Using Case-Mix Adjustment Methods To Measure the Effectiveness of Substance Abuse Treatment: Three Examples Using Client Employment Outcomes.

ERIC Educational Resources Information Center

Koenig, Lane; Fields, Errol L.; Dall, Timothy M.; Ameen, Ansari Z.; Harwood, Henrick J.

This report demonstrates three applications of case-mix methods using regression analysis. The results are used to assess the relative effectiveness of substance abuse treatment providers. The report also examines the ability of providers to improve client employment outcomes, an outcome domain relatively unexamined in the assessment of provider…

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

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.

Nursing home performance under case-mix reimbursement: responding to heavy-care incentives and market changes.

PubMed Central

Davis, M A; Freeman, J W; Kirby, E C

1998-01-01

OBJECTIVE: To examine the effect of case mix-adjusted reimbursement policy and market factors on nursing home performance. DATA SOURCES AND STUDY SETTING: Data from Medicaid certification inspection surveys, Medicaid cost reports, and the Kentucky State Center for Health Statistics for the years 1989 and 1991, to examine changes in nursing home performance stemming from the adoption of case mix-adjusted reimbursement in 1990. STUDY DESIGN: In addition to cross-sectional regressions, a first-difference approach to fixed-effects regression analyses was employed to control for facility differences that were essentially fixed during the survey years and to estimate the effects of time-varying predictors on changes in facility expenditures, efficiency, and profitability. PRINCIPAL FINDINGS: Facilities that increased the proportion of Medicaid residents and eliminated excess capacity experienced higher profitability gains during the beginning phase of case-mix reimbursement. Having a heavy-care resident population was positively related to expenditures prior to reimbursement reform, and it was negatively related to expenditures after the case-mix reimbursement policy was introduced. While facility-level changes in case mix had no reliable influence on costs or profits, nursing homes showing an increased prevalence of poor-quality nursing practices exhibited increases in efficiency and profitability. At the market level, reductions in excess or empty nursing home beds were accompanied by a significant growth in home health services. Moreover, nursing homes located in markets with expanding home health services exhibited higher increases in costs per case-mix unit. CONCLUSIONS: Characteristics of the reimbursement system appear to reward a cost minimization orientation with potentially detrimental effects on quality of care. These effects, exacerbated by a supply-constrained market, may be mitigated by policies that encourage the expansion of home health service availability. PMID:9776938

Nursing home performance under case-mix reimbursement: responding to heavy-care incentives and market changes.

PubMed

Davis, M A; Freeman, J W; Kirby, E C

1998-10-01

To examine the effect of case mix-adjusted reimbursement policy and market factors on nursing home performance. Data from Medicaid certification inspection surveys, Medicaid cost reports, and the Kentucky State Center for Health Statistics for the years 1989 and 1991, to examine changes in nursing home performance stemming from the adoption of case mix-adjusted reimbursement in 1990. In addition to cross-sectional regressions, a first-difference approach to fixed-effects regression analyses was employed to control for facility differences that were essentially fixed during the survey years and to estimate the effects of time-varying predictors on changes in facility expenditures, efficiency, and profitability. Facilities that increased the proportion of Medicaid residents and eliminated excess capacity experienced higher profitability gains during the beginning phase of case-mix reimbursement. Having a heavy-care resident population was positively related to expenditures prior to reimbursement reform, and it was negatively related to expenditures after the case-mix reimbursement policy was introduced. While facility-level changes in case mix had no reliable influence on costs or profits, nursing homes showing an increased prevalence of poor-quality nursing practices exhibited increases in efficiency and profitability. At the market level, reductions in excess or empty nursing home beds were accompanied by a significant growth in home health services. Moreover, nursing homes located in markets with expanding home health services exhibited higher increases in costs per case-mix unit. Characteristics of the reimbursement system appear to reward a cost minimization orientation with potentially detrimental effects on quality of care. These effects, exacerbated by a supply-constrained market, may be mitigated by policies that encourage the expansion of home health service availability.

Developing a case mix classification for child and adolescent mental health services: the influence of presenting problems, complexity factors and service providers on number of appointments.

PubMed

Martin, Peter; Davies, Roger; Macdougall, Amy; Ritchie, Benjamin; Vostanis, Panos; Whale, Andy; Wolpert, Miranda

2017-09-01

Case-mix classification is a focus of international attention in considering how best to manage and fund services, by providing a basis for fairer comparison of resource utilization. Yet there is little evidence of the best ways to establish case mix for child and adolescent mental health services (CAMHS). To develop a case mix classification for CAMHS that is clinically meaningful and predictive of number of appointments attended and to investigate the influence of presenting problems, context and complexity factors and provider variation. We analysed 4573 completed episodes of outpatient care from 11 English CAMHS. Cluster analysis, regression trees and a conceptual classification based on clinical best practice guidelines were compared regarding their ability to predict number of appointments, using mixed effects negative binomial regression. The conceptual classification is clinically meaningful and did as well as data-driven classifications in accounting for number of appointments. There was little evidence for effects of complexity or context factors, with the possible exception of school attendance problems. Substantial variation in resource provision between providers was not explained well by case mix. The conceptually-derived classification merits further testing and development in the context of collaborative decision making.

The Calibration of AVHRR/3 Visible Dual Gain Using Meteosat-8 as a MODIS Calibration Transfer Medium

NASA Technical Reports Server (NTRS)

Avey, Lance; Garber, Donald; Nguyen, Louis; Minnis, Patrick

2007-01-01

This viewgraph presentation reviews the NOAA-17 AVHRR visible channels calibrated against MET-8/MODIS using dual gain regression methods. The topics include: 1) Motivation; 2) Methodology; 3) Dual Gain Regression Methods; 4) Examples of Regression methods; 5) AVHRR/3 Regression Strategy; 6) Cross-Calibration Method; 7) Spectral Response Functions; 8) MET8/NOAA-17; 9) Example of gain ratio adjustment; 10) Effect of mixed low/high count FOV; 11) Monitor dual gains over time; and 12) Conclusions

Factors associated with parasite dominance in fishes from Brazil.

PubMed

Amarante, Cristina Fernandes do; Tassinari, Wagner de Souza; Luque, Jose Luis; Pereira, Maria Julia Salim

2016-06-14

The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Wagler, Amy E.

2014-01-01

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

Modeling containment of large wildfires using generalized linear mixed-model analysis

Treesearch

Mark Finney; Isaac C. Grenfell; Charles W. McHugh

2009-01-01

Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rupšys, P.

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

PubMed

Zhao, Xin; Han, Meng; Ding, Lili; Calin, Adrian Cantemir

2018-01-01

The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neural network (MIDAS-BP model) to forecast carbon dioxide emissions. Such analysis uses mixed frequency data to study the effects of quarterly economic growth on annual carbon dioxide emissions. The forecasting ability of MIDAS-BP is remarkably better than MIDAS, ordinary least square (OLS), polynomial distributed lags (PDL), autoregressive distributed lags (ADL), and auto-regressive moving average (ARMA) models. The MIDAS-BP model is suitable for forecasting carbon dioxide emissions for both the short and longer term. This research is expected to influence the methodology for forecasting carbon dioxide emissions by improving the forecast accuracy. Empirical results show that economic growth has both negative and positive effects on carbon dioxide emissions that last 15 quarters. Carbon dioxide emissions are also affected by their own change within 3 years. Therefore, there is a need for policy makers to explore an alternative way to develop the economy, especially applying new energy policies to establish a low carbon society.

The Bayesian group lasso for confounded spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

[Primary branch size of Pinus koraiensis plantation: a prediction based on linear mixed effect model].

PubMed

Dong, Ling-Bo; Liu, Zhao-Gang; Li, Feng-Ri; Jiang, Li-Chun

2013-09-01

By using the branch analysis data of 955 standard branches from 60 sampled trees in 12 sampling plots of Pinus koraiensis plantation in Mengjiagang Forest Farm in Heilongjiang Province of Northeast China, and based on the linear mixed-effect model theory and methods, the models for predicting branch variables, including primary branch diameter, length, and angle, were developed. Considering tree effect, the MIXED module of SAS software was used to fit the prediction models. The results indicated that the fitting precision of the models could be improved by choosing appropriate random-effect parameters and variance-covariance structure. Then, the correlation structures including complex symmetry structure (CS), first-order autoregressive structure [AR(1)], and first-order autoregressive and moving average structure [ARMA(1,1)] were added to the optimal branch size mixed-effect model. The AR(1) improved the fitting precision of branch diameter and length mixed-effect model significantly, but all the three structures didn't improve the precision of branch angle mixed-effect model. In order to describe the heteroscedasticity during building mixed-effect model, the CF1 and CF2 functions were added to the branch mixed-effect model. CF1 function improved the fitting effect of branch angle mixed model significantly, whereas CF2 function improved the fitting effect of branch diameter and length mixed model significantly. Model validation confirmed that the mixed-effect model could improve the precision of prediction, as compare to the traditional regression model for the branch size prediction of Pinus koraiensis plantation.

Robust, Adaptive Functional Regression in Functional Mixed Model Framework.

PubMed

Zhu, Hongxiao; Brown, Philip J; Morris, Jeffrey S

2011-09-01

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this paper, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large data sets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g. images), and using other invertible transformations as alternatives to wavelets.

Robust, Adaptive Functional Regression in Functional Mixed Model Framework

PubMed Central

Zhu, Hongxiao; Brown, Philip J.; Morris, Jeffrey S.

2012-01-01

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this paper, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large data sets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g. images), and using other invertible transformations as alternatives to wavelets. PMID:22308015

Applications of MIDAS regression in analysing trends in water quality

NASA Astrophysics Data System (ADS)

Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

2014-04-01

We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

The nonlinear relations of the approximate number system and mathematical language to early mathematics development.

PubMed

Purpura, David J; Logan, Jessica A R

2015-12-01

Both mathematical language and the approximate number system (ANS) have been identified as strong predictors of early mathematics performance. Yet, these relations may be different depending on a child's developmental level. The purpose of this study was to evaluate the relations between these domains across different levels of ability. Participants included 114 children who were assessed in the fall and spring of preschool on a battery of academic and cognitive tasks. Children were 3.12 to 5.26 years old (M = 4.18, SD = .58) and 53.6% were girls. Both mixed-effect and quantile regressions were conducted. The mixed-effect regressions indicated that mathematical language, but not the ANS, nor other cognitive domains, predicted mathematics performance. However, the quantile regression analyses revealed a more nuanced relation among domains. Specifically, it was found that mathematical language and the ANS predicted mathematical performance at different points on the ability continuum. These dual nonlinear relations indicate that different mechanisms may enhance mathematical acquisition dependent on children's developmental abilities. (c) 2015 APA, all rights reserved).

Growth and inactivation of Salmonella at low refrigerated storage temperatures and thermal inactivation on raw chicken meat and laboratory media: mixed effect meta-analysis.

PubMed

Smadi, Hanan; Sargeant, Jan M; Shannon, Harry S; Raina, Parminder

2012-12-01

Growth and inactivation regression equations were developed to describe the effects of temperature on Salmonella concentration on chicken meat for refrigerated temperatures (⩽10°C) and for thermal treatment temperatures (55-70°C). The main objectives were: (i) to compare Salmonella growth/inactivation in chicken meat versus laboratory media; (ii) to create regression equations to estimate Salmonella growth in chicken meat that can be used in quantitative risk assessment (QRA) modeling; and (iii) to create regression equations to estimate D-values needed to inactivate Salmonella in chicken meat. A systematic approach was used to identify the articles, critically appraise them, and pool outcomes across studies. Growth represented in density (Log10CFU/g) and D-values (min) as a function of temperature were modeled using hierarchical mixed effects regression models. The current meta-analysis analysis found a significant difference (P⩽0.05) between the two matrices - chicken meat and laboratory media - for both growth at refrigerated temperatures and inactivation by thermal treatment. Growth and inactivation were significantly influenced by temperature after controlling for other variables; however, no consistent pattern in growth was found. Validation of growth and inactivation equations against data not used in their development is needed. Copyright © 2012 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

The value of a statistical life: a meta-analysis with a mixed effects regression model.

PubMed

Bellavance, François; Dionne, Georges; Lebeau, Martin

2009-03-01

The value of a statistical life (VSL) is a very controversial topic, but one which is essential to the optimization of governmental decisions. We see a great variability in the values obtained from different studies. The source of this variability needs to be understood, in order to offer public decision-makers better guidance in choosing a value and to set clearer guidelines for future research on the topic. This article presents a meta-analysis based on 39 observations obtained from 37 studies (from nine different countries) which all use a hedonic wage method to calculate the VSL. Our meta-analysis is innovative in that it is the first to use the mixed effects regression model [Raudenbush, S.W., 1994. Random effects models. In: Cooper, H., Hedges, L.V. (Eds.), The Handbook of Research Synthesis. Russel Sage Foundation, New York] to analyze studies on the value of a statistical life. We conclude that the variability found in the values studied stems in large part from differences in methodologies.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

Creep analysis of silicone for podiatry applications.

PubMed

Janeiro-Arocas, Julia; Tarrío-Saavedra, Javier; López-Beceiro, Jorge; Naya, Salvador; López-Canosa, Adrián; Heredia-García, Nicolás; Artiaga, Ramón

2016-10-01

This work shows an effective methodology to characterize the creep-recovery behavior of silicones before their application in podiatry. The aim is to characterize, model and compare the creep-recovery properties of different types of silicone used in podiatry orthotics. Creep-recovery phenomena of silicones used in podiatry orthotics is characterized by dynamic mechanical analysis (DMA). Silicones provided by Herbitas are compared by observing their viscoelastic properties by Functional Data Analysis (FDA) and nonlinear regression. The relationship between strain and time is modeled by fixed and mixed effects nonlinear regression to compare easily and intuitively podiatry silicones. Functional ANOVA and Kohlrausch-Willians-Watts (KWW) model with fixed and mixed effects allows us to compare different silicones observing the values of fitting parameters and their physical meaning. The differences between silicones are related to the variations of breadth of creep-recovery time distribution and instantaneous deformation-permanent strain. Nevertheless, the mean creep-relaxation time is the same for all the studied silicones. Silicones used in palliative orthoses have higher instantaneous deformation-permanent strain and narrower creep-recovery distribution. The proposed methodology based on DMA, FDA and nonlinear regression is an useful tool to characterize and choose the proper silicone for each podiatry application according to their viscoelastic properties. Copyright © 2016 Elsevier Ltd. All rights reserved.

The use of cognitive ability measures as explanatory variables in regression analysis.

PubMed

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2012-12-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

Development, Discouragement, or Diversion? New Evidence on the Effects of College Remediation Policy

ERIC Educational Resources Information Center

Scott-Clayton, Judith; Rodriguez, Olga

2015-01-01

Half of all college students will enroll in remedial coursework but evidence of its effectiveness is mixed. Using a regression-discontinuity design with data from a large urban community college system, we make three contributions. First, we articulate three alternative hypotheses regarding the potential impacts of remediation. Second, in addition…

Dynamic prediction in functional concurrent regression with an application to child growth.

PubMed

Leroux, Andrew; Xiao, Luo; Crainiceanu, Ciprian; Checkley, William

2018-04-15

In many studies, it is of interest to predict the future trajectory of subjects based on their historical data, referred to as dynamic prediction. Mixed effects models have traditionally been used for dynamic prediction. However, the commonly used random intercept and slope model is often not sufficiently flexible for modeling subject-specific trajectories. In addition, there may be useful exposures/predictors of interest that are measured concurrently with the outcome, complicating dynamic prediction. To address these problems, we propose a dynamic functional concurrent regression model to handle the case where both the functional response and the functional predictors are irregularly measured. Currently, such a model cannot be fit by existing software. We apply the model to dynamically predict children's length conditional on prior length, weight, and baseline covariates. Inference on model parameters and subject-specific trajectories is conducted using the mixed effects representation of the proposed model. An extensive simulation study shows that the dynamic functional regression model provides more accurate estimation and inference than existing methods. Methods are supported by fast, flexible, open source software that uses heavily tested smoothing techniques. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Using mixed treatment comparisons and meta-regression to perform indirect comparisons to estimate the efficacy of biologic treatments in rheumatoid arthritis.

PubMed

Nixon, R M; Bansback, N; Brennan, A

2007-03-15

Mixed treatment comparison (MTC) is a generalization of meta-analysis. Instead of the same treatment for a disease being tested in a number of studies, a number of different interventions are considered. Meta-regression is also a generalization of meta-analysis where an attempt is made to explain the heterogeneity between the treatment effects in the studies by regressing on study-level covariables. Our focus is where there are several different treatments considered in a number of randomized controlled trials in a specific disease, the same treatment can be applied in several arms within a study, and where differences in efficacy can be explained by differences in the study settings. We develop methods for simultaneously comparing several treatments and adjusting for study-level covariables by combining ideas from MTC and meta-regression. We use a case study from rheumatoid arthritis. We identified relevant trials of biologic verses standard therapy or placebo and extracted the doses, comparators and patient baseline characteristics. Efficacy is measured using the log odds ratio of achieving six-month ACR50 responder status. A random-effects meta-regression model is fitted which adjusts the log odds ratio for study-level prognostic factors. A different random-effect distribution on the log odds ratios is allowed for each different treatment. The odds ratio is found as a function of the prognostic factors for each treatment. The apparent differences in the randomized trials between tumour necrosis factor alpha (TNF- alpha) antagonists are explained by differences in prognostic factors and the analysis suggests that these drugs as a class are not different from each other. Copyright (c) 2006 John Wiley & Sons, Ltd.

Penalized nonparametric scalar-on-function regression via principal coordinates

PubMed Central

Reiss, Philip T.; Miller, David L.; Wu, Pei-Shien; Hua, Wen-Yu

2016-01-01

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This paper introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive modeling software, allows for fast optimal tuning parameter selection and for extensions to multiple functional predictors, exponential family-valued responses, and mixed-effects models. In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model. PMID:29217963

The Effects of Baseline Estimation on the Reliability, Validity, and Precision of CBM-R Growth Estimates

ERIC Educational Resources Information Center

Van Norman, Ethan R.; Christ, Theodore J.; Zopluoglu, Cengiz

2013-01-01

This study examined the effect of baseline estimation on the quality of trend estimates derived from Curriculum Based Measurement of Oral Reading (CBM-R) progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for schedules ranging from 6-20 weeks for datasets with high and low…

Multivariate statistical approach to estimate mixing proportions for unknown end members

USGS Publications Warehouse

Valder, Joshua F.; Long, Andrew J.; Davis, Arden D.; Kenner, Scott J.

2012-01-01

A multivariate statistical method is presented, which includes principal components analysis (PCA) and an end-member mixing model to estimate unknown end-member hydrochemical compositions and the relative mixing proportions of those end members in mixed waters. PCA, together with the Hotelling T2 statistic and a conceptual model of groundwater flow and mixing, was used in selecting samples that best approximate end members, which then were used as initial values in optimization of the end-member mixing model. This method was tested on controlled datasets (i.e., true values of estimates were known a priori) and found effective in estimating these end members and mixing proportions. The controlled datasets included synthetically generated hydrochemical data, synthetically generated mixing proportions, and laboratory analyses of sample mixtures, which were used in an evaluation of the effectiveness of this method for potential use in actual hydrological settings. For three different scenarios tested, correlation coefficients (R2) for linear regression between the estimated and known values ranged from 0.968 to 0.993 for mixing proportions and from 0.839 to 0.998 for end-member compositions. The method also was applied to field data from a study of end-member mixing in groundwater as a field example and partial method validation.

Testing homogeneity in Weibull-regression models.

PubMed

Bolfarine, Heleno; Valença, Dione M

2005-10-01

In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.

The Effects of Social Capital Elements on Job Satisfaction and Motivation Levels of Teachers

ERIC Educational Resources Information Center

Boydak Özan, Mukadder; Yavuz Özdemir, Tuncay; Yaras, Zübeyde

2017-01-01

The purpose of this study is to examine the effects of social capital elements' on job satisfaction and motivation levels of teachers. The mixed method was used in the study. The quantitative data were analyzed through Correlation and Multiple Regression analyses. An interview form developed by the researchers was used for analyzing the…

OPC modeling by genetic algorithm

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Tsay, C. S.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.; Lin, B. J.

2005-05-01

Optical proximity correction (OPC) is usually used to pre-distort mask layouts to make the printed patterns as close to the desired shapes as possible. For model-based OPC, a lithographic model to predict critical dimensions after lithographic processing is needed. The model is usually obtained via a regression of parameters based on experimental data containing optical proximity effects. When the parameters involve a mix of the continuous (optical and resist models) and the discrete (kernel numbers) sets, the traditional numerical optimization method may have difficulty handling model fitting. In this study, an artificial-intelligent optimization method was used to regress the parameters of the lithographic models for OPC. The implemented phenomenological models were constant-threshold models that combine diffused aerial image models with loading effects. Optical kernels decomposed from Hopkin"s equation were used to calculate aerial images on the wafer. Similarly, the numbers of optical kernels were treated as regression parameters. This way, good regression results were obtained with different sets of optical proximity effect data.

