that the costs outweigh the benefits. However, for males and in particular males aged 75 years and above, home based intervention indicated a potential to reduce health care costs when compared to usual care (within trial: -$10,416 [95%CI: -$26,745, $5,913]; modelled analysis: -$1,980 [95%CI: -$22,843, $14,863]). This work provides a crucial impetus for future research to understand for whom disease management programs are likely to benefit most. PMID:26657844
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Reconciling medical expenditure estimates from the MEPS and NHEA, 2007.
Bernard, Didem; Cowan, Cathy; Selden, Thomas; Cai, Liming; Catlin, Aaron; Heffler, Stephen
2012-01-01
Provide a comparison of health care expenditure estimates for 2007 from the Medical Expenditure Panel Survey (MEPS) and the National Health Expenditure Accounts (NHEA). Reconciling these estimates serves two important purposes. First, it is an important quality assurance exercise for improving and ensuring the integrity of each source's estimates. Second, the reconciliation provides a consistent baseline of health expenditure data for policy simulations. Our results assist researchers to adjust MEPS to be consistent with the NHEA so that the projected costs as well as budgetary and tax implications of any policy change are consistent with national health spending estimates. The Medical Expenditure Panel Survey produced by the Agency for Healthcare Research and Quality, and the National Health Center for Health Statistics and the National Health Expenditures produced by the Centers for Medicare & Medicaid Service's Office of the Actuary. In this study, we focus on the personal health care (PHC) sector, which includes the goods and services rendered to treat or prevent a specific disease or condition in an individual. The official 2007 NHEA estimate for PHC spending is $1,915 billion and the MEPS estimate is $1,126 billion. Adjusting the NHEA estimates for differences in underlying populations, covered services, and other measurement concepts reduces the NHEA estimate for 2007 to $1,366 billion. As a result, MEPS is $240 billion, or 17.6 percent, less than the adjusted NHEA total.
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Chew, Derek P; Carter, Robert; Rankin, Bree; Boyden, Andrew; Egan, Helen
2010-05-01
The cost effectiveness of a general practice-based program for managing coronary heart disease (CHD) patients in Australia remains uncertain. We have explored this through an economic model. A secondary prevention program based on initial clinical assessment and 3 monthly review, optimising of pharmacotherapies and lifestyle modification, supported by a disease registry and financial incentives for quality of care and outcomes achieved was assessed in terms of incremental cost effectiveness ratio (ICER), in Australian dollars per disability adjusted life year (DALY) prevented. Based on 2006 estimates, 263 487 DALYs were attributable to CHD in Australia. The proposed program would add $115 650 000 to the annual national heath expenditure. Using an estimated 15% reduction in death and disability and a 40% estimated program uptake, the program's ICER is $8081 per DALY prevented. With more conservative estimates of effectiveness and uptake, estimates of up to $38 316 per DALY are observed in sensitivity analysis. Although innovation in CHD management promises improved future patient outcomes, many therapies and strategies proven to reduce morbidity and mortality are available today. A general practice-based program for the optimal application of current therapies is likely to be cost-effective and provide substantial and sustainable benefits to the Australian community.
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Environmental Chemicals in Urine and Blood: Improving Methods for Creatinine and Lipid Adjustment
O’Brien, Katie M.; Upson, Kristen; Cook, Nancy R.; Weinberg, Clarice R.
2015-01-01
Background Investigators measuring exposure biomarkers in urine typically adjust for creatinine to account for dilution-dependent sample variation in urine concentrations. Similarly, it is standard to adjust for serum lipids when measuring lipophilic chemicals in serum. However, there is controversy regarding the best approach, and existing methods may not effectively correct for measurement error. Objectives We compared adjustment methods, including novel approaches, using simulated case–control data. Methods Using a directed acyclic graph framework, we defined six causal scenarios for epidemiologic studies of environmental chemicals measured in urine or serum. The scenarios include variables known to influence creatinine (e.g., age and hydration) or serum lipid levels (e.g., body mass index and recent fat intake). Over a range of true effect sizes, we analyzed each scenario using seven adjustment approaches and estimated the corresponding bias and confidence interval coverage across 1,000 simulated studies. Results For urinary biomarker measurements, our novel method, which incorporates both covariate-adjusted standardization and the inclusion of creatinine as a covariate in the regression model, had low bias and possessed 95% confidence interval coverage of nearly 95% for most simulated scenarios. For serum biomarker measurements, a similar approach involving standardization plus serum lipid level adjustment generally performed well. Conclusions To control measurement error bias caused by variations in serum lipids or by urinary diluteness, we recommend improved methods for standardizing exposure concentrations across individuals. Citation O’Brien KM, Upson K, Cook NR, Weinberg CR. 2016. Environmental chemicals in urine and blood: improving methods for creatinine and lipid adjustment. Environ Health Perspect 124:220–227; http://dx.doi.org/10.1289/ehp.1509693 PMID:26219104
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Longitudinal study of mammographic density measures that predict breast cancer risk
Krishnan, Kavitha; Baglietto, Laura; Stone, Jennifer; Simpson, Julie A; Severi, Gianluca; Evans, Christopher F; MacInnis, Robert J; Giles, Graham G; Apicella, Carmel; Hopper, John L
2016-01-01
Background After adjusting for age and body mass index (BMI), mammographic measures - dense area (DA), percent dense area (PDA) and non-dense area (NDA) - are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time. Methods We collected 4,320 mammograms (age range, 24-83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1-14). DA, PDA and NDA were measured using the Cumulus software and normalised using the Box-Cox method. Correlations in the normalised risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modelling of Gompertz curves. Results Mean normalised DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant from the mid 60s onwards. Mean normalised NDA increased non-linearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalised DA were 0.94, 0.93, 0.91, 0.91 and 0.91 for mammograms taken 2, 4, 6, 8 and 10 years apart, respectively. Similar correlations were estimated for the age and BMI adjusted normalized PDA and NDA. Conclusion The mammographic measures that predict breast cancer risk are highly correlated over time. Impact This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g. early 40s or even younger) and recommended appropriate screening and prevention strategies. PMID:28062399