Modeling stream network-scale variation in coho salmon overwinter survival and smolt size

EPA Science Inventory

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over ...

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

The use of cognitive ability measures as explanatory variables in regression analysis

PubMed Central

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2015-01-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual’s wage, or a decision such as an individual’s education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score, constructed via standard psychometric practice from individuals’ responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a “mixed effects structural equations” (MESE) model, may be more appropriate in many circumstances. PMID:26998417

Regression analysis using dependent Polya trees.

PubMed

Schörgendorfer, Angela; Branscum, Adam J

2013-11-30

Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Effects of morphological Family Size for young readers.

PubMed

Perdijk, Kors; Schreuder, Robert; Baayen, R Harald; Verhoeven, Ludo

2012-09-01

Dutch children, from the second and fourth grade of primary school, were each given a visual lexical decision test on 210 Dutch monomorphemic words. After removing words not recognized by a majority of the younger group, (lexical) decisions were analysed by mixed-model regression methods to see whether morphological Family Size influenced decision times over and above several other covariates. The effect of morphological Family Size on decision time was mixed: larger families led to significantly faster decision times for the second graders but not for the fourth graders. Since facilitative effects on decision times had been found for adults, we offer a developmental account to explain the absence of an effect of Family Size on decision times for fourth graders. ©2011 The British Psychological Society.

Do School Budgets Matter? The Effect of Budget Referenda on Student Dropout Rates

ERIC Educational Resources Information Center

Lee, Kyung-Gon; Polachek, Solomon W.

2018-01-01

This paper analyzes how changes in school expenditures affect dropout rates based on data from 466 school districts in New York during the 2003/04 to the 2007/08 school years. Past traditional regression approaches show mixed results in part because school expenditures are likely endogenous, so that one cannot disentangle cause and effect. The…

Development, Discouragement, or Diversion? New Evidence on the Effects of College Remediation. NBER Working Paper No. 18328

ERIC Educational Resources Information Center

Scott-Clayton, Judith; Rodriguez, Olga

2012-01-01

Half of all college students take at least one remedial course as part of their postsecondary experience, despite mixed evidence on the effectiveness of this intervention. Using a regression-discontinuity design with data from a large urban community college system, we extend the research on remediation in three ways. First, we articulate three…

Solving large test-day models by iteration on data and preconditioned conjugate gradient.

PubMed

Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A

1999-12-01

A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.

Effectiveness and cost effectiveness of television, radio and print advertisements in promoting the New York smokers' quitline.

PubMed

Farrelly, Matthew C; Hussin, Altijani; Bauer, Ursula E

2007-12-01

This study assessed the relative effectiveness and cost effectiveness of television, radio and print advertisements to generate calls to the New York smokers' quitline. Regression analysis was used to link total county level monthly quitline calls to television, radio and print advertising expenditures. Based on regression results, standardised measures of the relative effectiveness and cost effectiveness of expenditures were computed. There was a positive and statistically significant relation between call volume and expenditures for television (p<0.01) and radio (p<0.001) advertisements and a marginally significant effect for expenditures on newspaper advertisements (p<0.065). The largest effect was for television advertising. However, because of differences in advertising costs, for every $1000 increase in television, radio and newspaper expenditures, call volume increased by 0.1%, 5.7% and 2.8%, respectively. Television, radio and print media all effectively increased calls to the New York smokers' quitline. Although increases in expenditures for television were the most effective, their relatively high costs suggest they are not currently the most cost effective means to promote a quitline. This implies that a more efficient mix of media would place greater emphasis on radio than television. However, because the current study does not adequately assess the extent to which radio expenditures would sustain their effectiveness with substantial expenditure increases, it is not feasible to determine a more optimal mix of expenditures.

Use of Midlevel Practitioners to Achieve Labor Cost Savings in the Primary Care Practice of an MCO

PubMed Central

Roblin, Douglas W; Howard, David H; Becker, Edmund R; Kathleen Adams, E; Roberts, Melissa H

2004-01-01

Objective To estimate the savings in labor costs per primary care visit that might be realized from increased use of physician assistants (PAs) and nurse practitioners (NPs) in the primary care practices of a managed care organization (MCO). Study Setting/Data Sources Twenty-six capitated primary care practices of a group model MCO. Data on approximately two million visits provided by 206 practitioners were extracted from computerized visit records for 1997–2000. Computerized payroll ledgers were the source of annual labor costs per practice from 1997–2000. Study Design Likelihood of a visit attended by a PA/NP versus MD was modeled using logistic regression, with practice fixed effects, by department (adult medicine, pediatrics) and year. Parameter estimates and practice fixed effects from these regressions were used to predict the proportion of PA/NP visits per practice per year given a standard case mix. Least squares regressions, with practice fixed effects, were used to estimate the association of this standardized predicted proportion of PA/NP visits with average annual practitioner and total labor costs per visit, controlling for other practice characteristics. Results On average, PAs/NPs attended one in three adult medicine visits and one in five pediatric medicine visits. Likelihood of a PA/NP visit was significantly higher than average among patients presenting with minor acute illness (e.g., acute pharyngitis). In adult medicine, likelihood of a PA/NP visit was lower than average among older patients. Practitioner labor costs per visit and total labor costs per visit were lower (p<.01 and p=.08, respectively) among practices with greater use of PAs/NPs, standardized for case mix. Conclusions Primary care practices that used more PAs/NPs in care delivery realized lower practitioner labor costs per visit than practices that used less. Future research should investigate the cost savings and cost-effectiveness potential of delivery designs that change staffing mix and division of labor among clinical disciplines. PMID:15149481

Evaluating Effects of Developmental Education for College Students Using a Regression Discontinuity Design

ERIC Educational Resources Information Center

Moss, Brian G.; Yeaton, William H.

2013-01-01

Background: Annually, American colleges and universities provide developmental education (DE) to millions of underprepared students; however, evaluation estimates of DE benefits have been mixed. Objectives: Using a prototypic exemplar of DE, our primary objective was to investigate the utility of a replicative evaluative framework for assessing…

[Spatial heterogeneity in body condition of small yellow croaker in Yellow Sea and East China Sea based on mixed-effects model and quantile regression analysis].

PubMed

Liu, Zun-Lei; Yuan, Xing-Wei; Yan, Li-Ping; Yang, Lin-Lin; Cheng, Jia-Hua

2013-09-01

By using the 2008-2010 investigation data about the body condition of small yellow croaker in the offshore waters of southern Yellow Sea (SYS), open waters of northern East China Sea (NECS), and offshore waters of middle East China Sea (MECS), this paper analyzed the spatial heterogeneity of body length-body mass of juvenile and adult small yellow croakers by the statistical approaches of mean regression model and quantile regression model. The results showed that the residual standard errors from the analysis of covariance (ANCOVA) and the linear mixed-effects model were similar, and those from the simple linear regression were the highest. For the juvenile small yellow croakers, their mean body mass in SYS and NECS estimated by the mixed-effects mean regression model was higher than the overall average mass across the three regions, while the mean body mass in MECS was below the overall average. For the adult small yellow croakers, their mean body mass in NECS was higher than the overall average, while the mean body mass in SYS and MECS was below the overall average. The results from quantile regression indicated the substantial differences in the allometric relationships of juvenile small yellow croakers between SYS, NECS, and MECS, with the estimated mean exponent of the allometric relationship in SYS being 2.85, and the interquartile range being from 2.63 to 2.96, which indicated the heterogeneity of body form. The results from ANCOVA showed that the allometric body length-body mass relationships were significantly different between the 25th and 75th percentile exponent values (F=6.38, df=1737, P<0.01) and the 25th percentile and median exponent values (F=2.35, df=1737, P=0.039). The relationship was marginally different between the median and 75th percentile exponent values (F=2.21, df=1737, P=0.051). The estimated body length-body mass exponent of adult small yellow croakers in SYS was 3.01 (10th and 95th percentiles = 2.77 and 3.1, respectively). The estimated body length-body mass relationships were significantly different from the lower and upper quantiles of the exponent (F=3.31, df=2793, P=0.01) and the median and upper quantiles (F=3.56, df=2793, P<0.01), while no significant difference was observed between the lower and median quantiles (F=0.98, df=2793, P=0.43).

Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense mixed conifer forest

Treesearch

Marek K. Jakubowksi; Qinghua Guo; Brandon Collins; Scott Stephens; Maggi Kelly

2013-01-01

We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m

MANOVA vs nonlinear mixed effects modeling: The comparison of growth patterns of female and male quail

NASA Astrophysics Data System (ADS)

Gürcan, Eser Kemal

2017-04-01

The most commonly used methods for analyzing time-dependent data are multivariate analysis of variance (MANOVA) and nonlinear regression models. The aim of this study was to compare some MANOVA techniques and nonlinear mixed modeling approach for investigation of growth differentiation in female and male Japanese quail. Weekly individual body weight data of 352 male and 335 female quail from hatch to 8 weeks of age were used to perform analyses. It is possible to say that when all the analyses are evaluated, the nonlinear mixed modeling is superior to the other techniques because it also reveals the individual variation. In addition, the profile analysis also provides important information.

MIXED-STATUS FAMILIES AND WIC UPTAKE: THE EFFECTS OF RISK OF DEPORTATION ON PROGRAM USE

PubMed Central

Vargas, Edward D.; Pirog, Maureen A.

2016-01-01

Objective Develop and test measures of risk of deportation and mixed-status families on WIC uptake. Mixed-status is a situation in which some family members are U.S. citizens and other family members are in the U.S. without proper authorization. Methods Estimate a series of logistic regressions to estimate WIC uptake by merging data from Fragile Families and Child Well-being Survey with deportation data from U.S.-Immigration Customs and Enforcement. Results The findings of this study suggest that risk of deportation is negatively associated with WIC uptake and among mixed-status families; Mexican origin families are the most sensitive when it comes to deportations and program use. Conclusion Our analysis provides a typology and framework to study mixed-status families and evaluate their usage of social services by including an innovative measure of risk of deportation. PMID:27642194

Comparing colon cancer outcomes: The impact of low hospital case volume and case-mix adjustment.

PubMed

Fischer, C; Lingsma, H F; van Leersum, N; Tollenaar, R A E M; Wouters, M W; Steyerberg, E W

2015-08-01

When comparing performance across hospitals it is essential to consider the noise caused by low hospital case volume and to perform adequate case-mix adjustment. We aimed to quantify the role of noise and case-mix adjustment on standardized postoperative mortality and anastomotic leakage (AL) rates. We studied 13,120 patients who underwent colon cancer resection in 85 Dutch hospitals. We addressed differences between hospitals in postoperative mortality and AL, using fixed (ignoring noise) and random effects (incorporating noise) logistic regression models with general and additional, disease specific, case-mix adjustment. Adding disease specific variables improved the performance of the case-mix adjustment models for postoperative mortality (c-statistic increased from 0.77 to 0.81). The overall variation in standardized mortality ratios was similar, but some individual hospitals changed considerably. For the standardized AL rates the performance of the adjustment models was poor (c-statistic 0.59 and 0.60) and overall variation was small. Most of the observed variation between hospitals was actually noise. Noise had a larger effect on hospital performance than extended case-mix adjustment, although some individual hospital outcome rates were affected by more detailed case-mix adjustment. To compare outcomes between hospitals it is crucial to consider noise due to low hospital case volume with a random effects model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

PubMed

Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

2017-10-25

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

Effect of Rice Husk Ash and Fly Ash on the workability of concrete mixture in the High-Rise Construction

NASA Astrophysics Data System (ADS)

Van Tang, Lam; Bulgakov, Boris; Bazhenova, Sofia; Aleksandrova, Olga; Pham, Anh Ngoc; Dinh Vu, Tho

2018-03-01

The dense development of high-rise construction in urban areas requires a creation of new concretes with essential properties and innovative technologies for preparing concrete mixtures. Besides, it is necessary to develop new ways of presenting concrete mixture and keeping their mobility. This research uses the mathematical method of two-factors rotatable central compositional planning to imitate the effect of amount of rice husk (RHA) and fly ash of thermal power plants (FA) on the workability of high-mobility concrete mixtures. The results of this study displays regression equation of the second order dependence of the objective functions - slump cone and loss of concrete mixture mobility due to the input factors - the amounts RHA (x1) and FA (x2), as well as the surface expression image of these regression equations. An analysis of the regression equations also shows that the amount of RHA and FA had a significant influence on the concrete mixtures mobility. In fact, the particles of RHA and FA will play the role as peculiar "sliding bearings" between the grains of cement leading to the dispersion of cement in the concrete mixture. Therefore, it is possible to regulate the concrete mixture mobility when transporting fresh concrete to the formwork during the high-rise buildings construction in the hot and humid climate of Vietnam. Although the average value of slump test of freshly mixed concrete, measured 60 minutes later after the mixing completion, decreased from 18.2 to 10.52 cm, this value still remained within the allowable range to maintain the mixing and and the delivery of concrete mixture by pumping.

Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England using M-quantile random-effects regression.

PubMed

Tzavidis, Nikos; Salvati, Nicola; Schmid, Timo; Flouri, Eirini; Midouhas, Emily

2016-02-01

Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M -quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Mapping of macro and micro nutrients of mixed pastures using airborne AisaFENIX hyperspectral imagery

NASA Astrophysics Data System (ADS)

Pullanagari, R. R.; Kereszturi, Gábor; Yule, I. J.

2016-07-01

On-farm assessment of mixed pasture nutrient concentrations is important for animal production and pasture management. Hyperspectral imaging is recognized as a potential tool to quantify the nutrient content of vegetation. However, it is a great challenge to estimate macro and micro nutrients in heterogeneous mixed pastures. In this study, canopy reflectance data was measured by using a high resolution airborne visible-to-shortwave infrared (Vis-SWIR) imaging spectrometer measuring in the wavelength region 380-2500 nm to predict nutrient concentrations, nitrogen (N) phosphorus (P), potassium (K), sulfur (S), zinc (Zn), sodium (Na), manganese (Mn) copper (Cu) and magnesium (Mg) in heterogeneous mixed pastures across a sheep and beef farm in hill country, within New Zealand. Prediction models were developed using four different methods which are included partial least squares regression (PLSR), kernel PLSR, support vector regression (SVR), random forest regression (RFR) algorithms and their performance compared using the test data. The results from the study revealed that RFR produced highest accuracy (0.55 ⩽ R2CV ⩽ 0.78; 6.68% ⩽ nRMSECV ⩽ 26.47%) compared to all other algorithms for the majority of nutrients (N, P, K, Zn, Na, Cu and Mg) described, and the remaining nutrients (S and Mn) were predicted with high accuracy (0.68 ⩽ R2CV ⩽ 0.86; 13.00% ⩽ nRMSECV ⩽ 14.64%) using SVR. The best training models were used to extrapolate over the whole farm with the purpose of predicting those pasture nutrients and expressed through pixel based spatial maps. These spatially registered nutrient maps demonstrate the range and geographical location of often large differences in pasture nutrient values which are normally not measured and therefore not included in decision making when considering more effective ways to utilized pasture.

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

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.

Exploring the spatially varying innovation capacity of the US counties in the framework of Griliches' knowledge production function: a mixed GWR approach

NASA Astrophysics Data System (ADS)

Kang, Dongwoo; Dall'erba, Sandy

2016-04-01

Griliches' knowledge production function has been increasingly adopted at the regional level where location-specific conditions drive the spatial differences in knowledge creation dynamics. However, the large majority of such studies rely on a traditional regression approach that assumes spatially homogenous marginal effects of knowledge input factors. This paper extends the authors' previous work (Kang and Dall'erba in Int Reg Sci Rev, 2015. doi: 10.1177/0160017615572888) to investigate the spatial heterogeneity in the marginal effects by using nonparametric local modeling approaches such as geographically weighted regression (GWR) and mixed GWR with two distinct samples of the US Metropolitan Statistical Area (MSA) and non-MSA counties. The results indicate a high degree of spatial heterogeneity in the marginal effects of the knowledge input variables, more specifically for the local and distant spillovers of private knowledge measured across MSA counties. On the other hand, local academic knowledge spillovers are found to display spatially homogenous elasticities in both MSA and non-MSA counties. Our results highlight the strengths and weaknesses of each county's innovation capacity and suggest policy implications for regional innovation strategies.

Effects of Morphological Family Size for Young Readers

ERIC Educational Resources Information Center

Perdijk, Kors; Schreuder, Robert; Baayen, R. Harald; Verhoeven, Ludo

2012-01-01

Dutch children, from the second and fourth grade of primary school, were each given a visual lexical decision test on 210 Dutch monomorphemic words. After removing words not recognized by a majority of the younger group, (lexical) decisions were analysed by mixed-model regression methods to see whether morphological Family Size influenced decision…

Modeling stream network-scale variation in Coho salmon overwinter survival and smolt size

Treesearch

Joseph L. Ebersole; Mike E. Colvin; Parker J. Wigington; Scott G. Leibowitz; Joan P. Baker; Jana E. Compton; Bruce A. Miller; Michael A. Carins; Bruce P. Hansen; Henry R. La Vigne

2009-01-01

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over 3 years. Contributing basin area explained the majority of spatial...

Promoting participation in physical activity using framed messages: an application of prospect theory.

PubMed

Latimer, Amy E; Rench, Tara A; Rivers, Susan E; Katulak, Nicole A; Materese, Stephanie A; Cadmus, Lisa; Hicks, Althea; Keany Hodorowski, Julie; Salovey, Peter

2008-11-01

Messages designed to motivate participation in physical activity usually emphasize the benefits of physical activity (gain-framed) as well as the costs of inactivity (loss-framed). The framing implications of prospect theory suggest that the effectiveness of these messages could be enhanced by providing gain-framed information only. We compared the effectiveness of gain-, loss-, and mixed-framed messages for promoting moderate to vigorous physical activity. Randomized trial. Sedentary, healthy callers to the US National Cancer Institute's Cancer Information Service (N=322) received gain-, loss-, or mixed-framed messages on three occasions (baseline, Week 1, and Week 5). Social cognitive variables and self-reported physical activity were assessed at baseline, Week 2, and Week 9. Separate regression analyses were conducted to examine message effects at each assessment point. At Week 2, gain- and mixed-framed messages resulted in stronger intentions and greater self-efficacy than loss-framed messages. At Week 9, gain-framed messages resulted in greater physical activity participation than loss- or mixed-framed messages. Social cognitive variables at Week 2 did not mediate the Week 9 framing effects on physical activity participation. Using gain-framed messages exclusively may be a means of increasing the efficacy of physical activity materials.

Horses Auto-Recruit Their Lungs by Inspiratory Breath Holding Following Recovery from General Anaesthesia

PubMed Central

Mosing, Martina; Waldmann, Andreas D.; MacFarlane, Paul; Iff, Samuel; Auer, Ulrike; Bohm, Stephan H.; Bettschart-Wolfensberger, Regula; Bardell, David

2016-01-01

This study evaluated the breathing pattern and distribution of ventilation in horses prior to and following recovery from general anaesthesia using electrical impedance tomography (EIT). Six horses were anaesthetised for 6 hours in dorsal recumbency. Arterial blood gas and EIT measurements were performed 24 hours before (baseline) and 1, 2, 3, 4, 5 and 6 hours after horses stood following anaesthesia. At each time point 4 representative spontaneous breaths were analysed. The percentage of the total breath length during which impedance remained greater than 50% of the maximum inspiratory impedance change (breath holding), the fraction of total tidal ventilation within each of four stacked regions of interest (ROI) (distribution of ventilation) and the filling time and inflation period of seven ROI evenly distributed over the dorso-ventral height of the lungs were calculated. Mixed effects multi-linear regression and linear regression were used and significance was set at p<0.05. All horses demonstrated inspiratory breath holding until 5 hours after standing. No change from baseline was seen for the distribution of ventilation during inspiration. Filling time and inflation period were more rapid and shorter in ventral and slower and longer in most dorsal ROI compared to baseline, respectively. In a mixed effects multi-linear regression, breath holding was significantly correlated with PaCO2 in both the univariate and multivariate regression. Following recovery from anaesthesia, horses showed inspiratory breath holding during which gas redistributed from ventral into dorsal regions of the lungs. This suggests auto-recruitment of lung tissue which would have been dependent and likely atelectic during anaesthesia. PMID:27331910

Effectiveness and cost effectiveness of television, radio and print advertisements in promoting the New York smokers' quitline

PubMed Central

Farrelly, Matthew C; Hussin, Altijani; Bauer, Ursula E

2007-01-01

Objectives This study assessed the relative effectiveness and cost effectiveness of television, radio and print advertisements to generate calls to the New York smokers' quitline. Methods Regression analysis was used to link total county level monthly quitline calls to television, radio and print advertising expenditures. Based on regression results, standardised measures of the relative effectiveness and cost effectiveness of expenditures were computed. Results There was a positive and statistically significant relation between call volume and expenditures for television (p<0.01) and radio (p<0.001) advertisements and a marginally significant effect for expenditures on newspaper advertisements (p<0.065). The largest effect was for television advertising. However, because of differences in advertising costs, for every $1000 increase in television, radio and newspaper expenditures, call volume increased by 0.1%, 5.7% and 2.8%, respectively. Conclusions Television, radio and print media all effectively increased calls to the New York smokers' quitline. Although increases in expenditures for television were the most effective, their relatively high costs suggest they are not currently the most cost effective means to promote a quitline. This implies that a more efficient mix of media would place greater emphasis on radio than television. However, because the current study does not adequately assess the extent to which radio expenditures would sustain their effectiveness with substantial expenditure increases, it is not feasible to determine a more optimal mix of expenditures. PMID:18048625

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

Accelerating Improvement and Narrowing Gaps: Trends in Patients' Experiences with Hospital Care Reflected in HCAHPS Public Reporting.