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Iachan, Ronaldo; H. Johnson, Christopher; L. Harding, Richard; Kyle, Tonja; Saavedra, Pedro; L. Frazier, Emma; Beer, Linda; L. Mattson, Christine; Skarbinski, Jacek
2016-01-01
Background: Health surveys of the general US population are inadequate for monitoring human immunodeficiency virus (HIV) infection because the relatively low prevalence of the disease (<0.5%) leads to small subpopulation sample sizes. Objective: To collect a nationally and locally representative probability sample of HIV-infected adults receiving medical care to monitor clinical and behavioral outcomes, supplementing the data in the National HIV Surveillance System. This paper describes the sample design and weighting methods for the Medical Monitoring Project (MMP) and provides estimates of the size and characteristics of this population. Methods: To develop a method for obtaining valid, representative estimates of the in-care population, we implemented a cross-sectional, three-stage design that sampled 23 jurisdictions, then 691 facilities, then 9,344 HIV patients receiving medical care, using probability-proportional-to-size methods. The data weighting process followed standard methods, accounting for the probabilities of selection at each stage and adjusting for nonresponse and multiplicity. Nonresponse adjustments accounted for differing response at both facility and patient levels. Multiplicity adjustments accounted for visits to more than one HIV care facility. Results: MMP used a multistage stratified probability sampling design that was approximately self-weighting in each of the 23 project areas and nationally. The probability sample represents the estimated 421,186 HIV-infected adults receiving medical care during January through April 2009. Methods were efficient (i.e., induced small, unequal weighting effects and small standard errors for a range of weighted estimates). Conclusion: The information collected through MMP allows monitoring trends in clinical and behavioral outcomes and informs resource allocation for treatment and prevention activities. PMID:27651851
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Nightingale, C M; Donin, A S; Kerry, S R; Owen, C G; Rudnicka, A R; Brage, S; Westgate, K L; Ekelund, U; Cook, D G; Whincup, P H
2016-01-01
Objective Little is known about levels of physical fitness in children from different ethnic groups in the UK. We therefore studied physical fitness in UK children (aged 9–10 years) of South Asian, black African–Caribbean and white European origin. Design Cross-sectional study. Setting Primary schools in the UK. Participants 1625 children (aged 9–10 years) of South Asian, black African–Caribbean and white European origin in the UK studied between 2006 and 2007. Outcome measures A step test assessed submaximal physical fitness from which estimated VO2 max was derived. Ethnic differences in estimated VO2 max were estimated using multilevel linear regression allowing for clustering at school level and adjusting for age, sex and month as fixed effects. Results The study response rate was 63%. In adjusted analyses, boys had higher levels of estimated VO2 max than girls (mean difference 3.06 mL O2/min/kg, 95% CI 2.66 to 3.47, p<0.0001). Levels of estimated VO2 max were lower in South Asians than those in white Europeans (mean difference −0.79 mL O2/min/kg, 95% CI −1.41 to −0.18, p=0.01); levels of estimated VO2 max in black African–Caribbeans were higher than those in white Europeans (mean difference 0.60 mL O2/min/kg, 95% CI 0.02 to 1.17, p=0.04); these patterns were similar in boys and girls. The lower estimated VO2 max in South Asians, compared to white Europeans, was consistent among Indian, Pakistani and Bangladeshi children and was attenuated by 78% after adjustment for objectively measured physical activity (average daily steps). Conclusions South Asian children have lower levels of physical fitness than white Europeans and black African–Caribbeans in the UK. This ethnic difference in physical fitness is at least partly explained by ethnic differences in physical activity. PMID:27324713
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Nightingale, C M; Donin, A S; Kerry, S R; Owen, C G; Rudnicka, A R; Brage, S; Westgate, K L; Ekelund, U; Cook, D G; Whincup, P H
2016-06-20
Little is known about levels of physical fitness in children from different ethnic groups in the UK. We therefore studied physical fitness in UK children (aged 9-10 years) of South Asian, black African-Caribbean and white European origin. Cross-sectional study. Primary schools in the UK. 1625 children (aged 9-10 years) of South Asian, black African-Caribbean and white European origin in the UK studied between 2006 and 2007. A step test assessed submaximal physical fitness from which estimated VO2 max was derived. Ethnic differences in estimated VO2 max were estimated using multilevel linear regression allowing for clustering at school level and adjusting for age, sex and month as fixed effects. The study response rate was 63%. In adjusted analyses, boys had higher levels of estimated VO2 max than girls (mean difference 3.06 mL O2/min/kg, 95% CI 2.66 to 3.47, p<0.0001). Levels of estimated VO2 max were lower in South Asians than those in white Europeans (mean difference -0.79 mL O2/min/kg, 95% CI -1.41 to -0.18, p=0.01); levels of estimated VO2 max in black African-Caribbeans were higher than those in white Europeans (mean difference 0.60 mL O2/min/kg, 95% CI 0.02 to 1.17, p=0.04); these patterns were similar in boys and girls. The lower estimated VO2 max in South Asians, compared to white Europeans, was consistent among Indian, Pakistani and Bangladeshi children and was attenuated by 78% after adjustment for objectively measured physical activity (average daily steps). South Asian children have lower levels of physical fitness than white Europeans and black African-Caribbeans in the UK. This ethnic difference in physical fitness is at least partly explained by ethnic differences in physical activity. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
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Pak, N; Vera, G; Araya, H
1985-03-01
The purpose of the present study was to evaluate the amino acid score adjusted by digestibility to estimate protein quality and utilizable protein in foods and diets, considering net protein utilization (NPU) as a biological reference method. Ten foods of vegetable origin and ten of animal origin, as well as eight mixtures of foods of vegetable and animal origin were studied. When all the foods were considered, a positive (r = 0.83) and highly significant correlation (p less than 0.001) between NPU and the amino acid score adjusted by digestibility was found. When the foods were separated according to their origin, this correlation was positive only for the foods of vegetable origin (r = 0.93) and statistically significant (p less than 0.001). Also, only in those foods were similar values found between NPU and amino acid score adjusted by digestibility, as well as in utilizable protein estimated considering both methods. Caution is required to interpret protein quality and utilizable protein values of foods of animal origin and mixtures of foods of vegetable and animal origin when the amino acid score method adjusted by digestibility, or NPU, are utilized.
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Nguyen, Nguyen Xuan; Sheingold, Steven H
2011-11-04
The indirect medical education (IME) and disproportionate share hospital (DSH) adjustments to Medicare's prospective payment rates for inpatient services are generally intended to compensate hospitals for patient care costs related to teaching activities and care of low income populations. These adjustments were originally established based on the statistical relationships between IME and DSH and hospital costs. Due to a variety of policy considerations, the legislated levels of these adjustments may have deviated over time from these "empirically justified levels," or simply, "empirical levels." In this paper, we estimate the empirical levels of IME and DSH using 2006 hospital data and 2009 Medicare final payment rules. Our analyses suggest that the empirical level for IME would be much smaller than under current law-about one-third to one-half. Our analyses also support the DSH adjustment prescribed by the Affordable Care Act of 2010 (ACA)--about one-quarter of the pre-ACA level. For IME, the estimates imply an increase in costs of 1.88% for each 10% increase in teaching intensity. For DSH, the estimates imply that costs would rise by 0.52% for each 10% increase in the low-income patient share for large urban hospitals. Public Domain.
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Quinn, Casey; Ma, Qiufei; Kudlac, Amber; Palmer, Stephen; Barber, Beth; Zhao, Zhongyun
2017-02-01
Advances in the treatment of metastatic melanoma have been achieved in recent years: immunotherapies and targeted therapies have demonstrated survival benefits over older agents such as granulocyte-macrophage colony-stimulating factor (GM-CSF), dacarbazine, and glycoprotein peptide vaccine (gp100) in pivotal phase 3 trials. It is important to compare therapies to guide the treatment decision-making process, and establishing the relationship between older agents can strengthen the networks of evidence for newer therapies. We report the outcome of an indirect comparison of GM-CSF, dacarbazine, and gp100 in metastatic melanoma through meta-analysis of absolute treatment effect. A systematic literature review identified trials for inclusion in the meta-analysis. A valid network meta-analysis was not feasible: treatment-specific meta-analysis was conducted. A published algorithm was used to adjust overall survival estimates from trials of GM-CSF, dacarbazine, and gp100 for heterogeneity in baseline prognostic factors. Survival estimates were compared in three patient groups: stage IIIB-IV M1c, stage IIIB-IV M1a, and stage IV M1b/c. One trial of GM-CSF, four of dacarbazine, and one of gp100 were included in the analysis. After adjusting for differences in baseline prognostic factors, median overall survival (OS) in all patient groups was longer for those receiving GM-CSF than for those receiving dacarbazine or gp100. The observed survival over time for GM-CSF was similar to the adjusted survival for dacarbazine and greater than for gp100 in all patient groups. The relative treatment effect of GM-CSF, dacarbazine, and gp100 has been reliably estimated by adjusting for differences in baseline prognostic factors. Results suggest that OS with GM-CSF is at least as good as with dacarbazine and greater than with gp100. Given the role of these agents as controls in phase 3 trials of new immunotherapies and targeted agents, these results can be used to contextualize the efficacy of newer therapies. Amgen Inc.
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Dijkstra, Frederika; van Doorn, Eva; Bijlsma, Maarten J.; Donker, Gé A.; de Lange, Marit M. A.; Cadenau, Laura M.; Hak, Eelko; Meijer, Adam
2017-01-01
Influenza vaccine effectiveness (IVE) varies over different influenza seasons and virus (sub)types/lineages. To assess the association between IVE and circulating influenza virus (sub)types/lineages, we estimated the overall and (sub)type specific IVE in the Netherlands. We conducted a test-negative case control study among subjects with influenza-like illness or acute respiratory tract infection consulting the Sentinel Practices over 11 influenza seasons (2003/2004 through 2013/2014) in the Netherlands. The adjusted IVE was estimated using generalized linear mixed modelling and multiple logistic regression. In seven seasons vaccine strains did not match the circulating viruses. Overall adjusted IVE was 40% (95% CI 18 to 56%) and 20% (95% CI -5 to 38%) when vaccine (partially)matched and mismatched the circulating viruses, respectively. When A(H3N2) was the predominant virus, IVE was 38% (95% CI 14 to 55%). IVE against infection with former seasonal A(H1N1) virus was 83% (95% CI 52 to 94%), and with B virus 67% (95% CI 55 to 76%). In conclusion IVE estimates were particularly low when vaccine mismatched the circulating viruses and A(H3N2) was the predominant influenza virus subtype. Tremendous effort is required to improve vaccine production procedure and to explore the factors that influence the IVE against A(H3N2) virus. PMID:28068386
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Silva Miguel, Luís; Rocha, Evangelista; Ferreira, Jorge
2013-01-01
To estimate the cost-effectiveness and cost-utility of dabigatran in the prevention of stroke and systemic embolism in patients with non-valvular atrial fibrillation in Portugal. A Markov model was used to simulate patients' clinical course, estimating the occurrence of ischemic and hemorrhagic stroke, transient ischemic attack, systemic embolism, myocardial infarction, and intra- and extracranial hemorrhage. The clinical parameters are based on the results of the RE-LY trial, which compared dabigatran with warfarin, and on a meta-analysis that estimated the risk of each event in patients treated with aspirin or with no antithrombotic therapy. Dabigatran provides an increase of 0.331 life years and 0.354 quality-adjusted life years for each patient. From a societal perspective, these clinical gains entail an additional expenditure of 2978 euros. Thus, the incremental cost is 9006 euros per life year gained and 8409 euros per quality-adjusted life year. The results show that dabigatran reduces the number of events, especially the most severe such as ischemic and hemorrhagic stroke, as well as their long-term sequelae. The expense of dabigatran is partially offset by lower event-related costs and by the fact that INR monitoring is unnecessary. It can thus be concluded that the use of dabigatran in clinical practice in Portugal is cost-effective. Copyright © 2013 Sociedade Portuguesa de Cardiologia. Published by Elsevier España. All rights reserved.