PubMed

Elliott, Marc N; Cohea, Christopher W; Lehrman, William G; Goldstein, Elizabeth H; Cleary, Paul D; Giordano, Laura A; Beckett, Megan K; Zaslavsky, Alan M

2015-12-01

Measure HCAHPS improvement in hospitals participating in the second and fifth years of HCAHPS public reporting; determine whether change is greater for some hospital types. Surveys from 4,822,960 adult inpatients discharged July 2007-June 2008 or July 2010-June 2011 from 3,541 U.S. hospitals. Linear mixed-effect regression models with fixed effects for time, patient mix, and hospital characteristics (bedsize, ownership, Census division, teaching status, Critical Access status); random effects for hospitals and hospital-time interactions; fixed-effect interactions of hospital characteristics and patient characteristics (gender, health, education) with time predicted HCAHPS measures correcting for regression-to-the-mean biases. National probability sample of adult inpatients in any of four approved survey modes. HCAHPS scores increased by 2.8 percentage points from 2008 to 2011 in the most positive response category. Among the middle 95 percent of hospitals, changes ranged from a 5.1 percent decrease to a 10.2 percent gain overall. The greatest improvement was in for-profit and larger (200 or more beds) hospitals. Five years after HCAHPS public reporting began, meaningful improvement of patients' hospital care experiences continues, especially among initially low-scoring hospitals, reducing some gaps among hospitals. © Health Research and Educational Trust.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

The effect of skill mix in non-nursing assistants on work engagements among home visiting nurses in Japan.

PubMed

Naruse, Takashi; Taguchi, Atsuko; Kuwahara, Yuki; Nagata, Satoko; Sakai, Mahiro; Watai, Izumi; Murashima, Sachiyo

2015-05-01

This study evaluated the effect of a skill-mix programme intervention on work engagement in home visiting nurses. A skill-mix programme in which home visiting nurses are assisted by non-nursing workers is assumed to foster home visiting nurses' work engagement. Pre- and post-intervention evaluations of work engagement were conducted using self-administered questionnaires. A skill-mix programme was introduced in the intervention group of home visiting nurses. After 6 months, their pre- and post-intervention work engagement ratings were compared with those of a control group. Baseline questionnaires were returned by 174 home visiting nurses (44 in the intervention group, 130 in the control group). Post-intervention questionnaires were returned by 38 and 97 home visiting nurses from each group. The intervention group's average work engagement scores were 2.2 at baseline and 2.3 at post-intervention; the control group's were 3.3 and 2.6. Generalised linear regression showed significant between-group differences in score changes. The skill-mix programme might foster home visiting nurses' work engagement by improving the quality of care for each client. Future research is needed to explain the exact mechanisms that underlie its effectiveness. In order to improve the efficiency of services provided by home visiting nurses and foster their work engagement, skill-mix programmes might be beneficial. © 2014 John Wiley & Sons Ltd.

Civic Purpose in Late Adolescence: Factors That Prevent Decline in Civic Engagement after High School

ERIC Educational Resources Information Center

Malin, Heather; Han, Hyemin; Liauw, Indrawati

2017-01-01

This study investigated the effects of internal and demographic variables on civic development in late adolescence using the construct "civic purpose." We conducted surveys on civic engagement with 480 high school seniors, and surveyed them again 2 years later. Using multivariate regression and linear mixed models, we tested the main…

Curriculum-Based Measurement of Oral Reading: Quality of Progress Monitoring Outcomes

ERIC Educational Resources Information Center

Christ, Theodore J.; Zopluoglu, Cengiz; Long, Jeffery D.; Monaghen, Barbara D.

2012-01-01

Curriculum-based measurement of oral reading (CBM-R) is frequently used to set student goals and monitor student progress. This study examined the quality of growth estimates derived from CBM-R progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for multiple levels of…

Composites from southern pine juvenile wood. Part 3. Juvenile and mature wood furnish mixtures

Treesearch

A.D. Pugel; E.W. Price; Chung-Yun Hse; T.F. Shupe

2004-01-01

Composite panelsmade from mixtures ofmature andjuvenile southern pine (Pinus taeda L.) were evaluated for initial mechanical properties and dimensional stability. The effect that the proportion of juvenile wood had on panel properties was analyzed by regression and rule-of-mixtures models. The mixed furnish data: 1) highlighted the degree to which...

Solving a mixture of many random linear equations by tensor decomposition and alternating minimization.

DOT National Transportation Integrated Search

2016-09-01

We consider the problem of solving mixed random linear equations with k components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels (which sample...

Investigation of predictors affecting food mixing ability in mandibulectomy and/or glossectomy patients.

PubMed

Otomaru, Takafumi; Sumita, Yuka I; Chang, Qingan; Fueki, Kenji; Igarashi, Yoshimasa; Taniguchi, Hisashi

2009-07-01

Several previous reports have described factors that affect masticatory function. However, there are no known predictors that affect the food mixing ability of the masticatory function, and it has been impossible to predict masticatory function in mandibulectomy and/or glossectomy patients. The purpose of the present study was to develop a numerical formula that could predict the food mixing ability of the masticatory function among mandibulectomy and/or glossectomy patients. The null hypothesis of the study was that five predictors, namely mandibulectomy, mandibular continuity, number of residual mandibular teeth, occlusal units and tongue movement score, were unable to account for the mixing ability index (MAI) in mandibulectomy and/or glossectomy patients. The subjects were 20 patients who had undergone mandibulectomy and/or glossectomy. The above-described five predictors were assessed. Tongue movement was evaluated with a tongue movement test and the MAI was evaluated with a mixing ability test. Multiple regression analysis was used to examine whether the five predictors affected the MAI after prosthetic treatment. A regression equation was determined for the five predictors (R(2)=0.83; adjusted R(2)=0.77; p<0.001). The obtained regression equation could successfully account for the MAI in mandibulectomy and/or glossectomy patients.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

A mixed-method evaluation of peer-education workshops for school-aged children to teach about antibiotics, microbes and hygiene

PubMed Central

Young, Vicki L.; Cole, Amy; Lecky, Donna M.; Fettis, Dennis; Pritchard, Beth; Verlander, Neville Q.; Eley, Charlotte V.; McNulty, Cliodna A. M.

2017-01-01

Abstract Background: Delivering health topics in schools through peer education is known to be beneficial for all students involved. In this study, we have evaluated a peer-education workshop that aims to educate primary and secondary school students on hygiene, the spread of infection and antibiotics. Methods: Four schools in south-west England, in a range of localities, took part in peer-education workshops, with students completing before, after and knowledge-retention questionnaires. Mixed-effect logistic regression and mixed-effect linear regression were used to analyse the data. Data were analysed by topic, region and peer/non-peer-educator status. Qualitative interviews and focus groups with students and educators were conducted to assess changes in participants’ skills, confidence and behaviour. Results: Qualitative data indicated improvements in peer-educator skills and behaviour, including confidence, team-working and communication. There was a significant improvement in knowledge for all topics covered in the intervention, although this varied by region. In the antibiotics topic, peer-educators’ knowledge increased in the retention questionnaire, whereas non-peer-educators’ knowledge decreased. Knowledge declined in the retention questionnaires for the other topics, although this was mostly not significant. Conclusions: This study indicates that peer education is an effective way to educate young people on important topics around health and hygiene, and to concurrently improve communication skills. Its use should be encouraged across schools to help in the implementation of the National Institute for Health and Care Excellence (NICE) guidance that recommends children are taught in an age-appropriate manner about hygiene and antibiotics. PMID:28333334

Semiparametric regression during 2003–2007*

PubMed Central

Ruppert, David; Wand, M.P.; Carroll, Raymond J.

2010-01-01

Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application. PMID:20305800

Statistical inference methods for sparse biological time series data.

PubMed

Ndukum, Juliet; Fonseca, Luís L; Santos, Helena; Voit, Eberhard O; Datta, Susmita

2011-04-25

Comparing metabolic profiles under different biological perturbations has become a powerful approach to investigating the functioning of cells. The profiles can be taken as single snapshots of a system, but more information is gained if they are measured longitudinally over time. The results are short time series consisting of relatively sparse data that cannot be analyzed effectively with standard time series techniques, such as autocorrelation and frequency domain methods. In this work, we study longitudinal time series profiles of glucose consumption in the yeast Saccharomyces cerevisiae under different temperatures and preconditioning regimens, which we obtained with methods of in vivo nuclear magnetic resonance (NMR) spectroscopy. For the statistical analysis we first fit several nonlinear mixed effect regression models to the longitudinal profiles and then used an ANOVA likelihood ratio method in order to test for significant differences between the profiles. The proposed methods are capable of distinguishing metabolic time trends resulting from different treatments and associate significance levels to these differences. Among several nonlinear mixed-effects regression models tested, a three-parameter logistic function represents the data with highest accuracy. ANOVA and likelihood ratio tests suggest that there are significant differences between the glucose consumption rate profiles for cells that had been--or had not been--preconditioned by heat during growth. Furthermore, pair-wise t-tests reveal significant differences in the longitudinal profiles for glucose consumption rates between optimal conditions and heat stress, optimal and recovery conditions, and heat stress and recovery conditions (p-values <0.0001). We have developed a nonlinear mixed effects model that is appropriate for the analysis of sparse metabolic and physiological time profiles. The model permits sound statistical inference procedures, based on ANOVA likelihood ratio tests, for testing the significance of differences between short time course data under different biological perturbations.

Wavelet-based functional linear mixed models: an application to measurement error-corrected distributed lag models.

PubMed

Malloy, Elizabeth J; Morris, Jeffrey S; Adar, Sara D; Suh, Helen; Gold, Diane R; Coull, Brent A

2010-07-01

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient is necessary for estimation. Additional issues in this setting are the possibility of exposure measurement error and the need to incorporate additional potential confounders, such as meteorological or co-pollutant measures, that themselves may have effects that vary over time. To accommodate all these features, we develop wavelet-based linear mixed distributed lag models that incorporate repeated measures of functional data as covariates into a linear mixed model. A Bayesian approach to model fitting uses wavelet shrinkage to regularize functional coefficients. We show that, as long as the exposure error induces fine-scale variability in the functional exposure profile and the distributed lag function representing the exposure effect varies smoothly in time, the model corrects for the exposure measurement error without further adjustment. Both these conditions are likely to hold in the environmental applications we consider. We examine properties of the method using simulations and apply the method to data from a study examining the association between PM, measured as hourly averages for 1-7 days, and markers of acute systemic inflammation. We use the method to fully control for the effects of confounding by other time-varying predictors, such as temperature and co-pollutants.

Changing perception: facial reanimation surgery improves attractiveness and decreases negative facial perception.

PubMed

Dey, Jacob K; Ishii, Masaru; Boahene, Kofi D O; Byrne, Patrick J; Ishii, Lisa E

2014-01-01

Determine the effect of facial reanimation surgery on observer-graded attractiveness and negative facial perception of patients with facial paralysis. Randomized controlled experiment. Ninety observers viewed images of paralyzed faces, smiling and in repose, before and after reanimation surgery, as well as normal comparison faces. Observers rated the attractiveness of each face and characterized the paralyzed faces by rating severity, disfigured/bothersome, and importance to repair. Iterated factor analysis indicated these highly correlated variables measure a common domain, so they were combined to create the disfigured, important to repair, bothersome, severity (DIBS) factor score. Mixed effects linear regression determined the effect of facial reanimation surgery on attractiveness and DIBS score. Facial paralysis induces an attractiveness penalty of 2.51 on a 10-point scale for faces in repose and 3.38 for smiling faces. Mixed effects linear regression showed that reanimation surgery improved attractiveness for faces both in repose and smiling by 0.84 (95% confidence interval [CI]: 0.67, 1.01) and 1.24 (95% CI: 1.07, 1.42) respectively. Planned hypothesis tests confirmed statistically significant differences in attractiveness ratings between postoperative and normal faces, indicating attractiveness was not completely normalized. Regression analysis also showed that reanimation surgery decreased DIBS by 0.807 (95% CI: 0.704, 0.911) for faces in repose and 0.989 (95% CI: 0.886, 1.093), an entire standard deviation, for smiling faces. Facial reanimation surgery increases attractiveness and decreases negative facial perception of patients with facial paralysis. These data emphasize the need to optimize reanimation surgery to restore not only function, but also symmetry and cosmesis to improve facial perception and patient quality of life. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

PubMed

Lloyd-Jones, Luke R; Robinson, Matthew R; Yang, Jian; Visscher, Peter M

2018-04-01

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure ( e.g. , a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects. Copyright © 2018 by the Genetics Society of America.

Hospital costs by cost center of inpatient hospitalization for medicare patients undergoing major abdominal surgery.

PubMed

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.

Robust and efficient estimation with weighted composite quantile regression

NASA Astrophysics Data System (ADS)

Jiang, Xuejun; Li, Jingzhi; Xia, Tian; Yan, Wanfeng

2016-09-01

In this paper we introduce a weighted composite quantile regression (CQR) estimation approach and study its application in nonlinear models such as exponential models and ARCH-type models. The weighted CQR is augmented by using a data-driven weighting scheme. With the error distribution unspecified, the proposed estimators share robustness from quantile regression and achieve nearly the same efficiency as the oracle maximum likelihood estimator (MLE) for a variety of error distributions including the normal, mixed-normal, Student's t, Cauchy distributions, etc. We also suggest an algorithm for the fast implementation of the proposed methodology. Simulations are carried out to compare the performance of different estimators, and the proposed approach is used to analyze the daily S&P 500 Composite index, which verifies the effectiveness and efficiency of our theoretical results.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Measurement of faculty anesthesiologists' quality of clinical supervision has greater reliability when controlling for the leniency of the rating anesthesia resident: a retrospective cohort study.

PubMed

Dexter, Franklin; Ledolter, Johannes; Hindman, Bradley J

2017-06-01

Our department monitors the quality of anesthesiologists' clinical supervision and provides each anesthesiologist with periodic feedback. We hypothesized that greater differentiation among anesthesiologists' supervision scores could be obtained by adjusting for leniency of the rating resident. From July 1, 2013 to December 31, 2015, our department has utilized the de Oliveira Filho unidimensional nine-item supervision scale to assess the quality of clinical supervision provided by faculty as rated by residents. We examined all 13,664 ratings of the 97 anesthesiologists (ratees) by the 65 residents (raters). Testing for internal consistency among answers to questions (large Cronbach's alpha > 0.90) was performed to rule out that one or two questions accounted for leniency. Mixed-effects logistic regression was used to compare ratees while controlling for rater leniency vs using Student t tests without rater leniency. The mean supervision scale score was calculated for each combination of the 65 raters and nine questions. The Cronbach's alpha was very large (0.977). The mean score was calculated for each of the 3,421 observed combinations of resident and anesthesiologist. The logits of the percentage of scores equal to the maximum value of 4.00 were normally distributed (residents, P = 0.24; anesthesiologists, P = 0.50). There were 20/97 anesthesiologists identified as significant outliers (13 with below average supervision scores and seven with better than average) using the mixed-effects logistic regression with rater leniency entered as a fixed effect but not by Student's t test. In contrast, there were three of 97 anesthesiologists identified as outliers (all three above average) using Student's t tests but not by logistic regression with leniency. The 20 vs 3 was significant (P < 0.001). Use of logistic regression with leniency results in greater detection of anesthesiologists with significantly better (or worse) clinical supervision scores than use of Student's t tests (i.e., without adjustment for rater leniency).

Superquantile/CVaR Risk Measures: Second-Order Theory

DTIC Science & Technology

2014-07-17

order version of quantile regression . Keywords: superquantiles, conditional value-at-risk, second-order superquantiles, mixed superquan- tiles... quantile regression . 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18. NUMBER OF PAGES 26 19a...second-order superquantiles is in the domain of generalized regression . We laid out in [16] a parallel methodology to that of quantile regression

Evaluation of aroma enhancement for "Ecolly" dry white wines by mixed inoculation of selected Rhodotorula mucilaginosa and Saccharomyces cerevisiae.

PubMed

Wang, Xing-Chen; Li, Ai-Hua; Dizy, Marta; Ullah, Niamat; Sun, Wei-Xuan; Tao, Yong-Sheng

2017-08-01

To improve the aroma profile of Ecolly dry white wine, the simultaneous and sequential inoculations of selected Rhodotorula mucilaginosa and Saccharomyces cerevisiae were performed in wine making of this work. The two yeasts were mixed in various ratios for making the mixed inoculum. The amount of volatiles and aroma characteristics were determined the following year. Mixed fermentation improved both the varietal and fermentative aroma compound composition, especially that of (Z)-3-hexene-1-ol, nerol oxide, certain acetates and ethyls group compounds. Citrus, sweet fruit, acid fruit, berry, and floral aroma traits were enhanced by mixed fermentation; however, an animal note was introduced upon using higher amounts of R. mucilaginosa. Aroma traits were regressed with volatiles as observed by the partial least-square regression method. Analysis of correlation coefficients revealed that the aroma traits were the multiple interactions of volatile compounds, with the fermentative volatiles having more impact on aroma than varietal compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brand emotional credibility: effects of mixed emotions about branded products with varying credibility.

PubMed

Mileti, Antonio; Prete, M Irene; Guido, Gianluigi

2013-10-01

This research investigates the effects of mixed emotions on the positioning and on the intention to purchase different categories of branded products (i.e., Attractiveness-products, Expertise-products, and Trustworthiness-products), in relation to their main component of credibility (Ohanian, 1990). On the basis of a focus group (n = 12) aimed to identify the three branded products used as stimuli and a pre-test (n = 240) directed to discover emotions elicited by them, two studies (n = 630; n = 240) were carried out. Positioning and multiple regression analyses showed that positive and negative emotions are positively related with the positioning and the purchase intention of Attractiveness-products, and, respectively, positively and negatively related with those of Trustworthiness-products; whereas negative emotions are negatively associated with those of Expertise-products. Brand Emotional Credibility--i.e., the emotional believability of the brand positioning signals--may help to identify unconscious elements and the simultaneous importance of mixed emotions associated with different products to match consumers' desires and expectations.

Evaluation of the effect of yellow konjac flour-κ-carrageenan mixed gels and red koji rice extracts on the properties of restructured meat using response surface methodology.

PubMed

Widjanarko, Simon Bambang; Amalia, Qory; Hermanto, Mochamad Bagus; Mubarok, Ahmad Zaki

2018-05-01

In the present study, the effect of two independent variables, yellow konjac flour-κ-carrageenan (KFC) mixed gels and red koji rice (RKR) extracts for the development of restructured meat product, was investigated using central composite design of response surface methodology (RSM). The assessed physical characteristics were hardness, water holding capacity (WHC), and color (° hue ) of the restructured meat products. The second order regression models with high R 2 value were significantly fitted to predict the changes in hardness, WHC and color. The results showed that the predicted optimum formula of restructured meat were the addition of KFC mixed gels at 10.21% and RKR extracts at 6.11%. The experiments results validate these optimum formula and found to be not statistically different at 5% level. Thus, the RSM was successfully employed and can be used to optimize the formulation of restructured meat.

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

Random effects coefficient of determination for mixed and meta-analysis models

PubMed Central

Demidenko, Eugene; Sargent, James; Onega, Tracy

2011-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, Rr2, that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If Rr2 is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of Rr2 apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects—the model can be estimated using the dummy variable approach. We derive explicit formulas for Rr2 in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine. PMID:23750070

Regression Analysis of Mixed Recurrent-Event and Panel-Count Data with Additive Rate Models

PubMed Central

Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L.

2015-01-01

Summary Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007; Zhao et al., 2011). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013). In this paper, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. PMID:25345405

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

Comparative Effectiveness of Emergency Resuscitative Thoracotomy versus Closed Chest Compressions among Patients with Critical Blunt Trauma: A Nationwide Cohort Study in Japan.

PubMed

Suzuki, Kodai; Inoue, Shigeaki; Morita, Seiji; Watanabe, Nobuo; Shintani, Ayumi; Inokuchi, Sadaki; Ogura, Shinji

2016-01-01

Although emergency resuscitative thoracotomy is performed as a salvage maneuver for critical blunt trauma patients, evidence supporting superior effectiveness of emergency resuscitative thoracotomy compared to conventional closed-chest compressions remains insufficient. The objective of this study was to investigate whether emergency resuscitative thoracotomy at the emergency department or in the operating room was associated with favourable outcomes after blunt trauma and to compare its effectiveness with that of closed-chest compressions. This was a retrospective nationwide cohort study. Data were obtained from the Japan Trauma Data Bank for the period between 2004 and 2012. The primary and secondary outcomes were patient survival rates 24 h and 28 d after emergency department arrival. Statistical analyses were performed using multivariable generalized mixed-effects regression analysis. We adjusted for the effects of different hospitals by introducing random intercepts in regression analysis to account for the differential quality of emergency resuscitative thoracotomy at hospitals where patients in cardiac arrest were treated. Sensitivity analyses were performed using propensity score matching. In total, 1,377 consecutive, critical blunt trauma patients who received cardiopulmonary resuscitation in the emergency department or operating room were included in the study. Of these patients, 484 (35.1%) underwent emergency resuscitative thoracotomy and 893 (64.9%) received closed-chest compressions. Compared to closed-chest compressions, emergency resuscitative thoracotomy was associated with lower survival rate 24 h after emergency department arrival (4.5% vs. 17.5%, respectively, P < 0.001) and 28 d after arrival (1.2% vs. 6.0%, respectively, P < 0.001). Multivariable generalized mixed-effects regression analysis with and without a propensity score-matched dataset revealed that the odds ratio for an unfavorable survival rate after 24 h was lower for emergency resuscitative thoracotomy than for closed-chest compressions (P < 0.001). Emergency resuscitative thoracotomy was independently associated with decreased odds of a favorable survival rate compared to closed-chest compressions.

The long-solved problem of the best-fit straight line: application to isotopic mixing lines

NASA Astrophysics Data System (ADS)

Wehr, Richard; Saleska, Scott R.

2017-01-01

It has been almost 50 years since York published an exact and general solution for the best-fit straight line to independent points with normally distributed errors in both x and y. York's solution is highly cited in the geophysical literature but almost unknown outside of it, so that there has been no ebb in the tide of books and papers wrestling with the problem. Much of the post-1969 literature on straight-line fitting has sown confusion not merely by its content but by its very existence. The optimal least-squares fit is already known; the problem is already solved. Here we introduce the non-specialist reader to York's solution and demonstrate its application in the interesting case of the isotopic mixing line, an analytical tool widely used to determine the isotopic signature of trace gas sources for the study of biogeochemical cycles. The most commonly known linear regression methods - ordinary least-squares regression (OLS), geometric mean regression (GMR), and orthogonal distance regression (ODR) - have each been recommended as the best method for fitting isotopic mixing lines. In fact, OLS, GMR, and ODR are all special cases of York's solution that are valid only under particular measurement conditions, and those conditions do not hold in general for isotopic mixing lines. Using Monte Carlo simulations, we quantify the biases in OLS, GMR, and ODR under various conditions and show that York's general - and convenient - solution is always the least biased.

Restructuring in response to case mix reimbursement in nursing homes: A contingency approach

PubMed Central

Zinn, Jacqueline; Feng, Zhanlian; Mor, Vincent; Intrator, Orna; Grabowski, David

2013-01-01

Background Resident-based case mix reimbursement has become the dominant mechanism for publicly funded nursing home care. In 1998 skilled nursing facility reimbursement changed from cost-based to case mix adjusted payments under the Medicare Prospective Payment System for the costs of all skilled nursing facility care provided to Medicare recipients. In addition, as of 2004, 35 state Medicaid programs had implemented some form of case mix reimbursement. Purpose The purpose of the study is to determine if the implementation of Medicare and Medicaid case mix reimbursement increased the administrative burden on nursing homes, as evidenced by increased levels of nurses in administrative functions. Methodology/Approach The primary data for this study come from the Centers for Medicare and Medicaid Services Online Survey Certification and Reporting database from 1997 through 2004, a national nursing home database containing aggregated facility-level information, including staffing, organizational characteristics and resident conditions, on all Medicare/Medicaid certified nursing facilities in the country. We conducted multivariate regression analyses using a facility fixed-effects model to examine the effects of the implementation of Medicaid case mix reimbursement and Medicare Prospective Payment System on changes in the level of total administrative nurse staffing in nursing homes. Findings Both Medicaid case mix reimbursement and Medicare Prospective Payment System increased the level of administrative nurse staffing, on average by 5.5% and 4.0% respectively. However, lack of evidence for a substitution effect suggests that any decline in direct care staffing after the introduction of case mix reimbursement is not attributable to a shift from clinical nursing resources to administrative functions. Practice Implications Our findings indicate that the administrative burden posed by case mix reimbursement has resource implications for all freestanding facilities. At the margin, the increased administrative burden imposed by case mix may become a factor influencing a range of decisions, including resident admission and staff hiring. PMID:18360162

Restructuring in response to case mix reimbursement in nursing homes: a contingency approach.

PubMed

Zinn, Jacqueline; Feng, Zhanlian; Mor, Vincent; Intrator, Orna; Grabowski, David

2008-01-01

Resident-based case mix reimbursement has become the dominant mechanism for publicly funded nursing home care. In 1998 skilled nursing facility reimbursement changed from cost-based to case mix adjusted payments under the Medicare Prospective Payment System for the costs of all skilled nursing facility care provided to Medicare recipients. In addition, as of 2004, 35 state Medicaid programs had implemented some form of case mix reimbursement. The purpose of the study is to determine if the implementation of Medicare and Medicaid case mix reimbursement increased the administrative burden on nursing homes, as evidenced by increased levels of nurses in administrative functions. The primary data for this study come from the Centers for Medicare and Medicaid Services Online Survey Certification and Reporting database from 1997 through 2004, a national nursing home database containing aggregated facility-level information, including staffing, organizational characteristics and resident conditions, on all Medicare/Medicaid certified nursing facilities in the country. We conducted multivariate regression analyses using a facility fixed-effects model to examine the effects of the implementation of Medicaid case mix reimbursement and Medicare Prospective Payment System on changes in the level of total administrative nurse staffing in nursing homes. Both Medicaid case mix reimbursement and Medicare Prospective Payment System increased the level of administrative nurse staffing, on average by 5.5% and 4.0% respectively. However, lack of evidence for a substitution effect suggests that any decline in direct care staffing after the introduction of case mix reimbursement is not attributable to a shift from clinical nursing resources to administrative functions. Our findings indicate that the administrative burden posed by case mix reimbursement has resource implications for all freestanding facilities. At the margin, the increased administrative burden imposed by case mix may become a factor influencing a range of decisions, including resident admission and staff hiring.

Symptoms of Depression Depend on Rigid Parenting Attitudes, Gender, and Race in an At-Risk Sample of Early Adolescents

ERIC Educational Resources Information Center

Weed, Keri; Morales, Dawn A.; Harjes, Rachel

2013-01-01

Trajectories of depressive symptoms were compared between European American and African American boys and girls from ages 8 to 14 in a longitudinal sample of 130 children born to adolescent mothers. Mixed-effects regression modeling was used to analyze individual and group differences in level of depressive symptoms and their changes over time.…

Children's Compliance with American Academy of Pediatrics' Well-Child Care Visit Guidelines and the Early Detection of Autism

ERIC Educational Resources Information Center

Daniels, Amy M.; Mandell, David S.

2013-01-01

This study estimated compliance with American Academy of Pediatrics (AAP) guidelines for well-child care and the association between compliance and age at diagnosis in a national sample of Medicaid-enrolled children with autism (N = 1,475). Mixed effects linear regression was used to assess the relationship between compliance and age at diagnosis.…

Nursing home case-mix reimbursement in Mississippi and South Dakota.

PubMed

Arling, Greg; Daneman, Barry

2002-04-01

To evaluate the effects of nursing home case-mix reimbursement on facility case mix and costs in Mississippi and South Dakota. Secondary data from resident assessments and Medicaid cost reports from 154 Mississippi and 107 South Dakota nursing facilities in 1992 and 1994, before and after implementation of new case-mix reimbursement systems. The study relied on a two-wave panel design to examine case mix (resident acuity) and direct care costs in 1-year periods before and after implementation of a nursing home case-mix reimbursement system. Cross-lagged regression models were used to assess change in case mix and costs between periods while taking into account facility characteristics. Facility-level measures were constructed from Medicaid cost reports and Minimum Data Set-Plus assessment records supplied by each state. Resident case mix was based on the RUG-III classification system. Facility case-mix scores and direct care costs increased significantly between periods in both states. Changes in facility costs and case mix were significantly related in a positive direction. Medicare utilization and the rate of hospitalizations from the nursing facility also increased significantly between periods, particularly in Mississippi. The case-mix reimbursement systems appeared to achieve their intended goals: improved access for heavy-care residents and increased direct care expenditures in facilities with higher acuity residents. However, increases in Medicare utilization may have influenced facility case mix or costs, and some facilities may have been unprepared to care for higher acuity residents, as indicated by increased rates of hospitalization.

A mixed-method evaluation of peer-education workshops for school-aged children to teach about antibiotics, microbes and hygiene.

PubMed

Young, Vicki L; Cole, Amy; Lecky, Donna M; Fettis, Dennis; Pritchard, Beth; Verlander, Neville Q; Eley, Charlotte V; McNulty, Cliodna A M

2017-07-01

Delivering health topics in schools through peer education is known to be beneficial for all students involved. In this study, we have evaluated a peer-education workshop that aims to educate primary and secondary school students on hygiene, the spread of infection and antibiotics. Four schools in south-west England, in a range of localities, took part in peer-education workshops, with students completing before, after and knowledge-retention questionnaires. Mixed-effect logistic regression and mixed-effect linear regression were used to analyse the data. Data were analysed by topic, region and peer/non-peer-educator status. Qualitative interviews and focus groups with students and educators were conducted to assess changes in participants' skills, confidence and behaviour. Qualitative data indicated improvements in peer-educator skills and behaviour, including confidence, team-working and communication. There was a significant improvement in knowledge for all topics covered in the intervention, although this varied by region. In the antibiotics topic, peer-educators' knowledge increased in the retention questionnaire, whereas non-peer-educators' knowledge decreased. Knowledge declined in the retention questionnaires for the other topics, although this was mostly not significant. This study indicates that peer education is an effective way to educate young people on important topics around health and hygiene, and to concurrently improve communication skills. Its use should be encouraged across schools to help in the implementation of the National Institute for Health and Care Excellence (NICE) guidance that recommends children are taught in an age-appropriate manner about hygiene and antibiotics. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

The Effects of Fat Structures and Ice Cream Mix Viscosity on Physical and Sensory Properties of Ice Cream.

PubMed

Amador, Julia; Hartel, Rich; Rankin, Scott

2017-08-01

The purpose of this work was to investigate iciness perception and other sensory textural attributes of ice cream due to ice and fat structures and mix viscosity. Two studies were carried out varying processing conditions and mix formulation. In the 1st study, ice creams were collected at -3, -5, and -7.5 °C draw temperatures. These ice creams contained 0%, 0.1%, or 0.2% emulsifier, an 80:20 blend of mono- and diglycerides: polysorbate 80. In the 2nd study, ice creams were collected at -3 °C draw temperature and contained 0%, 0.2%, or 0.4% stabilizer, a blend of guar gum, locust bean gum, and carrageenan. Multiple linear regressions were used to determine relationships between ice crystal size, destabilized fat, and sensory iciness. In the ice and fat structure study, an inverse correlation was found between fat destabilization and sensory iciness. Ice creams with no difference in ice crystal size were perceived to be less icy with increasing amounts of destabilized fat. Destabilized fat correlated inversely with drip-through rate and sensory greasiness. In the ice cream mix viscosity study, an inverse correlation was found between mix viscosity and sensory iciness. Ice creams with no difference in ice crystal size were perceived to be less icy when formulated with higher mix viscosity. A positive correlation was found between mix viscosity and sensory greasiness. These results indicate that fat structures and mix viscosity have significant effects on ice cream microstructure and sensory texture including the reduction of iciness perception. © 2017 Institute of Food Technologists®.

Unequal views of inequality: Cross-national support for redistribution 1985-2011.

PubMed

VanHeuvelen, Tom

2017-05-01

This research examines public views on government responsibility to reduce income inequality, support for redistribution. While individual-level correlates of support for redistribution are relatively well understood, many questions remain at the country-level. Therefore, I examine how country-level characteristics affect aggregate support for redistribution. I test explanations of aggregate support using a unique dataset combining 18 waves of the International Social Survey Programme and European Social Survey. Results from mixed-effects logistic regression and fixed-effects linear regression models show two primary and contrasting effects. States that reduce inequality through bundles of tax and transfer policies are rewarded with more supportive publics. In contrast, economic development has a seemingly equivalent and dampening effect on public support. Importantly, the effect of economic development grows at higher levels of development, potentially overwhelming the amplifying effect of state redistribution. My results therefore suggest a fundamental challenge to proponents of egalitarian politics. Copyright © 2016 Elsevier Inc. All rights reserved.

Rural Hospital Ownership: Medical Service Provision, Market Mix, and Spillover Effects

PubMed Central

Horwitz, Jill R; Nichols, Austin

2011-01-01

Objective To test whether nonprofit, for-profit, or government hospital ownership affects medical service provision in rural hospital markets, either directly or through the spillover effects of ownership mix. Data Sources/Study Setting Data are from the American Hospital Association, U.S. Census, CMS Healthcare Cost Report Information System and Prospective Payment System Minimum Data File, and primary data collection for geographic coordinates. The sample includes all nonfederal, general medical, and surgical hospitals located outside of metropolitan statistical areas and within the continental United States from 1988 to 2005. Study Design We estimate multivariate regression models to examine the effects of (1) hospital ownership and (2) hospital ownership mix within rural hospital markets on profitable versus unprofitable medical service offerings. Principal Findings Rural nonprofit hospitals are more likely than for-profit hospitals to offer unprofitable services, many of which are underprovided services. Nonprofits respond less than for-profits to changes in service profitability. Nonprofits with more for-profit competitors offer more profitable services and fewer unprofitable services than those with fewer for-profit competitors. Conclusions Rural hospital ownership affects medical service provision at the hospital and market levels. Nonprofit hospital regulation should reflect both the direct and spillover effects of ownership. PMID:21639860

Rural hospital ownership: medical service provision, market mix, and spillover effects.

PubMed

Horwitz, Jill R; Nichols, Austin

2011-10-01

To test whether nonprofit, for-profit, or government hospital ownership affects medical service provision in rural hospital markets, either directly or through the spillover effects of ownership mix. Data are from the American Hospital Association, U.S. Census, CMS Healthcare Cost Report Information System and Prospective Payment System Minimum Data File, and primary data collection for geographic coordinates. The sample includes all nonfederal, general medical, and surgical hospitals located outside of metropolitan statistical areas and within the continental United States from 1988 to 2005. We estimate multivariate regression models to examine the effects of (1) hospital ownership and (2) hospital ownership mix within rural hospital markets on profitable versus unprofitable medical service offerings. Rural nonprofit hospitals are more likely than for-profit hospitals to offer unprofitable services, many of which are underprovided services. Nonprofits respond less than for-profits to changes in service profitability. Nonprofits with more for-profit competitors offer more profitable services and fewer unprofitable services than those with fewer for-profit competitors. Rural hospital ownership affects medical service provision at the hospital and market levels. Nonprofit hospital regulation should reflect both the direct and spillover effects of ownership. © Health Research and Educational Trust.

The Pediatric Home Care/Expenditure Classification Model (P/ECM): A Home Care Case-Mix Model for Children Facing Special Health Care Challenges.

PubMed

Phillips, Charles D

2015-01-01

Case-mix classification and payment systems help assure that persons with similar needs receive similar amounts of care resources, which is a major equity concern for consumers, providers, and programs. Although health service programs for adults regularly use case-mix payment systems, programs providing health services to children and youth rarely use such models. This research utilized Medicaid home care expenditures and assessment data on 2,578 children receiving home care in one large state in the USA. Using classification and regression tree analyses, a case-mix model for long-term pediatric home care was developed. The Pediatric Home Care/Expenditure Classification Model (P/ECM) grouped children and youth in the study sample into 24 groups, explaining 41% of the variance in annual home care expenditures. The P/ECM creates the possibility of a more equitable, and potentially more effective, allocation of home care resources among children and youth facing serious health care challenges.

The Pediatric Home Care/Expenditure Classification Model (P/ECM): A Home Care Case-Mix Model for Children Facing Special Health Care Challenges

PubMed Central

Phillips, Charles D.

2015-01-01

Case-mix classification and payment systems help assure that persons with similar needs receive similar amounts of care resources, which is a major equity concern for consumers, providers, and programs. Although health service programs for adults regularly use case-mix payment systems, programs providing health services to children and youth rarely use such models. This research utilized Medicaid home care expenditures and assessment data on 2,578 children receiving home care in one large state in the USA. Using classification and regression tree analyses, a case-mix model for long-term pediatric home care was developed. The Pediatric Home Care/Expenditure Classification Model (P/ECM) grouped children and youth in the study sample into 24 groups, explaining 41% of the variance in annual home care expenditures. The P/ECM creates the possibility of a more equitable, and potentially more effective, allocation of home care resources among children and youth facing serious health care challenges. PMID:26740744

Effects of Process Parameters and Cryotreated Electrode on the Radial Overcut of Aisi 304 IN SiC Powder Mixed Edm

NASA Astrophysics Data System (ADS)

Bhaumik, Munmun; Maity, Kalipada

Powder mixed electro discharge machining (PMEDM) is further advancement of conventional electro discharge machining (EDM) where the powder particles are suspended in the dielectric medium to enhance the machining rate as well as surface finish. Cryogenic treatment is introduced in this process for improving the tool life and cutting tool properties. In the present investigation, the characterization of the cryotreated tempered electrode was performed. An attempt has been made to study the effect of cryotreated double tempered electrode on the radial overcut (ROC) when SiC powder is mixed in the kerosene dielectric during electro discharge machining of AISI 304. The process performance has been evaluated by means of ROC when peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameters and machining is performed by using tungsten carbide electrodes (untreated and double tempered electrodes). A regression analysis was performed to correlate the data between the response and the process parameters. Microstructural analysis was carried out on the machined surfaces. Least radial overcut was observed for conventional EDM as compared to powder mixed EDM. Cryotreated double tempered electrode significantly reduced the radial overcut than untreated electrode.

Less money, more problems: How changes in disposable income affect child maltreatment.

PubMed

McLaughlin, Michael

2017-05-01

A number of research studies have documented an association between child maltreatment and family income. Yet, little is known about the specific types of economic shocks that affect child maltreatment rates. The paucity of information is troubling given that more than six million children are reported for maltreatment annually in the U.S. alone. This study examines whether an exogenous shock to families' disposable income, a change in the price of gasoline, predicts changes in child maltreatment. The findings of a fixed-effects regression show that increases in state-level gas prices are associated with increases in state-level child maltreatment referral rates, even after controlling for demographic and other economic variables. The results are robust to the manner of estimation; random-effects and mixed-effects regressions produce similar estimates. The findings suggest that fluctuations in the price of gas may have important consequences for children. Copyright © 2017 Elsevier Ltd. All rights reserved.

Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.