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Yeung, Kai; Li, Meng; Carlson, Josh J
2017-10-01
The rise in pharmaceutical expenditures in recent years has increased health care payer interest in ensuring good value for the money. Indication-based pricing (IBP) sets separate, indication-specific prices paid to the manufacturer according to the expected efficacy of a drug in each of its indications. IBP allows payers to consistently pay for value across indications. While promising, a limitation of IBP as originally conceived is that efficacy estimates are typically based on clinical trial data, which may differ from real-world effectiveness. An outcomes guarantee is a type of performance-based risk-sharing arrangement that adjusts payments according to prospectively tracked outcomes. We suggest that an outcomes guarantee contract, which has been used by some payers, may be adapted to achieve indication-based prices supported by real-world effectiveness. To illustrate the potential of an outcomes guarantee to achieve indication-based prices aligned with real-world value, using a case study of trastuzumab for the treatment of metastatic breast and advanced gastric cancers. We estimated costs and outcomes under traditional IBP (i.e., expected value IBP) and outcomes guarantee frameworks and calculated incremental cost-effectiveness ratios (ICERs) comparing treatment with and without trastuzumab. Efficacy data came from pivotal trials, whereas effectiveness data came from observational studies. We adjusted trastuzumab prices in order to achieve target ICERs of $150,000 per quality-adjusted life-year under each framework and for each indication. To achieve the ICER target under traditional IBP, the unit price of trastuzumab using efficacy evidence was adjusted for metastatic breast and advanced gastric cancers from an average sales price of $9.17 per mg to $3.50 per mg and $0.93 per mg, respectively. Under an outcomes guarantee, the unit price of trastuzumab using effectiveness evidence was adjusted for metastatic breast cancer and advanced gastric cancer to $8.66 per mg and $0.20 per mg, respectively. Like expected value IBP, outcomes guarantee contracts can also vary payment based on indication. In addition, an outcomes guarantee can also reduce uncertainty regarding effectiveness and better align payment with the actual value of a treatment. No funding supported this study. Carlson reports consulting fees from Genentech, Pfizer, and Seattle Genetics. The other authors have no conflicts of interest to disclose. Study concept and design were contributed by Carlson, Yeung, and Li. Yeung, Carlson, and Li collected and analyzed the data. The manuscript was written primarily by Yeung, along with Carlson and Li, and revised by all the authors.
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Body composition status and the risk of migraine: A meta-analysis.
Gelaye, Bizu; Sacco, Simona; Brown, Wendy J; Nitchie, Haley L; Ornello, Raffaele; Peterlin, B Lee
2017-05-09
To evaluate the association between migraine and body composition status as estimated based on body mass index and WHO physical status categories. Systematic electronic database searches were conducted for relevant studies. Two independent reviewers performed data extraction and quality appraisal. Odds ratios (OR) and confidence intervals (CI) were pooled using a random effects model. Significant values, weighted effect sizes, and tests of homogeneity of variance were calculated. A total of 12 studies, encompassing data from 288,981 unique participants, were included. The age- and sex-adjusted pooled risk of migraine in those with obesity was increased by 27% compared with those of normal weight (odds ratio [OR] 1.27; 95% confidence interval [CI] 1.16-1.37, p < 0.001) and remained increased after multivariate adjustments. Although the age- and sex-adjusted pooled migraine risk was increased in overweight individuals (OR 1.08; 95% CI 1.04, 1.12, p < 0.001), significance was lost after multivariate adjustments. The age- and sex-adjusted pooled risk of migraine in underweight individuals was marginally increased by 13% compared with those of normal weight (OR 1.13; 95% CI 1.02, 1.24, p < 0.001) and remained increased after multivariate adjustments. The current body of evidence shows that the risk of migraine is increased in obese and underweight individuals. Studies are needed to confirm whether interventions that modify obesity status decrease the risk of migraine. © 2017 American Academy of Neurology.
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Adaptive torque estimation of robot joint with harmonic drive transmission
NASA Astrophysics Data System (ADS)
Shi, Zhiguo; Li, Yuankai; Liu, Guangjun
2017-11-01
Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.
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Consequences of land-cover misclassification in models of impervious surface
McMahon, G.
2007-01-01
Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.
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Copas, Andrew; Glynn, Judith R; Bester, Andre; Nelson, Gill; Shearer, Stuart; Murray, Jill
2010-01-01
Objectives To estimate the effect of HIV infection on time off work. To provide baseline estimates for economic and actuarial models, and for evaluations of ART and other workplace interventions. Methods A retrospective cohort study of gold miners with known dates of seroconversion to HIV, and an HIV-negative comparison group, used routinely collected data to estimate the proportion of time off work by calendar period (1992–2002, prior to the introduction of ART), age, time since seroconversion and period before death. The authors calculated ORs for overall time off work and RR ratios (RRR, using multinomial logistic regression) for reasons off work relative to being at work. Results 1703 HIV-positive and 4859 HIV-negative men were followed for 34 424 person-years. HIV-positive miners spent a higher proportion of time off work than negative miners (20.7% vs 16.1%) due to greater medical and unauthorised absence. Compared with HIV-negative miners, overall time off work increased in the first 2 years after seroconversion (adjusted OR 1.40 (95% CI 1.36 to 1.45)) and then remained broadly stable for a number years, reaching 38.8% in the final year before death (adjusted OR 3.27, 95% CI 2.95 to 3.63). Absence for medical reasons showed the strongest link to HIV infection, increasing from an adjusted RRR of 2.66 (95% CI 2.45 to 2.90) for the first 2 years since seroconversion to 13.6 (95% CI 11.8 to 15.6) in the year prior to death. Conclusions Time off work provides a quantifiable measure of the effect of HIV on overall morbidity. HIV/AIDS affects both labour supply (increased time off work) and demand for health services (increased medical absence). The effects occur soon after seroconversion and stabilise before reaching very high levels in the period prior to death. Occupational health services are an important setting to identify HIV-infected men early. PMID:21115507
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Do case-mix adjusted nursing home reimbursements actually reflect costs? Minnesota's experience.
Nyman, J A; Connor, R A
1994-07-01
Some states have adopted Medicaid reimbursement systems that pay nursing homes according to patient type. These case-mix adjusted reimbursements are intended in part to eliminate the incentive in prospective systems to exclude less profitable patients. This study estimates the marginal costs of different patient types under Minnesota's case-mix system and compares them to their corresponding reimbursements. We find that estimated costs do not match reimbursement rates, again making some patient types less profitable than others. Further, in confirmation of our estimates, we find that the percentage change in patient days between 1986 and 1990 is explained by our profitability estimates.
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Federal Register 2010, 2011, 2012, 2013, 2014
2011-03-14
... dead discards as well as the amount of 2010 underharvest (of 2010 adjusted quota) allowed by ICCAT to... would adjust these base quotas for the 2012 fishing year based on the best estimate of dead discards and... early 2012). As described below, 160 mt is used as a proxy for dead discards based on the 2009 estimate...
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A demographic explanation for the recent rise in European fertility.
Bongaarts, John; Sobotka, Tomáš
2012-01-01
Between 1998 and 2008 European countries experienced the first continent-wide increase in the period total fertility rate (TFR) since the 1960s. After discussing period and cohort influences on fertility trends, we examine the role of tempo distortions of period fertility and different methods for removing them. We highlight the usefulness of a new indicator: the tempo- and parity-adjusted total fertility rate (TFRp*). This variant of the adjusted total fertility rate proposed by Bongaarts and Feeney also controls for the parity composition of the female population and provides more stable values than the indicators proposed in the past. Finally, we estimate levels and trends in tempo and parity distribution distortions in selected countries in Europe. Our analysis of period and cohort fertility indicators in the Czech Republic, Netherlands, Spain, and Sweden shows that the new adjusted measure gives a remarkable fit with the completed fertility of women in prime childbearing years in a given period, which suggests that it provides an accurate adjustment for tempo and parity composition distortions. Using an expanded dataset for ten countries, we demonstrate that adjusted fertility as measured by TFRp* remained nearly stable since the late 1990s. This finding implies that the recent upturns in the period TFR in Europe are largely explained by a decline in the pace of fertility postponement. Other tempo-adjusted fertility indicators have not indicated such a large role for the diminishing tempo effect in these TFR upturns. As countries proceed through their postponement transitions, tempo effects will decline further and eventually disappear, thus putting continued upward pressure on period fertility. However, such an upward trend may be obscured for a few years by the effects of economic recession.
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Marsh, Kimberly; Mahy, Mary; Salomon, Joshua A.; Hogan, Daniel R.
2014-01-01
Objective(s): To assess differences between HIV prevalence estimates derived from national population surveys and antenatal care (ANC) surveillance sites and to improve the calibration of ANC-derived estimates in Spectrum 2013 to more appropriately account for differences between these data. Design: Retrospective analysis of national population survey and ANC surveillance data from 25 countries with generalized epidemics in sub-Saharan Africa and 8 countries with concentrated epidemics. Methods: Adult national population survey and ANC surveillance HIV prevalence estimates were compared for all available national population survey data points for the years 1999–2012. For sub-Saharan Africa, a mixed-effects linear regression model determined whether the relationship between national population and ANC estimates was constant across surveys. A new calibration method was developed to incorporate national population survey data directly into the likelihood for HIV prevalence in countries with generalized epidemics. Results were used to develop default rules for adjusting ANC data for countries with no national population surveys. Results: ANC surveillance data typically overestimate population prevalence, although a wide variation, particularly in rural areas, is observed across countries and survey years. The new calibration method yields similar point estimates to previous approaches, but leads to an average 44% increase in the width of 95% uncertainty intervals. Conclusion: Important biases remain in ANC surveillance data for HIV prevalence. The new approach to model-fitting in Spectrum 2013 more appropriately accounts for this bias when producing national estimates in countries with generalized epidemics. In countries with concentrated epidemics, local sex ratios should be used to calibrate ANC surveillance estimates. PMID:25203158
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Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R
2016-12-01
: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Effect of distance-related heterogeneity on population size estimates from point counts
Efford, Murray G.; Dawson, Deanna K.