PubMed

Bobb, Jennifer F; Valeri, Linda; Claus Henn, Birgit; Christiani, David C; Wright, Robert O; Mazumdar, Maitreyi; Godleski, John J; Coull, Brent A

2015-07-01

Because humans are invariably exposed to complex chemical mixtures, estimating the health effects of multi-pollutant exposures is of critical concern in environmental epidemiology, and to regulatory agencies such as the U.S. Environmental Protection Agency. However, most health effects studies focus on single agents or consider simple two-way interaction models, in part because we lack the statistical methodology to more realistically capture the complexity of mixed exposures. We introduce Bayesian kernel machine regression (BKMR) as a new approach to study mixtures, in which the health outcome is regressed on a flexible function of the mixture (e.g. air pollution or toxic waste) components that is specified using a kernel function. In high-dimensional settings, a novel hierarchical variable selection approach is incorporated to identify important mixture components and account for the correlated structure of the mixture. Simulation studies demonstrate the success of BKMR in estimating the exposure-response function and in identifying the individual components of the mixture responsible for health effects. We demonstrate the features of the method through epidemiology and toxicology applications. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Pre-natal exposures to cocaine and alcohol and physical growth patterns to age 8 years

PubMed Central

Lumeng, Julie C.; Cabral, Howard J.; Gannon, Katherine; Heeren, Timothy; Frank, Deborah A.

2007-01-01

Two hundred and two primarily African American/Caribbean children (classified by maternal report and infant meconium as 38 heavier, 74 lighter and 89 not cocaine-exposed) were measured repeatedly from birth to age 8 years to assess whether there is an independent effect of prenatal cocaine exposure on physical growth patterns. Children with fetal alcohol syndrome identifiable at birth were excluded. At birth, cocaine and alcohol exposures were significantly and independently associated with lower weight, length and head circumference in cross-sectional multiple regression analyses. The relationship over time of pre-natal exposures to weight, height, and head circumference was then examined by multiple linear regression using mixed linear models including covariates: child’s gestational age, gender, ethnicity, age at assessment, current caregiver, birth mother’s use of alcohol, marijuana and tobacco during the pregnancy and pre-pregnancy weight (for child’s weight) and height (for child’s height and head circumference). The cocaine effects did not persist beyond infancy in piecewise linear mixed models, but a significant and independent negative effect of pre-natal alcohol exposure persisted for weight, height, and head circumference. Catch-up growth in cocaine-exposed infants occurred primarily by 6 months of age for all growth parameters, with some small fluctuations in growth rates in the preschool age range but no detectable differences between heavier versus unexposed nor lighter versus unexposed thereafter. PMID:17412558

Comparing School-Based Teen Pregnancy Prevention Programming: Mixed Outcomes in an At-Risk State.

PubMed

Oman, Roy F; Merritt, Breanca T; Fluhr, Janene; Williams, Jean M

2015-12-01

The purpose of this study is to compare the effectiveness of a national comprehensive teen pregnancy prevention (TPP) intervention to a national abstinence-only TPP intervention on middle school students' knowledge, attitudes, and behaviors related to teen sexual behaviors in a state with high teen birth rates. Pre- and post-intervention data were collected annually (2005-2010) from seventh-grade students to evaluate school-based TPP programs that implemented a comprehensive (N = 3244) or abstinence-only (N = 3172) intervention. Chi-square and t tests, logistic regressions, and hierarchical multiple regressions examined relationships between sexuality-related behavioral intentions, knowledge, and attitudes. Students in both interventions reported significant (p < .05) improvements post-intervention. Youth in the comprehensive TPP intervention were more likely (p < .05) to have significantly improved their attitudes (odds ratios [ORs] = 1.35, 1.83, 1.23) and behavior regarding abstinence decisions in the past 3 months (OR = 1.39). The interventions' improvements in attitudes were more explanatory for behavioral intentions for students in the abstinence-only intervention than for students in the comprehensive TPP intervention. The mixed results suggest the comprehensive TPP intervention was only slightly more effective than the abstinence intervention, but that changing student attitudes and perceptions may be a key component of more effective TPP interventions. © 2015, American School Health Association.

Regression analysis of mixed recurrent-event and panel-count data

PubMed Central

Zhu, Liang; Tong, Xinwei; Sun, Jianguo; Chen, Manhua; Srivastava, Deo Kumar; Leisenring, Wendy; Robison, Leslie L.

2014-01-01

In event history studies concerning recurrent events, two types of data have been extensively discussed. One is recurrent-event data (Cook and Lawless, 2007. The Analysis of Recurrent Event Data. New York: Springer), and the other is panel-count data (Zhao and others, 2010. Nonparametric inference based on panel-count data. Test 20, 1–42). In the former case, all study subjects are monitored continuously; thus, complete information is available for the underlying recurrent-event processes of interest. In the latter case, study subjects are monitored periodically; thus, only incomplete information is available for the processes of interest. In reality, however, a third type of data could occur in which some study subjects are monitored continuously, but others are monitored periodically. When this occurs, we have mixed recurrent-event and panel-count data. This paper discusses regression analysis of such mixed data and presents two estimation procedures for the problem. One is a maximum likelihood estimation procedure, and the other is an estimating equation procedure. The asymptotic properties of both resulting estimators of regression parameters are established. Also, the methods are applied to a set of mixed recurrent-event and panel-count data that arose from a Childhood Cancer Survivor Study and motivated this investigation. PMID:24648408

Using existing case-mix methods to fund trauma cases.

PubMed

Monakova, Julia; Blais, Irene; Botz, Charles; Chechulin, Yuriy; Picciano, Gino; Basinski, Antoni

2010-01-01

Policymakers frequently face the need to increase funding in isolated and frequently heterogeneous (clinically and in terms of resource consumption) patient subpopulations. This article presents a methodologic solution for testing the appropriateness of using existing grouping and weighting methodologies for funding subsets of patients in the scenario where a case-mix approach is preferable to a flat-rate based payment system. Using as an example the subpopulation of trauma cases of Ontario lead trauma hospitals, the statistical techniques of linear and nonlinear regression models, regression trees, and spline models were applied to examine the fit of the existing case-mix groups and reference weights for the trauma cases. The analyses demonstrated that for funding Ontario trauma cases, the existing case-mix systems can form the basis for rational and equitable hospital funding, decreasing the need to develop a different grouper for this subset of patients. This study confirmed that Injury Severity Score is a poor predictor of costs for trauma patients. Although our analysis used the Canadian case-mix classification system and cost weights, the demonstrated concept of using existing case-mix systems to develop funding rates for specific subsets of patient populations may be applicable internationally.

Random effects coefficient of determination for mixed and meta-analysis models.

PubMed

Demidenko, Eugene; Sargent, James; Onega, Tracy

2012-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

EPA Science Inventory

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on ...

Regression analysis of mixed recurrent-event and panel-count data with additive rate models.

PubMed

Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L

2015-03-01

Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007, The Statistical Analysis of Recurrent Events. New York: Springer-Verlag; Zhao et al., 2011, Test 20, 1-42). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013, Statistics in Medicine 32, 1954-1963). In this article, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. © 2014, The International Biometric Society.

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

Two biased estimation techniques in linear regression: Application to aircraft

NASA Technical Reports Server (NTRS)

Klein, Vladislav

1988-01-01

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Stress and health behaviors as potential mediators of the relationship between neighborhood quality and allostatic load.

PubMed

Buschmann, Robert N; Prochaska, John D; Cutchin, Malcolm P; Peek, M Kristen

2018-03-29

Neighborhood quality is associated with health. Increasingly, researchers are focusing on the mechanisms underlying that association, including the role of stress, risky health behaviors, and subclinical measures such as allostatic load (AL). This study uses mixed-effects regression modeling to examine the association between two objective measures and one subjective measure of neighborhood quality and AL in an ethnically diverse population-based sample (N = 2706) from a medium-sized Texas city. We also examine whether several measures of psychological stress and health behaviors mediate any relationship between neighborhood quality and AL. In this sample, all three separate measures of neighborhood quality were associated with individual AL (P < .01). However, only the subjective measure, perceived neighborhood quality, was associated with AL after adjusting for covariates. In mixed-effects multiple regression models there was no evidence of mediation by either stress or health behaviors. In this study, only one measure of neighborhood quality was related to a measure of health, which contrasts with considerable previous research in this area. In this sample, neighborhood quality may affect AL through other mechanisms, or there may be other health-affecting factors is this area that share that overshadow local neighborhood variation. Copyright © 2018 Elsevier Inc. All rights reserved.

[Key physical parameters of hawthorn leaf granules by stepwise regression analysis method].

PubMed

Jiang, Qie-Ying; Zeng, Rong-Gui; Li, Zhe; Luo, Juan; Zhao, Guo-Wei; Lv, Dan; Liao, Zheng-Gen

2017-05-01

The purpose of this study was to investigate the effect of key physical properties of hawthorn leaf granule on its dissolution behavior. Hawthorn leaves extract was utilized as a model drug. The extract was mixed with microcrystalline cellulose or starch with the same ratio by using different methods. Appropriate amount of lubricant and disintegrating agent was added into part of the mixed powder, and then the granules were prepared by using extrusion granulation and high shear granulation. The granules dissolution behavior was evaluated by using equilibrium dissolution quantity and dissolution rate constant of the hypericin as the indicators. Then the effect of physical properties on dissolution behavior was analyzed through the stepwise regression analysis method. The equilibrium dissolution quantity of hypericin and adsorption heat constant in hawthorn leaves were positively correlated with the monolayer adsorption capacity and negatively correlated with the moisture absorption rate constant. The dissolution rate constants were decreased with the increase of Hausner rate, monolayer adsorption capacity and adsorption heat constant, and were increased with the increase of Carr index and specific surface area. Adsorption heat constant, monolayer adsorption capacity, moisture absorption rate constant, Carr index and specific surface area were the key physical properties of hawthorn leaf granule to affect its dissolution behavior. Copyright© by the Chinese Pharmaceutical Association.

The long-solved problem of the best-fit straight line: Application to isotopic mixing lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wehr, Richard; Saleska, Scott R.

It has been almost 50 years since York published an exact and general solution for the best-fit straight line to independent points with normally distributed errors in both x and y. York's solution is highly cited in the geophysical literature but almost unknown outside of it, so that there has been no ebb in the tide of books and papers wrestling with the problem. Much of the post-1969 literature on straight-line fitting has sown confusion not merely by its content but by its very existence. The optimal least-squares fit is already known; the problem is already solved. Here we introducemore » the non-specialist reader to York's solution and demonstrate its application in the interesting case of the isotopic mixing line, an analytical tool widely used to determine the isotopic signature of trace gas sources for the study of biogeochemical cycles. The most commonly known linear regression methods – ordinary least-squares regression (OLS), geometric mean regression (GMR), and orthogonal distance regression (ODR) – have each been recommended as the best method for fitting isotopic mixing lines. In fact, OLS, GMR, and ODR are all special cases of York's solution that are valid only under particular measurement conditions, and those conditions do not hold in general for isotopic mixing lines. Here, using Monte Carlo simulations, we quantify the biases in OLS, GMR, and ODR under various conditions and show that York's general – and convenient – solution is always the least biased.« less

The long-solved problem of the best-fit straight line: Application to isotopic mixing lines

DOE PAGES

Wehr, Richard; Saleska, Scott R.

2017-01-03

It has been almost 50 years since York published an exact and general solution for the best-fit straight line to independent points with normally distributed errors in both x and y. York's solution is highly cited in the geophysical literature but almost unknown outside of it, so that there has been no ebb in the tide of books and papers wrestling with the problem. Much of the post-1969 literature on straight-line fitting has sown confusion not merely by its content but by its very existence. The optimal least-squares fit is already known; the problem is already solved. Here we introducemore » the non-specialist reader to York's solution and demonstrate its application in the interesting case of the isotopic mixing line, an analytical tool widely used to determine the isotopic signature of trace gas sources for the study of biogeochemical cycles. The most commonly known linear regression methods – ordinary least-squares regression (OLS), geometric mean regression (GMR), and orthogonal distance regression (ODR) – have each been recommended as the best method for fitting isotopic mixing lines. In fact, OLS, GMR, and ODR are all special cases of York's solution that are valid only under particular measurement conditions, and those conditions do not hold in general for isotopic mixing lines. Here, using Monte Carlo simulations, we quantify the biases in OLS, GMR, and ODR under various conditions and show that York's general – and convenient – solution is always the least biased.« less

Exploring the effects of coexisting amyloid in subcortical vascular cognitive impairment.

PubMed

Dao, Elizabeth; Hsiung, Ging-Yuek Robin; Sossi, Vesna; Jacova, Claudia; Tam, Roger; Dinelle, Katie; Best, John R; Liu-Ambrose, Teresa

2015-10-12

Mixed pathology, particularly Alzheimer's disease with cerebrovascular lesions, is reported as the second most common cause of dementia. Research on mixed dementia typically includes people with a primary AD diagnosis and hence, little is known about the effects of co-existing amyloid pathology in people with vascular cognitive impairment (VCI). The purpose of this study was to understand whether individual differences in amyloid pathology might explain variations in cognitive impairment among individuals with clinical subcortical VCI (SVCI). Twenty-two participants with SVCI completed an (11)C Pittsburgh compound B (PIB) position emission tomography (PET) scan to quantify global amyloid deposition. Cognitive function was measured using: 1) MOCA; 2) ADAS-Cog; 3) EXIT-25; and 4) specific executive processes including a) Digits Forward and Backwards Test, b) Stroop-Colour Word Test, and c) Trail Making Test. To assess the effect of amyloid deposition on cognitive function we conducted Pearson bivariate correlations to determine which cognitive measures to include in our regression models. Cognitive variables that were significantly correlated with PIB retention values were entered in a hierarchical multiple linear regression analysis to determine the unique effect of amyloid on cognitive function. We controlled for age, education, and ApoE ε4 status. Bivariate correlation results showed that PIB binding was significantly correlated with ADAS-Cog (p < 0.01) and MOCA (p < 0.01); increased PIB binding was associated with worse cognitive function on both cognitive measures. PIB binding was not significantly correlated with the EXIT-25 or with specific executive processes (p > 0.05). Regression analyses controlling for age, education, and ApoE ε4 status indicated an independent association between PIB retention and the ADAS-Cog (adjusted R-square change of 15.0%, Sig F Change = 0.03). PIB retention was also independently associated with MOCA scores (adjusted R-Square Change of 27.0%, Sig F Change = 0.02). We found that increased global amyloid deposition was significantly associated with greater memory and executive dysfunctions as measured by the ADAS-Cog and MOCA. Our findings point to the important role of co-existing amyloid deposition for cognitive function in those with a primary SVCI diagnosis. As such, therapeutic approaches targeting SVCI must consider the potential role of amyloid for the optimal care of those with mixed dementia. NCT01027858.

Real medical benefit assessed by indirect comparison.

PubMed

Falissard, Bruno; Zylberman, Myriam; Cucherat, Michel; Izard, Valérie; Meyer, François

2009-01-01

Frequently, in data packages submitted for Marketing Approval to the CHMP, there is a lack of relevant head-to-head comparisons of medicinal products that could enable national authorities responsible for the approval of reimbursement to assess the Added Therapeutic Value (ASMR) of new clinical entities or line extensions of existing therapies.Indirect or mixed treatment comparisons (MTC) are methods stemming from the field of meta-analysis that have been designed to tackle this problem. Adjusted indirect comparisons, meta-regressions, mixed models, Bayesian network analyses pool results of randomised controlled trials (RCTs), enabling a quantitative synthesis.The REAL procedure, recently developed by the HAS (French National Authority for Health), is a mixture of an MTC and effect model based on expert opinions. It is intended to translate the efficacy observed in the trials into effectiveness expected in day-to-day clinical practice in France.

The role of gender in a smoking cessation intervention: a cluster randomized clinical trial.

PubMed

Puente, Diana; Cabezas, Carmen; Rodriguez-Blanco, Teresa; Fernández-Alonso, Carmen; Cebrian, Tránsito; Torrecilla, Miguel; Clemente, Lourdes; Martín, Carlos

2011-05-23

The prevalence of smoking in Spain is high in both men and women. The aim of our study was to evaluate the role of gender in the effectiveness of a specific smoking cessation intervention conducted in Spain. This study was a secondary analysis of a cluster randomized clinical trial in which the randomization unit was the Basic Care Unit (family physician and nurse who care for the same group of patients). The intervention consisted of a six-month period of implementing the recommendations of a Clinical Practice Guideline. A total of 2,937 current smokers at 82 Primary Care Centers in 13 different regions of Spain were included (2003-2005). The success rate was measured by a six-month continued abstinence rate at the one-year follow-up. A logistic mixed-effects regression model, taking Basic Care Units as random-effect parameter, was performed in order to analyze gender as a predictor of smoking cessation. At the one-year follow-up, the six-month continuous abstinence quit rate was 9.4% in men and 8.5% in women (p = 0.400). The logistic mixed-effects regression model showed that women did not have a higher odds of being an ex-smoker than men after the analysis was adjusted for confounders (OR adjusted = 0.9, 95% CI = 0.7-1.2). Gender does not appear to be a predictor of smoking cessation at the one-year follow-up in individuals presenting at Primary Care Centers. CLINICALTRIALS.GOV IDENTIFIER: NCT00125905.

An overview of longitudinal data analysis methods for neurological research.

PubMed

Locascio, Joseph J; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Medicaid payment rates, case-mix reimbursement, and nursing home staffing--1996-2004.

PubMed

Feng, Zhanlian; Grabowski, David C; Intrator, Orna; Zinn, Jacqueline; Mor, Vincent

2008-01-01

We examined the impact of state Medicaid payment rates and case-mix reimbursement on direct care staffing levels in US nursing homes. We used a recent time series of national nursing home data from the Online Survey Certification and Reporting system for 1996-2004, merged with annual state Medicaid payment rates and case-mix reimbursement information. A 5-category response measure of total staffing levels was defined according to expert recommended thresholds, and examined in a multinomial logistic regression model. Facility fixed-effects models were estimated separately for Registered Nurse (RN), Licensed Practical Nurse (LPN), and Certified Nurse Aide (CNA) staffing levels measured as average hours per resident day. Higher Medicaid payment rates were associated with increases in total staffing levels to meet a higher recommended threshold. However, these gains in overall staffing were accompanied by a reduction of RN staffing and an increase in both LPN and CNA staffing levels. Under case-mix reimbursement, the likelihood of nursing homes achieving higher recommended staffing thresholds decreased, as did levels of professional staffing. Independent of the effects of state, market, and facility characteristics, there was a significant downward trend in RN staffing and an upward trend in both LPN and CNA staffing. Although overall staffing may increase in response to more generous Medicaid reimbursement, it may not translate into improvements in the skill mix of staff. Adjusting for reimbursement levels and resident acuity, total staffing has not increased after the implementation of case-mix reimbursement.

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate which Fires Produce Ozone

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Andreae, Meinrat O.

2016-01-01

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(burn) = delta C(tot) added to the fire plume, where C(tot) approximately equals (CO2 = CO). Mixed-effects regression can estimate pre-fire background values of C(tot) (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta, epsilon lambda tau alpha-x(sub I)/C(sub burn))I,j. MERET and "consensus" require more than emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (b scant, b abs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate Which Fires Produce Ozone

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Andreae, Meinrat O.

2015-01-01

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(sub burn) = delta C(sub tot) added to the fire plume, where C(sub tot) approximately equals (CO2 + CO). Mixed-effects regression can estimate pre-fire background values of Ctot (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta epsilon lambda tau alpha-x(sub i)/(C(sub burn))i,j., MERET and "consensus" require more than two emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (bscat, babs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics.

Comparability of the effect of storage time and temperature on serum anti-Müllerian hormone measurement between original and modified enzyme-linked immunosorbent assay.

PubMed

Yue, Chao-Yan; Ying, Chun-Mei

2017-01-01

To explore the effect of modified enzyme-linked immunosorbent assay on the AMH results is increased or decreased, and to investigate the effect of storage time and temperature on AMH measurements with and without sample premixing assay buffer using the Kangrun ELISA method. Serum AMH concentration were measured by ELISA, consistency between two kits, and comparability between original and the modified assay under different stored conditions were analyzed by Passing-Bablok regression analysis and Bland-Altman bias evaluation. There was a strong consistency between AMH concentrations measured in Kangrun ELISA and Ansh Labs ultra-sensitive AMH ELISA. Pre-mixing serum specimens with assay buffer gave consistent results compared with original assay. Modified protocol can reduce the amplitude of increase affected by sample aged and give the most consistent results regardless of storage conditions. Pre-mixing protocol did not influence the results of fresh serum or frozen serum incubation <3days at 4°C and -80°C, but when specimens detected after collection and stored in other storage conditions, should be pre-mixed with assay buffer to insure its accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

Advanced Statistical Analyses to Reduce Inconsistency of Bond Strength Data.