2009-01-01
Point counts are used widely to index bird populations. Variation in the proportion of birds counted is a known source of error, and for robust inference it has been advocated that counts be converted to estimates of absolute population size. We used simulation to assess nine methods for the conduct and analysis of point counts when the data included distance-related heterogeneity of individual detection probability. Distance from the observer is a ubiquitous source of heterogeneity, because nearby birds are more easily detected than distant ones. Several recent methods (dependent double-observer, time of first detection, time of detection, independent multiple-observer, and repeated counts) do not account for distance-related heterogeneity, at least in their simpler forms. We assessed bias in estimates of population size by simulating counts with fixed radius w over four time intervals (occasions). Detection probability per occasion was modeled as a half-normal function of distance with scale parameter sigma and intercept g(0) = 1.0. Bias varied with sigma/w; values of sigma inferred from published studies were often 50% for a 100-m fixed-radius count. More critically, the bias of adjusted counts sometimes varied more than that of unadjusted counts, and inference from adjusted counts would be less robust. The problem was not solved by using mixture models or including distance as a covariate. Conventional distance sampling performed well in simulations, but its assumptions are difficult to meet in the field. We conclude that no existing method allows effective estimation of population size from point counts.
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Real-time adjusting of rainfall estimates from commercial microwave links
NASA Astrophysics Data System (ADS)
Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch
2017-04-01
Urban stormwater predictions require reliable rainfall information with space-time resolution higher than commonly provided by standard rainfall monitoring networks of national weather services. Rainfall data from commercial microwave links (CMLs) could fill this gap. CMLs are line-of-sight radio connections widely used by cellular operators which operate at millimeter bands, where radio waves are attenuated by raindrops. Attenuation data of each single CML in the cellular network can be remotely accessed in (near) real-time with virtually arbitrary sampling frequency and convert to rainfall intensity. Unfortunately, rainfall estimates from CMLs can be substantially biased. Fencl et al., (2017), therefore, proposed adjusting method which enables to correct for this bias. They used rain gauge (RG) data from existing rainfall monitoring networks, which would have otherwise insufficient spatial and temporal resolution for urban rainfall monitoring when used alone without CMLs. In this investigation, we further develop the method to improve its performance in a real-time setting. First, a shortcoming of the original algorithm which delivers unreliable results at the beginning of a rainfall event is overcome by introducing model parameter prior distributions estimated from previous parameter realizations. Second, weights reflecting variance between RGs are introduced into cost function, which is minimized when optimizing model parameters. Finally, RG data used for adjusting are preprocessed by moving average filter. The performance of improved adjusting method is evaluated on four short CMLs (path length < 2 km) located in the small urban catchment (2.3 km2) in Prague-Letnany (CZ). The adjusted CMLs are compared to reference rainfall calculated from six RGs in the catchment. The suggested improvements of the method lead on average to 10% higher Nash-Sutcliffe efficiency coefficient (median value 0.85) for CML adjustment to hourly RG data. Reliability of CML rainfall estimates is especially improved at the beginning of rainfall events and during strong convective rainfalls, whereas performance during longer frontal rainfalls is almost unchanged. Our results clearly demonstrate that adjusting of CMLs to existing RGs represents a viable approach with great potential for real-time applications in stormwater management. This work was supported by the project of Czech Science Foundation (GACR) No.17-16389S. References: Fencl, M., Dohnal, M., Rieckermann, J. and Bareš, V.: Gauge-Adjusted Rainfall Estimates from Commercial Microwave Links, Hydrol Earth Syst. Sci., 2017 (accepted).
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Cordovilla-Guardia, Sergio; Fernández-Mondéjar, Enrique; Vilar-López, Raquel; Navas, Juan F; Portillo-Santamaría, Mónica; Rico-Martín, Sergio; Lardelli-Claret, Pablo
2017-01-01
Estimate the effectiveness of brief interventions in reducing trauma recidivism in hospitalized trauma patients who screened positive for alcohol and/or illicit drug use. Dynamic cohort study based on registry data from 1818 patients included in a screening and brief intervention program for alcohol and illicit drug use for hospitalized trauma patients. Three subcohorts emerged from the data analysis: patients who screened negative, those who screened positive and were offered brief intervention, and those who screened positive and were not offered brief intervention. Follow-up lasted from 10 to 52 months. Trauma-free survival, adjusted hazard rate ratios (aHRR) and adjusted incidence rate ratios (aIRR) were calculated, and complier average causal effect (CACE) analysis was used. We found a higher cumulative risk of trauma recidivism in the subcohort who screened positive. In this subcohort, an aHRR of 0.63 (95% CI: 0.41-0.95) was obtained for the group offered brief intervention compared to the group not offered intervention. CACE analysis yielded an estimated 52% reduction in trauma recidivism associated with the brief intervention. The brief intervention offered during hospitalization in trauma patients positive for alcohol and/or illicit drug use can halve the incidence of trauma recidivism.
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Fernández-Mondéjar, Enrique; Vilar-López, Raquel; Navas, Juan F.; Portillo-Santamaría, Mónica; Rico-Martín, Sergio; Lardelli-Claret, Pablo
2017-01-01
Objective Estimate the effectiveness of brief interventions in reducing trauma recidivism in hospitalized trauma patients who screened positive for alcohol and/or illicit drug use. Methods Dynamic cohort study based on registry data from 1818 patients included in a screening and brief intervention program for alcohol and illicit drug use for hospitalized trauma patients. Three subcohorts emerged from the data analysis: patients who screened negative, those who screened positive and were offered brief intervention, and those who screened positive and were not offered brief intervention. Follow-up lasted from 10 to 52 months. Trauma-free survival, adjusted hazard rate ratios (aHRR) and adjusted incidence rate ratios (aIRR) were calculated, and complier average causal effect (CACE) analysis was used. Results We found a higher cumulative risk of trauma recidivism in the subcohort who screened positive. In this subcohort, an aHRR of 0.63 (95% CI: 0.41–0.95) was obtained for the group offered brief intervention compared to the group not offered intervention. CACE analysis yielded an estimated 52% reduction in trauma recidivism associated with the brief intervention. Conclusion The brief intervention offered during hospitalization in trauma patients positive for alcohol and/or illicit drug use can halve the incidence of trauma recidivism. PMID:28813444
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Manyema, Mercy; Veerman, Lennert J; Tugendhaft, Aviva; Labadarios, Demetre; Hofman, Karen J
2016-05-31
Stroke poses a growing human and economic burden in South Africa. Excess sugar consumption, especially from sugar-sweetened beverages (SSBs), has been associated with increased obesity and stroke risk. Research shows that price increases for SSBs can influence consumption and modelling evidence suggests that taxing SSBs has the potential to reduce obesity and related diseases. This study estimates the potential impact of an SSB tax on stroke-related mortality, costs and health-adjusted life years in South Africa. A proportional multi-state life table-based model was constructed in Microsoft Excel (2010). We used consumption data from the 2012 South African National Health and Nutrition Examination Survey, previously published own and cross price elasticities of SSBs and energy balance equations to estimate changes in daily energy intake and BMI arising from increased SSB prices. Stroke relative risk, and prevalent years lived with disability estimates from the Global Burden of Disease Study and modelled disease epidemiology estimates from a previous study, were used to estimate the effect of the BMI changes on the burden of stroke. Our model predicts that an SSB tax may avert approximately 72 000 deaths, 550 000 stroke-related health-adjusted life years and over ZAR5 billion, (USD400 million) in health care costs over 20 years (USD296-576 million). Over 20 years, the number of incident stroke cases may be reduced by approximately 85 000 and prevalent cases by about 13 000. Fiscal policy has the potential, as part of a multi-faceted approach, to mitigate the growing burden of stroke in South Africa and contribute to the achievement of the target set by the Department of Health to reduce relative premature mortality (less than 60 years) from non-communicable diseases by the year 2020.
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Jayasinghe, Sanjay; Macartney, Kristine
2013-01-30
Hospital discharge records and laboratory data have shown a substantial early impact from the rotavirus vaccination program that commenced in 2007 in Australia. However, these assessments are affected by the validity and reliability of hospital discharge coding and stool testing to measure the true incidence of hospitalised disease. The aim of this study was to assess the validity of these data sources for disease estimation, both before and after, vaccine introduction. All hospitalisations at a major paediatric centre in children aged <5 years from 2000 to 2009 containing acute gastroenteritis (AGE) ICD 10 AM diagnosis codes were linked to hospital laboratory stool testing data. The validity of the rotavirus-specific diagnosis code (A08.0) and the incidence of hospitalisations attributable to rotavirus by both direct estimation and with adjustments for non-testing and miscoding were calculated for pre- and post-vaccination periods. A laboratory record of stool testing was available for 36% of all AGE hospitalisations (n=4948) the rotavirus code had high specificity (98.4%; 95% CI, 97.5-99.1%) and positive predictive value (96.8%; 94.8-98.3%), and modest sensitivity (61.6%; 58-65.1%). Of all rotavirus test positive hospitalisations only a third had a rotavirus code. The estimated annual average number of rotavirus hospitalisations, following adjustment for non-testing and miscoding was 5- and 6-fold higher than identified, respectively, from testing and coding alone. Direct and adjusted estimates yielded similar percentage reductions in annual average rotavirus hospitalisations of over 65%. Due to the limited use of stool testing and poor sensitivity of the rotavirus-specific diagnosis code routine hospital discharge and laboratory data substantially underestimate the true incidence of rotavirus hospitalisations and absolute vaccine impact. However, this data can still be used to monitor vaccine impact as the effects of miscoding and under-testing appear to be comparable between pre and post vaccination periods. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Geodesy in Antarctica: A pilot study based on the TAMDEF GPS network, Victoria Land, Antarctica
NASA Astrophysics Data System (ADS)
Vazquez Becerra, Guadalupe Esteban
The objective of the research presented in this dissertation is a combination of practical and theoretical problems to investigate unique aspects of GPS (Global Positioning System) geodesy in Antarctica. This is derived from a complete analysis of a GPS network called TAMDEF (Trans Antarctic Mountains Deformation), located in Victoria Land, Antarctica. In order to permit access to the International Terrestrial Reference Frame (ITRF), the McMurdo (MCM4) IGS (The International GNSS Service for Geodynamics, formerly the International GPS Service) site was adopted as part of the TAMDEF network. The following scientific achievements obtained from the cited analysis will be discussed as follows: (1) The GPS data processing for the TAMDEF network relied on the PAGES (Program for Adjustment of GPS Ephemerides) software that uses the double-differenced iono-free linear combination, which helps removing a big partial of bias (mm level) in the final positioning. (2) To validate the use of different antenna types in TAMDEF, an antenna testing experiment was conducted using the National Geodetic Survey (NGS) antenna calibration data, appropriate for each antenna type. Sub-daily and daily results from the antenna testing are at the sub-millimeter level, based on the fact that 24-hour solutions were used to average any possible bias. (3) A potential contributor that might have an impact on the TAMDEF stations positioning is the pseudorange multipath effect; thus, the root mean squared