PubMed

Minamino, T; Mine, A; Shintani, A; Higashi, M; Kawaguchi-Uemura, A; Kabetani, T; Hagino, R; Imai, D; Tajiri, Y; Matsumoto, M; Yatani, H

2017-11-01

This study was designed to clarify the interrelationship of factors that affect the value of microtensile bond strength (µTBS), focusing on nondestructive testing by which information of the specimens can be stored and quantified. µTBS test specimens were prepared from 10 noncarious human molars. Six factors of µTBS test specimens were evaluated: presence of voids at the interface, X-ray absorption coefficient of resin, X-ray absorption coefficient of dentin, length of dentin part, size of adhesion area, and individual differences of teeth. All specimens were observed nondestructively by optical coherence tomography and micro-computed tomography before µTBS testing. After µTBS testing, the effect of these factors on µTBS data was analyzed by the general linear model, linear mixed effects regression model, and nonlinear regression model with 95% confidence intervals. By the general linear model, a significant difference in individual differences of teeth was observed ( P < 0.001). A significantly positive correlation was shown between µTBS and length of dentin part ( P < 0.001); however, there was no significant nonlinearity ( P = 0.157). Moreover, a significantly negative correlation was observed between µTBS and size of adhesion area ( P = 0.001), with significant nonlinearity ( P = 0.014). No correlation was observed between µTBS and X-ray absorption coefficient of resin ( P = 0.147), and there was no significant nonlinearity ( P = 0.089). Additionally, a significantly positive correlation was observed between µTBS and X-ray absorption coefficient of dentin ( P = 0.022), with significant nonlinearity ( P = 0.036). A significant difference was also observed between the presence and absence of voids by linear mixed effects regression analysis. Our results showed correlations between various parameters of tooth specimens and µTBS data. To evaluate the performance of the adhesive more precisely, the effect of tooth variability and a method to reduce variation in bond strength values should also be considered.

Effects of photochemical oxidation on the mixing state and light absorption of black carbon in the urban atmosphere of China

NASA Astrophysics Data System (ADS)

Wang, Qiyuan; Huang, Rujin; Zhao, Zhuzi; Cao, Junji; Ni, Haiyan; Tie, Xuexi; Zhu, Chongshu; Shen, Zhenxing; Wang, Meng; Dai, Wenting; Han, Yongming; Zhang, Ningning; Prévôt, André S. H.

2017-04-01

The relationship between the refractory black carbon (rBC) aerosol mixing state and the atmospheric oxidation capacity was investigated to assess the possible influence of oxidants on the particles’ light absorption effects at two large cities in China. The number fraction of thickly-coated rBC particles (F rBC) was positively correlated with a measure of the oxidant concentrations (OX = O3 + NO2), indicating an enhancement of coated rBC particles under more oxidizing conditions. The slope of a linear regression of F rBC versus OX was 0.58% ppb-1 for Beijing and 0.84% ppb-1 for Xi’an, and these relationships provide some insights into the evolution of rBC mixing state in relation to atmospheric oxidation processes. The mass absorption cross-section of rBC (MACrBC) increased with OX during the daytime at Xi’an, at a rate of 0.26 m2 g-1 ppb-1, suggesting that more oxidizing conditions lead to internal mixing that enhances the light-absorbing capacity of rBC particles. Understanding the dependence of the increasing rates of F rBC and MACrBC as a function of OX may lead to improvements of climate models that deal with the warming effects, but more studies in different cities and seasons are needed to gauge the broader implications of these findings.

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

PubMed

Zhang, Xueying; Chu, Yiyi; Wang, Yuxuan; Zhang, Kai

2018-08-01

The regulatory monitoring data of particulate matter with an aerodynamic diameter <2.5μm (PM 2.5 ) in Texas have limited spatial and temporal coverage. The purpose of this study is to estimate the ground-level PM 2.5 concentrations on a daily basis using satellite-retrieved Aerosol Optical Depth (AOD) in the state of Texas. We obtained the AOD values at 1-km resolution generated through the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm based on the images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM 2.5 concentrations (μg/m 3 ) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R 2 ) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. Mixed-effects regression models showed good prediction performance (R 2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R 2 : 0.62 for the East region; R 2 : 0.69 for the year of 2009). The PM 2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM 2.5 in more polluted areas. Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM 2.5 in Texas. Predicted PM 2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM 2.5 in Texas. Copyright © 2017 Elsevier B.V. All rights reserved.

The creation and evaluation of a model to simulate the probability of conception in seasonal-calving pasture-based dairy heifers.

PubMed

Fenlon, Caroline; O'Grady, Luke; Butler, Stephen; Doherty, Michael L; Dunnion, John

2017-01-01

Herd fertility in pasture-based dairy farms is a key driver of farm economics. Models for predicting nulliparous reproductive outcomes are rare, but age, genetics, weight, and BCS have been identified as factors influencing heifer conception. The aim of this study was to create a simulation model of heifer conception to service with thorough evaluation. Artificial Insemination service records from two research herds and ten commercial herds were provided to build and evaluate the models. All were managed as spring-calving pasture-based systems. The factors studied were related to age, genetics, and time of service. The data were split into training and testing sets and bootstrapping was used to train the models. Logistic regression (with and without random effects) and generalised additive modelling were selected as the model-building techniques. Two types of evaluation were used to test the predictive ability of the models: discrimination and calibration. Discrimination, which includes sensitivity, specificity, accuracy and ROC analysis, measures a model's ability to distinguish between positive and negative outcomes. Calibration measures the accuracy of the predicted probabilities with the Hosmer-Lemeshow goodness-of-fit, calibration plot and calibration error. After data cleaning and the removal of services with missing values, 1396 services remained to train the models and 597 were left for testing. Age, breed, genetic predicted transmitting ability for calving interval, month and year were significant in the multivariate models. The regression models also included an interaction between age and month. Year within herd was a random effect in the mixed regression model. Overall prediction accuracy was between 77.1% and 78.9%. All three models had very high sensitivity, but low specificity. The two regression models were very well-calibrated. The mean absolute calibration errors were all below 4%. Because the models were not adept at identifying unsuccessful services, they are not suggested for use in predicting the outcome of individual heifer services. Instead, they are useful for the comparison of services with different covariate values or as sub-models in whole-farm simulations. The mixed regression model was identified as the best model for prediction, as the random effects can be ignored and the other variables can be easily obtained or simulated.

Covariate Selection for Multilevel Models with Missing Data

PubMed Central

Marino, Miguel; Buxton, Orfeu M.; Li, Yi

2017-01-01

Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

Bayesian Nonparametric Inference – Why and How

PubMed Central

Müller, Peter; Mitra, Riten

2013-01-01

We review inference under models with nonparametric Bayesian (BNP) priors. The discussion follows a set of examples for some common inference problems. The examples are chosen to highlight problems that are challenging for standard parametric inference. We discuss inference for density estimation, clustering, regression and for mixed effects models with random effects distributions. While we focus on arguing for the need for the flexibility of BNP models, we also review some of the more commonly used BNP models, thus hopefully answering a bit of both questions, why and how to use BNP. PMID:24368932

Regression analysis of mixed recurrent-event and panel-count data.

PubMed

Zhu, Liang; Tong, Xinwei; Sun, Jianguo; Chen, Manhua; Srivastava, Deo Kumar; Leisenring, Wendy; Robison, Leslie L

2014-07-01

In event history studies concerning recurrent events, two types of data have been extensively discussed. One is recurrent-event data (Cook and Lawless, 2007. The Analysis of Recurrent Event Data. New York: Springer), and the other is panel-count data (Zhao and others, 2010. Nonparametric inference based on panel-count data. Test 20: , 1-42). In the former case, all study subjects are monitored continuously; thus, complete information is available for the underlying recurrent-event processes of interest. In the latter case, study subjects are monitored periodically; thus, only incomplete information is available for the processes of interest. In reality, however, a third type of data could occur in which some study subjects are monitored continuously, but others are monitored periodically. When this occurs, we have mixed recurrent-event and panel-count data. This paper discusses regression analysis of such mixed data and presents two estimation procedures for the problem. One is a maximum likelihood estimation procedure, and the other is an estimating equation procedure. The asymptotic properties of both resulting estimators of regression parameters are established. Also, the methods are applied to a set of mixed recurrent-event and panel-count data that arose from a Childhood Cancer Survivor Study and motivated this investigation. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Correcting for population structure and kinship using the linear mixed model: theory and extensions.

PubMed

Hoffman, Gabriel E

2013-01-01

Population structure and kinship are widespread confounding factors in genome-wide association studies (GWAS). It has been standard practice to include principal components of the genotypes in a regression model in order to account for population structure. More recently, the linear mixed model (LMM) has emerged as a powerful method for simultaneously accounting for population structure and kinship. The statistical theory underlying the differences in empirical performance between modeling principal components as fixed versus random effects has not been thoroughly examined. We undertake an analysis to formalize the relationship between these widely used methods and elucidate the statistical properties of each. Moreover, we introduce a new statistic, effective degrees of freedom, that serves as a metric of model complexity and a novel low rank linear mixed model (LRLMM) to learn the dimensionality of the correction for population structure and kinship, and we assess its performance through simulations. A comparison of the results of LRLMM and a standard LMM analysis applied to GWAS data from the Multi-Ethnic Study of Atherosclerosis (MESA) illustrates how our theoretical results translate into empirical properties of the mixed model. Finally, the analysis demonstrates the ability of the LRLMM to substantially boost the strength of an association for HDL cholesterol in Europeans.

Pectin methyl esterase and natural microflora of fresh mixed orange and carrot juice treated with pulsed electric fields.

PubMed

Rodrigo, D; Barbosa-Cánovas, G V; Martínez, A; Rodrigo, M

2003-12-01

The effects of pulsed electric fields (PEFs) on pectin methyl esterase (PME), molds and yeast, and total flora in fresh (nonpasteurized) mixed orange and carrot juice were studied. The PEF effect was more extensive when juices with high levels of initial PME activity were subjected to treatment and when PEF treatment (at 25 kV/cm for 340 micros) was combined with a moderate temperature (63 degrees C), with the maximum level of PME inactivation being 81.4%. These conditions produced 3.7 decimal reductions in molds and yeast and 2.4 decimal reductions in total flora. Experimental inactivation data for PME, molds and yeast, and total flora were fitted to Bigelow, Hülsheger, and Weibull inactivation models by nonlinear regression. The best fit (lowest mean square error) was obtained with the Weibull model.

Non-homogeneous hybrid rocket fuel for enhanced regression rates utilizing partial entrainment

NASA Astrophysics Data System (ADS)

Boronowsky, Kenny

A concept was developed and tested to enhance the performance and regression rate of hydroxyl terminated polybutadiene (HTPB), a commonly used hybrid rocket fuel. By adding small nodules of paraffin into the HTPB fuel, a non-homogeneous mixture was created resulting in increased regression rates. The goal was to develop a fuel with a simplified single core geometry and a tailorable regression rate. The new fuel would benefit from the structural stability of HTPB yet not suffer from the large void fraction representative of typical HTPB core geometries. Regression rates were compared between traditional HTPB single core grains, 85% HTPB mixed with 15% (by weight) paraffin cores, 70% HTPB mixed with 30% paraffin cores, and plain paraffin single core grains. Each fuel combination was tested at oxidizer flow rates, ranging from 0.9 - 3.3 g/s of gaseous oxygen, in a small scale hybrid test rocket and average regression rates were measured. While large uncertainties were present in the experimental setup, the overall data showed that the regression rate was enhanced as paraffin concentration increased. While further testing would be required at larger scales of interest, the trends are encouraging. Inclusion of paraffin nodules in the HTPB grain may produce a greater advantage than other more noxious additives in current use. In addition, it may lead to safer rocket motors with higher integrated thrust due to the decreased void fraction.

Comparing transfusion reaction rates for various plasma types: a systematic review and meta-analysis/regression.

PubMed

Saadah, Nicholas H; van Hout, Fabienne M A; Schipperus, Martin R; le Cessie, Saskia; Middelburg, Rutger A; Wiersum-Osselton, Johanna C; van der Bom, Johanna G

2017-09-01

We estimated rates for common plasma-associated transfusion reactions and compared reported rates for various plasma types. We performed a systematic review and meta-analysis of peer-reviewed articles that reported plasma transfusion reaction rates. Random-effects pooled rates were calculated and compared between plasma types. Meta-regression was used to compare various plasma types with regard to their reported plasma transfusion reaction rates. Forty-eight studies reported transfusion reaction rates for fresh-frozen plasma (FFP; mixed-sex and male-only), amotosalen INTERCEPT FFP, methylene blue-treated FFP, and solvent/detergent-treated pooled plasma. Random-effects pooled average rates for FFP were: allergic reactions, 92/10 5 units transfused (95% confidence interval [CI], 46-184/10 5 units transfused); febrile nonhemolytic transfusion reactions (FNHTRs), 12/10 5 units transfused (95% CI, 7-22/10 5 units transfused); transfusion-associated circulatory overload (TACO), 6/10 5 units transfused (95% CI, 1-30/10 5 units transfused); transfusion-related acute lung injury (TRALI), 1.8/10 5 units transfused (95% CI, 1.2-2.7/10 5 units transfused); and anaphylactic reactions, 0.8/10 5 units transfused (95% CI, 0-45.7/10 5 units transfused). Risk differences between plasma types were not significant for allergic reactions, TACO, or anaphylactic reactions. Methylene blue-treated FFP led to fewer FNHTRs than FFP (risk difference = -15.3 FNHTRs/10 5 units transfused; 95% CI, -24.7 to -7.1 reactions/10 5 units transfused); and male-only FFP led to fewer cases of TRALI than mixed-sex FFP (risk difference = -0.74 TRALI/10 5 units transfused; 95% CI, -2.42 to -0.42 injuries/10 5 units transfused). Meta-regression demonstrates that the rate of FNHTRs is lower for methylene blue-treated compared with FFP, and the rate of TRALI is lower for male-only than for mixed-sex FFP; whereas no significant differences are observed between plasma types for allergic reactions, TACO, or anaphylactic reactions. Reported transfusion reaction rates suffer from high heterogeneity. © 2017 AABB.

Understanding the Impact of School Factors on School Counselor Burnout: A Mixed-Methods Study

ERIC Educational Resources Information Center

Bardhoshi, Gerta; Schweinle, Amy; Duncan, Kelly

2014-01-01

This mixed-methods study investigated the relationship between burnout and performing noncounseling duties among a national sample of professional school counselors, while identifying school factors that could attenuate this relationship. Results of regression analyses indicate that performing noncounseling duties significantly predicted burnout…

D.b.h./crown diameter relationships in mixed Appalachian hardwood stands

Treesearch

Neil I. Lamson; Neil I. Lamson

1987-01-01

Linear regression formulae for predicting crown diameter as a function of stem diameter are presented for nine species found in 50- to 80-year-old mixed hardwood stands in north-central West Virginia. Generally, crown diameter was closely related to tolerance; more tolerant species had larger crowns.

Cox Regression Models with Functional Covariates for Survival Data.

PubMed

Gellar, Jonathan E; Colantuoni, Elizabeth; Needham, Dale M; Crainiceanu, Ciprian M

2015-06-01

We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criterion such as AIC or EPIC. The model may be extended to allow for multiple functional predictors, time varying coefficients, and missing or unequally-spaced data. Methods were inspired by and applied to a study of the association between time to death after hospital discharge and daily measures of disease severity collected in the intensive care unit, among survivors of acute respiratory distress syndrome.

Improving Lidar-based Aboveground Biomass Estimation with Site Productivity for Central Hardwood Forests, USA

NASA Astrophysics Data System (ADS)

Shao, G.; Gallion, J.; Fei, S.

2016-12-01

Sound forest aboveground biomass estimation is required to monitor diverse forest ecosystems and their impacts on the changing climate. Lidar-based regression models provided promised biomass estimations in most forest ecosystems. However, considerable uncertainties of biomass estimations have been reported in the temperate hardwood and hardwood-dominated mixed forests. Varied site productivities in temperate hardwood forests largely diversified height and diameter growth rates, which significantly reduced the correlation between tree height and diameter at breast height (DBH) in mature and complex forests. It is, therefore, difficult to utilize height-based lidar metrics to predict DBH-based field-measured biomass through a simple regression model regardless the variation of site productivity. In this study, we established a multi-dimension nonlinear regression model incorporating lidar metrics and site productivity classes derived from soil features. In the regression model, lidar metrics provided horizontal and vertical structural information and productivity classes differentiated good and poor forest sites. The selection and combination of lidar metrics were discussed. Multiple regression models were employed and compared. Uncertainty analysis was applied to the best fit model. The effects of site productivity on the lidar-based biomass model were addressed.

An Overview of Longitudinal Data Analysis Methods for Neurological Research

PubMed Central

Locascio, Joseph J.; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models. PMID:22203825

Radio Propagation Prediction Software for Complex Mixed Path Physical Channels

DTIC Science & Technology

2006-08-14

63 4.4.6. Applied Linear Regression Analysis in the Frequency Range 1-50 MHz 69 4.4.7. Projected Scaling to...4.4.6. Applied Linear Regression Analysis in the Frequency Range 1-50 MHz In order to construct a comprehensive numerical algorithm capable of

Multilevel Models for Binary Data

ERIC Educational Resources Information Center

Powers, Daniel A.

2012-01-01

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

Acculturation, childhood trauma and the cortisol awakening response in Mexican-American adults.

PubMed

Mangold, Deborah; Wand, Gary; Javors, Martin; Mintz, James

2010-09-01

Exposure to chronic and traumatic stress has been associated with the dysregulation of crucial stress response systems. Acculturation has been associated with unique forms of chronic psychosocial stress. The purpose of this study was to examine the effects of exposure to early traumatic stress and acculturation on dysregulation of the cortisol awakening response (CAR) in Mexican-American adults. Salivary cortisol samples were collected at awakening and 30, 45, and 60 min thereafter, on two consecutive weekdays from 59 healthy Mexican-American adult males (26) and females (33), ages 18-38 years. Participants were assessed for level of acculturation and exposure to early trauma. Data were analyzed using a mixed effects regression model with repeated measures at four time points. Mixed effects regression results indicated a significant Early Trauma x Time interaction (p=.0029) and a significant Acculturation x Time interaction (p=.0015), after controlling for age and sex. Subsequent analyses of the interaction of Trauma x Acculturation x Time showed that more than minimal exposure to either risk factor was associated with attenuation of the awakening cortisol response (p=.0002). Higher levels of acculturation with greater Anglo-orientation were associated with attenuation of the CAR in Mexican-American adults. Both moderate and higher levels of exposure to early trauma were associated with an attenuated CAR. However, greater exposure to both risk factors was only incrementally worse than exposure to either one. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Peat soils stabilization using Effective Microorganisms (EM)

NASA Astrophysics Data System (ADS)

Yusof, N. Z.; Samsuddin, N. S.; Hanif, M. F.; Syed Osman, S. B.

2018-04-01

Peat soil is known as geotechnical problematic soil since it is the softest soil having highly organic and moisture content which led to high compressibility, low shear strength and long-term settlement. The aim of this study was to obtain the stabilized peat soils using the Effective Microorganisms (EM). The volume of EM added and mixed with peat soils varied with 2%, 4%, 6%, 8% and 10% and then were cured for 7, 14 and 21 days. The experiment was done for uncontrolled and controlled moisture content. Prior conducting the main experiments, the physical properties such as moisture content, liquid limit, specific gravity, and plastic limit etc. were measure for raw peat samples. The Unconfined Compressive Strength (UCS) test was performed followed by regression analysis to check the effect of EM on the soil strength. Obtained results have shown that the mix design for controlled moisture contents showed the promising improvement in their compressive strength. The peat soil samples with 10% of EM shows the highest increment in UCS value and the percentage of increments are in the range of 44% to 65% after curing for 21 days. The regression analysis of the EM with the soil compressive strength showed that in controlled moisture conditions, EM significantly improved the soil stability as the value of R2 ranged between 0.97 – 0.78. The results have indicated that the addition of EM in peat soils provides significant improving in the strength of the soil as well as the other engineering properties.

Comparison of response patterns in different survey designs: a longitudinal panel with mixed-mode and online-only design.