variations were estimated and analyzed in order to identify the most and least affected sites. MCM4 was found to be the site with highest multipath, and this is not good at all, since MCM4 is the primary ITRF access point for this part of Antarctica. Additionally, results from the pseudorange multipath can be used for further data cleaning to improve positioning results. (4) The Ocean Tide Modeling relied on the use of two models: CATS02.01 (Circum Antarctic Tidal Simulation) and TPXO6.2 (TOPEX/Poseidon) to investigate which model suits the Antarctic conditions best and its effect on the vertical coordinate component at the TAMDEF sites. (5) The scatter for the time-series results of the coordinate components for the TAMDEF sites are smaller when processed with respect to the Antarctic tectonic plate (Case I), in comparison with the other tectonic plates outside Antarctica (Case II-IV). Also, the seasonal effect due to the time-series seen in the TAMDEF sites with longer data span are site dependent; thus, data processing is not the reason for these effects. (6) Furthermore, the results coming from a homogeneous global network with coordinates referred and transformed to the ITRF2000 at epoch 2005.5 reflect the quality of the solution, obtained when processing TAMDEF network data with respect to the Antarctic tectonic plate. (7) An optimal data reduction strategy was developed, based on three different troposphere models and mapping functions, tested and used to estimate the total wet zenith delay (TWZD) which later was transformed to precipitable water vapor (PWV). PWV was estimated from GPS measurements and validated with a numerical weather model, AMPS (Antarctic Mesoscale Prediction System) and radiosonde PWV. Additionally, to validate the TWZD estimates at the MCM4 site before their conversion into the GPS PWV, these estimates were directly compared to TWZD computed by the CDDIS (Crustal Dynamics Data Information System) analysis center. (8) The results from the Least-Squares adjustment with Stochastic Constraints (SCLESS) as performed with PAGES are very comparable (mm-level) to those obtained from the alternative adjustment approaches: MINOLESS (Minimum-Norm Least-Squares adjustment); Partial-MINOLESS (Partial Minimum-Norm Least-Squares adjustment), and BLIMPBE (Best Linear Minimum Partial-Bias Estimation). Based on the applied network adjustment models within the Antarctic tectonic plate (Case I), it can be demonstrated that the GPS data used are clean of bias after proper care has been taken of ionosphere, troposphere, multipath, and some other sources that affect GPS positioning. Overall, it can be concluded that no suspected of bias was present in the obtained results, thus, GPS is indeed capable of capturing the signal which can be used for further geophysical interpretation within Antarctica.
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Software cost/resource modeling: Deep space network software cost estimation model
NASA Technical Reports Server (NTRS)
Tausworthe, R. J.
1980-01-01
A parametric software cost estimation model prepared for JPL deep space network (DSN) data systems implementation tasks is presented. The resource estimation model incorporates principles and data from a number of existing models, such as those of the General Research Corporation, Doty Associates, IBM (Walston-Felix), Rome Air Force Development Center, University of Maryland, and Rayleigh-Norden-Putnam. The model calibrates task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software lifecycle statistics. The estimation model output scales a standard DSN work breakdown structure skeleton, which is then input to a PERT/CPM system, producing a detailed schedule and resource budget for the project being planned.
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Willingness to pay for non angler recreation at the lower Snake River reservoirs
McKean, J.R.; Johnson, D.; Taylor, R.G.; Johnson, Richard L.
2005-01-01
This study applied the travel cost method to estimate demand for non angler recreation at the impounded Snake River in eastern Washington. Net value per person per recreation trip is estimated for the full non angler sample and separately for camping, boating, water-skiing, and swimming/picnicking. Certain recreation activities would be reduced or eliminated and new activities would be added if the dams were breached to protect endangered salmon and steelhead. The effect of breaching on non angling benefits was found by subtracting our benefits estimate from the projected non angling benefits with breaching. Major issues in demand model specification and definition of the price variables are discussed. The estimation method selected was truncated negative binomial regression with adjustment for self selection bias.
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Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin
Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.
2011-01-01
In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.
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Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin
Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.
2011-01-01
In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.
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Estimating pregnancy-related mortality from census data: experience in Latin America
Queiroz, Bernardo L; Wong, Laura; Plata, Jorge; Del Popolo, Fabiana; Rosales, Jimmy; Stanton, Cynthia
2009-01-01
Abstract Objective To assess the feasibility of measuring maternal mortality in countries lacking accurate birth and death registration through national population censuses by a detailed evaluation of such data for three Latin American countries. Methods We used established demographic techniques, including the general growth balance method, to evaluate the completeness and coverage of the household death data obtained through population censuses. We also compared parity to cumulative fertility data to evaluate the coverage of recent household births. After evaluating the data and adjusting it as necessary, we calculated pregnancy-related mortality ratios (PRMRs) per 100 000 live births and used them to estimate maternal mortality. Findings The PRMRs for Honduras (2001), Nicaragua (2005) and Paraguay (2002) were 168, 95 and 178 per 100 000 live births, respectively. Surprisingly, evaluation of the data for Nicaragua and Paraguay showed overreporting of adult deaths, so a downward adjustment of 20% to 30% was required. In Honduras, the number of adult female deaths required substantial upward adjustment. The number of live births needed minimal adjustment. The adjusted PRMR estimates are broadly consistent with existing estimates of maternal mortality from various data sources, though the comparison varies by source. Conclusion Census data can be used to measure pregnancy-related mortality as a proxy for maternal mortality in countries with poor death registration. However, because our data were obtained from countries with reasonably good statistical systems and literate populations, we cannot be certain the methods employed in the study will be equally useful in more challenging environments. Our data evaluation and adjustment methods worked, but with considerable uncertainty. Ways of quantifying this uncertainty are needed. PMID:19551237