PubMed

Rübsamen, Nicole; Akmatov, Manas K; Castell, Stefanie; Karch, André; Mikolajczyk, Rafael T

2017-01-01

Increasing availability of the Internet allows using only online data collection for more epidemiological studies. We compare response patterns in a population-based health survey using two survey designs: mixed-mode (choice between paper-and-pencil and online questionnaires) and online-only design (without choice). We used data from a longitudinal panel, the Hygiene and Behaviour Infectious Diseases Study (HaBIDS), conducted in 2014/2015 in four regions in Lower Saxony, Germany. Individuals were recruited using address-based probability sampling. In two regions, individuals could choose between paper-and-pencil and online questionnaires. In the other two regions, individuals were offered online-only participation. We compared sociodemographic characteristics of respondents who filled in all panel questionnaires between the mixed-mode group (n = 1110) and the online-only group (n = 482). Using 134 items, we performed multinomial logistic regression to compare responses between survey designs in terms of type (missing, "do not know" or valid response) and ordinal regression to compare responses in terms of content. We applied the false discovery rates (FDR) to control for multiple testing and investigated effects of adjusting for sociodemographic characteristic. For validation of the differential response patterns between mixed-mode and online-only, we compared the response patterns between paper and online mode among the respondents in the mixed-mode group in one region (n = 786). Respondents in the online-only group were older than those in the mixed-mode group, but both groups did not differ regarding sex or education. Type of response did not differ between the online-only and the mixed-mode group. Survey design was associated with different content of response in 18 of the 134 investigated items; which decreased to 11 after adjusting for sociodemographic variables. In the validation within the mixed-mode, only two of those were among the 11 significantly different items. The probability of observing by chance the same two or more significant differences in this setting was 22%. We found similar response patterns in both survey designs with only few items being answered differently, likely attributable to chance. Our study supports the equivalence of the compared survey designs and suggests that, in the studied setting, using online-only design does not cause strong distortion of the results.

The long-term differential achievement effects of school socioeconomic composition in primary education: A propensity score matching approach.

PubMed

Belfi, Barbara; Haelermans, Carla; De Fraine, Bieke

2016-12-01

The effects of school socio-economic composition on student achievement growth trajectories have been a hot topic of discussion among politicians around the world for many years. However, the bulk of research investigating school socio-economic composition effects has been limited in important ways. In an attempt to overcome the flaws in earlier research on school socio-economic composition effects, this study used data from a large sample, followed students throughout primary education, addressed selection bias problems, identified the grade(s) in which school socio-economic composition mattered the most, and studied the differential effects of school socio-economic composition by individual socio-economic status (SES). In a longitudinal design with seven occasions of data collection, the authors drew on a sample of N = 3,619 students (age at T1 about 5 years, age at T7 about 12 years) from 151 primary schools in Flanders (the northern part of Belgium). Students in low-, medium-, high-, and mixed-SES schools were matched using propensity scores. To compare students' achievement growth trajectories in the different school compositions, multilevel regression modelling with repeated measurements was applied. The results showed that students had more positive achievement growth in high-SES as compared to low-SES and mixed-SES schools. In two of the three comparisons, students in mixed-SES schools showed the lowest math development. The negative effects of mixed-SES schools on math achievement growth were the strongest for high-SES students. Our findings contribute to the ongoing discussion on the effects of school socio-economic composition on student achievement growth. © 2016 The British Psychological Society.

Experimental study and simulation of phosphorus purification effects of bioretention systems on urban surface runoff

PubMed Central

Liang, Zheng; Li, Yajiao; Li, Peng; Jiang, Chunbo

2018-01-01

Excessive phosphorus (P) contributes to eutrophication by degrading water quality and limiting human use of water resources. Identifying economic and convenient methods to control soluble reactive phosphorus (SRP) pollution in urban runoff is the key point of rainwater management strategies. Through three series of different tests involving influencing factors, continuous operation and intermittent operation, this study explored the purification effects of bioretention tanks under different experimental conditions, it included nine intermittent tests, single field continuous test with three groups of different fillers (Fly ash mixed with sand, Blast furnace slag, and Soil), and eight intermittent tests with single filler (Blast furnace slag mixed with sand). Among the three filler combinations studied, the filler with fly ash mixed with sand achieved the best pollution reduction efficiency. The setting of the submerged zone exerted minimal influence on the P removal of the three filler combinations. An extension of the dry period slightly promoted the P purification effect. The combination of fly ash mixed with sand demonstrated a positive purification effect on SRP during short- or long-term simulated rainfall duration. Blast furnace slag also presented a positive purification effect in the short term, although its continuous purification effect on SRP was poor in the long term. The purification abilities of soil in the short and long terms were weak. Under intermittent operations across different seasons, SRP removal was unstable, and effluent concentration processes were different. The purification effect of the bioretention system on SRP was predicted through partial least squares regression (PLS) modeling analysis. The event mean concentration removal of SRP was positively related to the adsorption capacity of filler and rainfall interval time and negatively related to submerged zones, influent concentration and volume. PMID:29742120

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Nurse staffing patterns and hospital efficiency in the United States.

PubMed

Bloom, J R; Alexander, J A; Nuchols, B A

1997-01-01

The objective of this exploratory study was to assess the effects of four nurse staffing patterns on the efficiency of patient care delivery in the hospital: registered nurses (RNs) from temporary agencies; part-time career RNs; RN rich skill mix; and organizationally experienced RNs. Using Transaction Cost Analysis, four regression models were specified to consider the effect of these staffing plans on personnel and benefit costs and on non-personnel operating costs. A number of additional variables were also included in the models to control for the effect of other organization and environmental determinants of hospital costs. Use of career part-time RNs and experienced staff reduced both personnel and benefit costs, as well as total non-personnel operating costs, while the use of temporary agencies for RNs increased non-personnel operating costs. An RN rich skill mix was not related to either measure of hospital costs. These findings provide partial support of the theory. Implications of our findings for future research on hospital management are discussed.

The PX-EM algorithm for fast stable fitting of Henderson's mixed model

PubMed Central

Foulley, Jean-Louis; Van Dyk, David A

2000-01-01

This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression. PMID:14736399

GWAS with longitudinal phenotypes: performance of approximate procedures

PubMed Central

Sikorska, Karolina; Montazeri, Nahid Mostafavi; Uitterlinden, André; Rivadeneira, Fernando; Eilers, Paul HC; Lesaffre, Emmanuel

2015-01-01

Analysis of genome-wide association studies with longitudinal data using standard procedures, such as linear mixed model (LMM) fitting, leads to discouragingly long computation times. There is a need to speed up the computations significantly. In our previous work (Sikorska et al: Fast linear mixed model computations for genome-wide association studies with longitudinal data. Stat Med 2012; 32.1: 165–180), we proposed the conditional two-step (CTS) approach as a fast method providing an approximation to the P-value for the longitudinal single-nucleotide polymorphism (SNP) effect. In the first step a reduced conditional LMM is fit, omitting all the SNP terms. In the second step, the estimated random slopes are regressed on SNPs. The CTS has been applied to the bone mineral density data from the Rotterdam Study and proved to work very well even in unbalanced situations. In another article (Sikorska et al: GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14: 166), we suggested semi-parallel computations, greatly speeding up fitting many linear regressions. Combining CTS with fast linear regression reduces the computation time from several weeks to a few minutes on a single computer. Here, we explore further the properties of the CTS both analytically and by simulations. We investigate the performance of our proposal in comparison with a related but different approach, the two-step procedure. It is analytically shown that for the balanced case, under mild assumptions, the P-value provided by the CTS is the same as from the LMM. For unbalanced data and in realistic situations, simulations show that the CTS method does not inflate the type I error rate and implies only a minimal loss of power. PMID:25712081

The role of gender in a smoking cessation intervention: a cluster randomized clinical trial

PubMed Central

2011-01-01

Background The prevalence of smoking in Spain is high in both men and women. The aim of our study was to evaluate the role of gender in the effectiveness of a specific smoking cessation intervention conducted in Spain. Methods This study was a secondary analysis of a cluster randomized clinical trial in which the randomization unit was the Basic Care Unit (family physician and nurse who care for the same group of patients). The intervention consisted of a six-month period of implementing the recommendations of a Clinical Practice Guideline. A total of 2,937 current smokers at 82 Primary Care Centers in 13 different regions of Spain were included (2003-2005). The success rate was measured by a six-month continued abstinence rate at the one-year follow-up. A logistic mixed-effects regression model, taking Basic Care Units as random-effect parameter, was performed in order to analyze gender as a predictor of smoking cessation. Results At the one-year follow-up, the six-month continuous abstinence quit rate was 9.4% in men and 8.5% in women (p = 0.400). The logistic mixed-effects regression model showed that women did not have a higher odds of being an ex-smoker than men after the analysis was adjusted for confounders (OR adjusted = 0.9, 95% CI = 0.7-1.2). Conclusions Gender does not appear to be a predictor of smoking cessation at the one-year follow-up in individuals presenting at Primary Care Centers. ClinicalTrials.gov Identifier NCT00125905. PMID:21605389

Restricted spatial regression in practice: Geostatistical models, confounding, and robustness under model misspecification

USGS Publications Warehouse

Hanks, Ephraim M.; Schliep, Erin M.; Hooten, Mevin B.; Hoeting, Jennifer A.

2015-01-01

In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Use of non-linear mixed-effects modelling and regression analysis to predict the number of somatic coliphages by plaque enumeration after 3 hours of incubation.

PubMed

Mendez, Javier; Monleon-Getino, Antonio; Jofre, Juan; Lucena, Francisco

2017-10-01

The present study aimed to establish the kinetics of the appearance of coliphage plaques using the double agar layer titration technique to evaluate the feasibility of using traditional coliphage plaque forming unit (PFU) enumeration as a rapid quantification method. Repeated measurements of the appearance of plaques of coliphages titrated according to ISO 10705-2 at different times were analysed using non-linear mixed-effects regression to determine the most suitable model of their appearance kinetics. Although this model is adequate, to simplify its applicability two linear models were developed to predict the numbers of coliphages reliably, using the PFU counts as determined by the ISO after only 3 hours of incubation. One linear model, when the number of plaques detected was between 4 and 26 PFU after 3 hours, had a linear fit of: (1.48 × Counts 3 h + 1.97); and the other, values >26 PFU, had a fit of (1.18 × Counts 3 h + 2.95). If the number of plaques detected was <4 PFU after 3 hours, we recommend incubation for (18 ± 3) hours. The study indicates that the traditional coliphage plating technique has a reasonable potential to provide results in a single working day without the need to invest in additional laboratory equipment.

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

PubMed

Son, Yeongkwon; Osornio-Vargas, Álvaro R; O'Neill, Marie S; Hystad, Perry; Texcalac-Sangrador, José L; Ohman-Strickland, Pamela; Meng, Qingyu; Schwander, Stephan

2018-05-17

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM 2.5 , PM 10 and SO 2 . Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments. Copyright © 2018. Published by Elsevier B.V.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

Regression of a vaginal leiomyoma after ovariohysterectomy in a dog: a case report.

PubMed

Sathya, Suresh; Linn, Kathleen

2014-01-01

An 11 yr old female mixed-breed Siberian husky was presented with a history of sanguineous vaginal discharge, swelling of the perineal area, decreased appetite, and lethargy. A single, large vaginal leiomyoma and multiple mammary tumors were diagnosed. Mastectomy and ovariohysterectomy were performed. The vaginal leiomyoma regressed completely after ovariohysterectomy. This is the first reported case of spontaneous regression of a vaginal leiomyoma after ovariohysterectomy in a dog.

Seasonal and Regional Variability in North Pacific Upper-Ocean Turbulence

NASA Astrophysics Data System (ADS)

Najjar, R.; Creedon, R.; Cronin, M. F.

2016-02-01

Turbulent diffusion at marine mixed layer base (MLB) plays a fundamental role in the transport of energy between the upper and abyssal ocean. Recent investigations of North Pacific mooring data at Ocean Climate Stations (OCS) Papa (50.1N,144.9W) and KEO (32.3N,144.6E) suggest seasonal and regional variability in thermal diffusivity (κT). In this investigation, it is hypothesized that these observed differences in κT are directly associated with synoptic variability in net surface heat flux (Q0), surface wind stress (τ), mixed layer depth (h), and density stratification at MLB (∂zσ|-h). To test this hypothesis, daily-averaged time series of κT are regressed against those of Q0, τ, h, and ∂zσ|-h at both Papa and KEO over a six year time period (2007-2013). Seasonality of each time series is removed before regression to capture synoptic variability of each variable. Preliminary results of the regression analysis suggest statistically significant correlations between κT and all forcing parameters at both mooring sites. These correlations have well-determined orders of magnitude and signs consistent with the hypothesis. As a result, differences in κT between Papa and KEO may be recast in terms of differences in their correlation coefficients. In order to continue investigation of these parameters and their effects on mean seasonal differences between the two regions, these results will be compared with turbulence predicted by the K-Profile Parameterization ocean turbulence model.

Toward a Better Understanding of Student Perceptions of Writing Feedback: A Mixed Methods Study

ERIC Educational Resources Information Center

Zumbrunn, Sharon; Marrs, Sarah; Mewborn, Caitlin

2016-01-01

This explanatory sequential mixed methods study investigated the writing feedback perceptions of middle and high school students (N = 598). The predictive and mediational roles of writing self-efficacy and perceptions of writing feedback on student writing self-regulation aptitude were examined using mediation regression analysis. To augment the…

Bias and uncertainty of δ13CO2 isotopic mixing models

Treesearch

Zachary E. Kayler; Lisa Ganio; Mark Hauck; Thomas G. Pypker; Elizabeth W. Sulzman; Alan C. Mix; Barbara J. Bond

2009-01-01

The goal of this study was to evaluate how factorial combinations of two mixing models and two regression approaches (Keeling-OLS, Miller—Tans-OLS, Keeling-GMR, Miller—Tans-GMR) compare in small [CO2] range versus large[CO2] range regimes, with different combinations of...

Campaign Strategies and Voter Approval of School Referenda: A Mixed Methods Analysis

ERIC Educational Resources Information Center

Johnson, Paul A.; Ingle, William Kyle

2009-01-01

Drawing from state administrative data and surveys of superintendents in Ohio, this mixed methods study examined factors associated with voters' approval of local school levies. Utilizing binomial logistic regression, this study found that new levies and poverty rates were significantly associated with a decrease in the likelihood of passage.…

Quantifying the safety effects of horizontal curves on two-way, two-lane rural roads.

PubMed

Gooch, Jeffrey P; Gayah, Vikash V; Donnell, Eric T

2016-07-01

The objective of this study is to quantify the safety performance of horizontal curves on two-way, two-lane rural roads relative to tangent segments. Past research is limited by small samples sizes, outdated statistical evaluation methods, and unreported standard errors. This study overcomes these drawbacks by using the propensity scores-potential outcomes framework. The impact of adjacent curves on horizontal curve safety is also explored using a cross-sectional regression model of only horizontal curves. The models estimated in the present study used eight years of crash data (2005-2012) obtained from over 10,000 miles of state-owned two-lane rural roads in Pennsylvania. These data included information on roadway geometry (e.g., horizontal curvature, lane width, and shoulder width), traffic volume, roadside hazard rating, and the presence of various low-cost safety countermeasures (e.g., centerline and shoulder rumble strips, curve and intersection warning pavement markings, and aggressive driving pavement dots). Crash prediction is performed by means of mixed effects negative binomial regression using the explanatory variables noted previously, as well as attributes of adjacent horizontal curves. The results indicate that both the presence of a horizontal curve and its degree of curvature must be considered when predicting the frequency of total crashes on horizontal curves. Both are associated with an increase in crash frequency, which is consistent with previous findings in the literature. Mixed effects negative binomial regression models for total crash frequency on horizontal curves indicate that the distance to adjacent curves is not statistically significant. However, the degree of curvature of adjacent curves in close proximity (within 0.75 miles) was found to be statistically significant and negatively correlated with crash frequency on the subject curve. This is logical, as drivers exiting a sharp curve are likely to be driving slower and with more awareness as they approach the next horizontal curve. Copyright © 2016 Elsevier Ltd. All rights reserved.

Keys to Reducing Summer Regression: The Reader, Routine, and Relationship

ERIC Educational Resources Information Center

Blanton, Morgan V.

2015-01-01

This study utilized mixed-methods, quasi-experimental design to investigate the impact of parent development and home-based summer reading on summer reading regression (as measured by oral reading fluency) at three Title I elementary schools in North Carolina. Title I parents and students participated in a parent development and communicated…

Do Mixed-Flora Preoperative Urine Cultures Matter?

PubMed

Polin, Michael R; Kawasaki, Amie; Amundsen, Cindy L; Weidner, Alison C; Siddiqui, Nazema Y

2017-06-01

To determine whether mixed-flora preoperative urine cultures, as compared with no-growth preoperative urine cultures, are associated with a higher prevalence of postoperative urinary tract infections (UTIs). This was a retrospective cohort study. Women who underwent urogynecologic surgery were included if their preoperative clean-catch urine culture result was mixed flora or no growth. Women were excluded if they received postoperative antibiotics for reasons other than treatment of a UTI. Women were divided into two cohorts based on preoperative urine culture results-mixed flora or no growth; the prevalence of postoperative UTI was compared between cohorts. Baseline characteristics were compared using χ 2 or Student t tests. A logistic regression analysis then was performed. We included 282 women who were predominantly postmenopausal, white, and overweight. There were many concomitant procedures; 46% underwent a midurethral sling procedure and 68% underwent pelvic organ prolapse surgery. Preoperative urine cultures resulted as mixed flora in 192 (68%) and no growth in 90 (32%) patients. Overall, 14% were treated for a UTI postoperatively. There was no difference in the proportion of patients treated for a postoperative UTI between the two cohorts (25 mixed flora vs 13 no growth, P = 0.77). These results remained when controlling for potentially confounding variables in a logistic regression model (adjusted odds ratio 0.92, 95% confidence interval 0.43-1.96). In women with mixed-flora compared with no-growth preoperative urine cultures, there were no differences in the prevalence of postoperative UTI. The clinical practice of interpreting mixed-flora cultures as negative is appropriate.

Taking Effective Treatments to Scale: Organizational Effects on Outcomes of Multisystemic Therapy for Youth with Co-occurring Substance Use

PubMed Central

Schoenwald, Sonja K.; Chapman, Jason E.; Henry, David B.; Sheidow, Ashli J.

2012-01-01

A prospective multi-site study examined organizational climate and structure effects on the behavior and functioning of delinquent youth with and without co-occurring substance treated with an evidence-based treatment for serious antisocial behavior (i.e., Multisystemic Therapy). Participants were 1979 youth treated by 429 therapists across 45 provider organizations in North America. Results of Mixed Effects Regression Models showed some aspects of climate and structure had no effects, some had similar effects, and some had slightly differential and sometimes counter-intuitive effects on the outcomes of these youth. Implications are considered for research to increase the array and availability of effective treatments for youth with co-occurring substance use across service sectors. PMID:22844190

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite.

PubMed

Castelo, Paula Midori; Gavião, Maria Beatriz Duarte; Pereira, Luciano José; Bonjardim, Leonardo Rigoldi

2010-01-01

The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). It was observed that MC group showed lower bite force than MN, and AFH/BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson's correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breast-feeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency.

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F

2017-04-01

Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.

Brief Intervention Decreases Drinking Frequency in HIV-Infected, Heavy Drinking Women: Results of a Randomized Controlled Trial

PubMed Central

Chander, Geetanjali; Hutton, Heidi E.; Lau, Bryan; Xu, Xiaoqiang; McCaul, Mary E.

2015-01-01

Objective Hazardous alcohol use by HIV-infected women is associated with poor HIV outcomes and HIV transmission risk behaviors. We examined the effectiveness of brief alcohol intervention (BI) among hazardous drinking women receiving care in an urban, HIV clinic. Methods Women were randomized to a 2-session BI or usual care. Outcomes assessed at baseline, 3, 6 and 12 months included 90-day frequency of any alcohol use and heavy/binge drinking (≥4 drinks per occasion), and average drinks per drinking episode. Secondary outcomes included HIV medication and appointment adherence, HIV1-RNA suppression, and days of unprotected vaginal sex. We examined intervention effectiveness using generalized mixed effect models and quantile regression. Results Of 148 eligible women, 74 were randomized to each arm. In mixed effects models, 90-day drinking frequency decreased among intervention group compared to control, with women in the intervention condition less likely to have a drinking day (OR: 0.42 (95% CI: 0.23–0.75). Heavy/binge drinking days and drinks per drinking day did not differ significantly between groups. Quantile regression demonstrated a decrease in drinking frequency in the middle to upper ranges of the distribution of drinking days and heavy/binge drinking days that differed significantly between intervention and control conditions. At follow-up, the intervention group had significantly fewer episodes of unprotected vaginal sex. No intervention effects were observed for other outcomes. Conclusions Brief alcohol intervention reduces frequency of alcohol use and unprotected vaginal sex among HIV-infected women. More intensive services may be needed to lower drinks per drinking day and enhance care for more severely affected drinkers. PMID:25967270

Determining vehicle operating speed and lateral position along horizontal curves using linear mixed-effects models.

PubMed

Fitzsimmons, Eric J; Kvam, Vanessa; Souleyrette, Reginald R; Nambisan, Shashi S; Bonett, Douglas G

2013-01-01

Despite recent improvements in highway safety in the United States, serious crashes on curves remain a significant problem. To assist in better understanding causal factors leading to this problem, this article presents and demonstrates a methodology for collection and analysis of vehicle trajectory and speed data for rural and urban curves using Z-configured road tubes. For a large number of vehicle observations at 2 horizontal curves located in Dexter and Ames, Iowa, the article develops vehicle speed and lateral position prediction models for multiple points along these curves. Linear mixed-effects models were used to predict vehicle lateral position and speed along the curves as explained by operational, vehicle, and environmental variables. Behavior was visually represented for an identified subset of "risky" drivers. Linear mixed-effect regression models provided the means to predict vehicle speed and lateral position while taking into account repeated observations of the same vehicle along horizontal curves. Speed and lateral position at point of entry were observed to influence trajectory and speed profiles. Rural horizontal curve site models are presented that indicate that the following variables were significant and influenced both vehicle speed and lateral position: time of day, direction of travel (inside or outside lane), and type of vehicle.

An optimal proportion of mixing broad-leaved forest for enhancing the effective productivity of moso bamboo.

PubMed

Cheng, Xiao-Fei; Shi, Pei-Jian; Hui, Cang; Wang, Fu-Sheng; Liu, Guo-Hua; Li, Bai-Lian

2015-04-01

Moso bamboos (Phyllostachys edulis) are important forestry plants in southern China, with substantial roles to play in regional economic and ecological systems. Mixing broad-leaved forests and moso bamboos is a common management practice in China, and it is fundamental to elucidate the interactions between broad-leaved trees and moso bamboos for ensuring the sustainable provision of ecosystem services. We examine how the proportion of broad-leaved forest in a mixed managed zone, topology, and soil profile affects the effective productivity of moso bamboos (i.e., those with significant economic value), using linear regression and generalized additive models. Bamboo's diameter at breast height follows a Weibull distribution. The importance of these variables to bamboo productivity is, respectively, slope (25.9%), the proportion of broad-leaved forest (24.8%), elevation (23.3%), gravel content by volume (16.6%), slope location (8.3%), and soil layer thickness (1.2%). Highest productivity is found on the 25° slope, with a 600-m elevation, and 30% broad-leaved forest. As such, broad-leaved forest in the upper slope can have a strong influence on the effective productivity of moso bamboo, ranking only after slope and before elevation. These factors can be considered in future management practice.

Response Surface Methodology for the Optimization of Preparation of Biocomposites Based on Poly(lactic acid) and Durian Peel Cellulose

PubMed Central

Penjumras, Patpen; Abdul Rahman, Russly; Talib, Rosnita A.; Abdan, Khalina

2015-01-01

Response surface methodology was used to optimize preparation of biocomposites based on poly(lactic acid) and durian peel cellulose. The effects of cellulose loading, mixing temperature, and mixing time on tensile strength and impact strength were investigated. A central composite design was employed to determine the optimum preparation condition of the biocomposites to obtain the highest tensile strength and impact strength. A second-order polynomial model was developed for predicting the tensile strength and impact strength based on the composite design. It was found that composites were best fit by a quadratic regression model with high coefficient of determination (R 2) value. The selected optimum condition was 35 wt.% cellulose loading at 165°C and 15 min of mixing, leading to a desirability of 94.6%. Under the optimum condition, the tensile strength and impact strength of the biocomposites were 46.207 MPa and 2.931 kJ/m2, respectively. PMID:26167523

Mixed models, linear dependency, and identification in age-period-cohort models.

PubMed

O'Brien, Robert M

2017-07-20

This paper examines the identification problem in age-period-cohort models that use either linear or categorically coded ages, periods, and cohorts or combinations of these parameterizations. These models are not identified using the traditional fixed effect regression model approach because of a linear dependency between the ages, periods, and cohorts. However, these models can be identified if the researcher introduces a single just identifying constraint on the model coefficients. The problem with such constraints is that the results can differ substantially depending on the constraint chosen. Somewhat surprisingly, age-period-cohort models that specify one or more of ages and/or periods and/or cohorts as random effects are identified. This is the case without introducing an additional constraint. I label this identification as statistical model identification and show how statistical model identification comes about in mixed models and why which effects are treated as fixed and which are treated as random can substantially change the estimates of the age, period, and cohort effects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Impact of case-mix on comparisons of patient-reported experience in NHS acute hospital trusts in England.

PubMed

Raleigh, Veena; Sizmur, Steve; Tian, Yang; Thompson, James

2015-04-01

To examine the impact of patient-mix on National Health Service (NHS) acute hospital trust scores in two national NHS patient surveys. Secondary analysis of 2012 patient survey data for 57,915 adult inpatients at 142 NHS acute hospital trusts and 45,263 adult emergency department attendees at 146 NHS acute hospital trusts in England. Changes in trust scores for selected questions, ranks, inter-trust variance and score-based performance bands were examined using three methods: no adjustment for case-mix; the current standardization method with weighting for age, sex and, for inpatients only, admission method; and a regression model adjusting in addition for ethnicity, presence of a long-term condition, proxy response (inpatients only) and previous emergency attendances (emergency department survey only). For both surveys, all the variables examined were associated with patients' responses and affected inter-trust variance in scores, although the direction and strength of impact differed between variables. Inter-trust variance was generally greatest for the unadjusted scores and lowest for scores derived from the full regression model. Although trust scores derived from the three methods were highly correlated (Kendall's tau coefficients 0.70-0.94), up to 14% of trusts had discordant ranks of when the standardization and regression methods were compared. Depending on the survey and question, up to 14 trusts changed performance bands when the regression model with its fuller case-mix adjustment was used rather than the current standardization method. More comprehensive case-mix adjustment of patient survey data than the current limited adjustment reduces performance variation between NHS acute hospital trusts and alters the comparative performance bands of some trusts. Given the use of these data for high-impact purposes such as performance assessment, regulation, commissioning, quality improvement and patient choice, a review of the long-standing method for analysing patient survey data would be timely, and could improve rigour and comparability across the NHS. Performance comparisons need to be perceived as fair and scientifically robust to maintain confidence in publicly reported data, and to support their use by both the public and the NHS. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

The Relative Effectiveness of Women-Only and Mixed-Gender Treatment for Substance-Abusing Women

PubMed Central

Prendergast, Michael L.; Messina, Nena P.; Hall, Elizabeth A.; Warda, Umme S.

2011-01-01

Following research indicating that the treatment needs of women are different from those of men, researchers and clinicians have argued that drug treatment programs for women should be designed to take their needs into account. Such programs tend to admit only women and incorporate philosophies and activities that are based on a social, peer-based model that is responsive to their needs. To assess the relative effectiveness of women-only (WO) outpatient programs compared to mixed-gender (MG) outpatient programs, 291 study volunteers were recruited (152 WO, 139 MG), and a 1-year follow-up was completed with 259 women (135 WO, 124 MG). Using bivariate, logistic regression, and generalized estimating equation analysis, the following four outcomes were examined: drug and alcohol use, criminal activity, arrests, and employment. In both groups, women showed improvement in the four outcome measures. Comparison of the groups on outcomes yielded mixed results; women who participated in WO treatment reported significantly less substance use and criminal activity than women in MG treatment, but there were no differences in arrest or employment status at follow up compared with those in MG treatment. PMID:21315540

The association of health-related fitness with indicators of academic performance in Texas schools.

PubMed

Welk, Gregory J; Jackson, Allen W; Morrow, James R; Haskell, William H; Meredith, Marilu D; Cooper, Kenneth H

2010-09-01

This study examined the associations between indicators of health-related physical fitness (cardiovascular fitness and body mass index) and academic performance (Texas Assessment of Knowledge and Skills). Partial correlations were generally stronger for cardiovascular fitness than body mass index and consistently stronger in the middle school grades. Mixed-model regression analyses revealed modest associations between fitness and academic achievement after controlling for potentially confounding variables. The effects of fitness on academic achievement were positive but small. A separate logistic regression analysis indicated that higher fitness rates increased the odds of schools achieving exemplary/recognized school status within the state. School fitness attainment is an indicator of higher performing schools. Direction of causality cannot be inferred due to the cross-sectional nature of the data.

Wood volume increment in thinned, 50- to 55-year-old, mixed-species Allegheny hardwoods

Treesearch

Christopher A. Nowak

1996-01-01

A thinning study in 50- to 55-year-old, even-aged, mixed species Allegheny hardwoods produced highly variable merchantable stemwood volume increment responses. Regression equations relating parameters of stand growth (ingrowth, mortality, survivor growth, net growth, and gross growth) to relative stand density had R2 values ranging from 0.07 to 0...

A Mixed-Methods Study Investigating the Relationship between Media Multitasking Orientation and Grade Point Average

ERIC Educational Resources Information Center

Lee, Jennifer

2012-01-01

The intent of this study was to examine the relationship between media multitasking orientation and grade point average. The study utilized a mixed-methods approach to investigate the research questions. In the quantitative section of the study, the primary method of statistical analyses was multiple regression. The independent variables for the…

A Mixed-Methods Inquiry into the Intimate Practices of Partnered Mature Students and Influences on Relationship, Sexual, and School Satisfaction

ERIC Educational Resources Information Center

van Rhijn, Tricia M.; Murray, Sarah H.; Mizzi, Robert C.

2015-01-01

Through the use of mixed qualitative and quantitative methods, the current study explored the impact of postsecondary study on the intimate relationships and school experiences of partnered mature students. Quantitative regression analyses indicated that parental status, family support, partner support, and sexual desire significantly predicted…

Maximum size-density relationships for mixed-hardwood forest stands in New England

Treesearch

Dale S. Solomon; Lianjun Zhang

2000-01-01

Maximum size-density relationships were investigated for two mixed-hardwood ecological types (sugar maple-ash and beech-red maple) in New England. Plots meeting type criteria and undergoing self-thinning were selected for each habitat. Using reduced major axis regression, no differences were found between the two ecological types. Pure species plots (the species basal...

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

Phylogenetically diverse macrophyte community promotes species diversity of mobile epi-benthic invertebrates

NASA Astrophysics Data System (ADS)

Nakamoto, Kenta; Hayakawa, Jun; Kawamura, Tomohiko; Kodama, Masafumi; Yamada, Hideaki; Kitagawa, Takashi; Watanabe, Yoshiro

2018-07-01

Various aspects of plant diversity such as species diversity and phylogenetic diversity enhance the species diversity of associated animals in terrestrial systems. In marine systems, however, the effects of macrophyte diversity on the species diversity of associated animals have received little attention. Here, we sampled in a subtropical seagrass-seaweed mixed bed to elucidate the effect of the macrophyte phylogenetic diversity based on the taxonomic relatedness as well as the macrophyte species diversity on species diversity of mobile epi-benthic invertebrates. Using regression analyses for each macrophyte parameter as well as multiple regression analyses, we found that the macrophyte phylogenetic diversity (taxonomic diversity index: Delta) positively influenced the invertebrate species richness and diversity index (H‧). Although the macrophyte species richness and H‧ also positively influenced the invertebrate species richness, the best fit model for invertebrate species richness did not include them, suggesting that the macrophyte species diversity indirectly influenced invertebrate species diversity. Possible explanations of the effects of macrophyte Delta on the invertebrate species diversity were the niche complementarity effect and the selection effect. This is the first study which demonstrates that macrophyte phylogenetic diversity has a strong effect on the species diversity of mobile epi-benthic invertebrates.

Effect of mixed mutans streptococci colonization on caries development.

PubMed

Seki, M; Yamashita, Y; Shibata, Y; Torigoe, H; Tsuda, H; Maeno, M

2006-02-01

To evaluate the clinical importance of mixed mutans streptococci colonization in predicting caries in preschool children. Caries prevalence was examined twice, with a 6-month interval, in 410 preschool children aged 3-4 years at baseline. A commercial strip method was used to evaluate the mutans streptococci score in plaque collected from eight selected interdental spaces and in saliva. Mutans streptococci typing polymerase chain reaction (PCR) assays (Streptococcus sobrinus and Streptococcus mutans, including serotypes c, e, and f) were performed using colonies on the strips as template. Twenty variables were examined in a univariate analysis to predict caries development: questionnaire variables, results of clinical examination, mutans streptococci scores, and PCR detection of S. sobrinus and S. mutans (including serotypes c, e, and f). Sixteen variables showed statistically significant associations (P < 0.04) in the univariate analysis. However, when entered into a logistic regression, only five variables remained significant (P < 0.05): caries experience at baseline; mixed colonization of S. sobrinus and S. mutans including S. mutans serotypes; high plaque mutans streptococci score; habitual use of sweet drinks; and nonuse of fluoride toothpaste. 'Mixed mutans streptococci colonization' is a novel measure correlated with caries development in their primary dentition.

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study.

PubMed

Mazzarini, Lorenzo; Kotzalidis, Georgios D; Piacentino, Daria; Rizzato, Salvatore; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Young, Allan H; Vieta, Eduard; Girardi, Paolo; Perugi, Giulio

2018-03-15

Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples. We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD. Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec. Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD. High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD. Copyright © 2017. Published by Elsevier B.V.

Association between percutaneous hemodynamic support device and survival from cardiac arrest in the state of Michigan.

PubMed

Pressman, Andrew; Sawyer, Kelly N; Devlin, William; Swor, Robert

2018-05-01

The role of circulatory support in the post-cardiac arrest period remains controversial. Our objective was to investigate the association between treatment with a percutaneous hemodynamic support device and outcome after admission for cardiac arrest. We performed a retrospective study of adult patients with admission diagnosis of cardiac arrest or ventricular fibrillation (VF) from the Michigan Inpatient Database, treated between July 1, 2010, and June 30, 2013. Patient demographics, clinical characteristics, treatments, and disposition were electronically abstracted based on ICD-9 codes at the hospital level. Mixed-effects logistic regression models were fit to test the effect of percutaneous hemodynamic support device defined as either percutaneous left ventricular assist device (pLVAD) or intra-aortic balloon pump (IABP) on survival. These models controlled for age, sex, VF, myocardial infarction (MI), and cardiogenic shock with hospital modeled as a random effect. A total of 103 hospitals contributed 4393 patients for analysis, predominately male (58.8%) with a mean age of 64.1years (SD 15.5). On univariate analysis, younger age, male sex, VF as the initial rhythm, acute MI, percutaneous coronary intervention, percutaneous hemodynamic support device, and absence of cardiogenic shock were associated with survival to discharge (each p<0.001). Mixed-effects logistic regressions revealed use of percutaneous hemodynamic support device was significantly associated with survival among all patients (OR 1.8 (1.28-2.54)), and especially in those with acute MI (OR 1.95 (1.31-2.93)) or cardiogenic shock (OR 1.96 (1.29-2.98)). Treatment with percutaneous hemodynamic support device in the post-arrest period may provide left ventricular support and improve outcome. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of Consuming Oat Bran Mixed in Water before a Meal on Glycemic Responses in Healthy Humans-A Pilot Study.

PubMed

Steinert, Robert E; Raederstorff, Daniel; Wolever, Thomas M S

2016-08-26

Viscous dietary fibers including oat β-glucan are one of the most effective classes of functional food ingredients for reducing postprandial blood glucose. The mechanism of action is thought to be via an increase in viscosity of the stomach contents that delays gastric emptying and reduces mixing of food with digestive enzymes, which, in turn, retards glucose absorption. Previous studies suggest that taking viscous fibers separate from a meal may not be effective in reducing postprandial glycemia. We aimed to re-assess the effect of consuming a preload of a commercially available oat-bran (4.5, 13.6 or 27.3 g) containing 22% of high molecular weight oat β-glucan (O22 (OatWell(®)22)) mixed in water before a test-meal of white bread on glycemic responses in 10 healthy humans. We found a significant effect of dose on blood glucose area under the curve (AUC) (p = 0.006) with AUC after 27.3 g of O22 being significantly lower than white bread only. Linear regression analysis showed that each gram of oat β-glucan reduced glucose AUC by 4.35% ± 1.20% (r = 0.507, p = 0.0008, n = 40) and peak rise by 6.57% ± 1.49% (r = 0.582, p < 0.0001). These data suggest the use of oat bran as nutritional preload strategy in the management of postprandial glycemia.

Meta-analytical synthesis of regression coefficients under different categorization scheme of continuous covariates.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-11-30

Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.

The dynamic volume changes of polymerising polymethyl methacrylate bone cement.

PubMed

Muller, Scott D; Green, Sarah M; McCaskie, Andrew W

2002-12-01

The Swedish hip register found an increased risk of early revision of vacuum-mixed cemented total hip replacements. The influence of cement mixing technique on the dynamic volume change in polymerising PMMA is not well understood and may be relevant to this observation. Applying Archimedes' principle, we have investigated the dynamic volume changes in polymerising cement and determined the influence of mixing technique. All specimens showed an overall volume reduction: hand-mixed 3.4% and vacuum-mixed 6.0%. Regression analysis of sectional porosity and volume reduction showed a highly significant relationship. Hand-mixed porous cement showed a transient volume increase before solidification. However, vacuum-mixed cement showed a progressive volume reduction throughout polymerisation. Transient expansion of porous cement occurs at the critical time of micro-interlock formation, possibly improving fixation. Conversely, progressive volume reduction of vacuum-mixed cement throughout the formation of interlock may damage fixation. Stable fixation of vacuum-mixed cement may depend on additional techniques to offset the altered volumetric behaviour of vacuum-mixed cement.

Mixed features in patients with a major depressive episode: the BRIDGE-II-MIX study.

PubMed

Perugi, Giulio; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Reis, Joao; Vieta, Eduard; Young, Allan H

2015-03-01

To estimate the frequency of mixed states in patients diagnosed with major depressive episode (MDE) according to conceptually different definitions and to compare their clinical validity. This multicenter, multinational cross-sectional Bipolar Disorders: Improving Diagnosis, Guidance and Education (BRIDGE)-II-MIX study enrolled 2,811 adult patients experiencing an MDE. Data were collected per protocol on sociodemographic variables, current and past psychiatric symptoms, and clinical variables that are risk factors for bipolar disorder. The frequency of mixed features was determined by applying both DSM-5 criteria and a priori described Research-Based Diagnostic Criteria (RBDC). Clinical variables associated with mixed features were assessed using logistic regression. Overall, 212 patients (7.5%) fulfilled DSM-5 criteria for MDE with mixed features (DSM-5-MXS), and 818 patients (29.1%) fulfilled diagnostic criteria for a predefined RBDC depressive mixed state (RBDC-MXS). The most frequent manic/hypomanic symptoms were irritable mood (32.6%), emotional/mood lability (29.8%), distractibility (24.4%), psychomotor agitation (16.1%), impulsivity (14.5%), aggression (14.2%), racing thoughts (11.8%), and pressure to keep talking (11.4%). Euphoria (4.6%), grandiosity (3.7%), and hypersexuality (2.6%) were less represented. In multivariate logistic regression analysis, RBDC-MXS was associated with the largest number of variables including diagnosis of bipolar disorder, family history of mania, lifetime suicide attempts, duration of the current episode > 1 month, atypical features, early onset, history of antidepressant-induced mania/hypomania, and lifetime comorbidity with anxiety, alcohol and substance use disorders, attention-deficit/hyperactivity disorder, and borderline personality disorder. Depressive mixed state, defined as the presence of 3 or more manic/hypomanic features, was present in around one-third of patients experiencing an MDE. The valid symptom, illness course and family history RBDC criteria we assessed identified 4 times more MDE patients as having mixed features and yielded statistically more robust associations with several illness characteristics of bipolar disorder than did DSM-5 criteria. © Copyright 2015 Physicians Postgraduate Press, Inc.

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite

PubMed Central

CASTELO, Paula Midori; GAVIÃO, Maria Beatriz Duarte; PEREIRA, Luciano José; BONJARDIM, Leonardo Rigoldi

2010-01-01

Objective The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. Material and methods The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). Results It was observed that MC group showed lower bite force than MN, and AFH/ BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson’s correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breastfeeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). Conclusions In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency. PMID:20485925

Strategies for improving water use efficiency of livestock production in rain-fed systems.

PubMed

Kebebe, E G; Oosting, S J; Haileslassie, A; Duncan, A J; de Boer, I J M

2015-05-01

Livestock production is a major consumer of fresh water, and the influence of livestock production on global fresh water resources is increasing because of the growing demand for livestock products. Increasing water use efficiency of livestock production, therefore, can contribute to the overall water use efficiency of agriculture. Previous studies have reported significant variation in livestock water productivity (LWP) within and among farming systems. Underlying causes of this variation in LWP require further investigation. The objective of this paper was to identify the factors that explain the variation in LWP within and among farming systems in Ethiopia. We quantified LWP for various farms in mixed-crop livestock systems and explored the effect of household demographic characteristics and farm assets on LWP using ANOVA and multilevel mixed-effect linear regression. We focused on water used to cultivate feeds on privately owned agricultural lands. There was a difference in LWP among farming systems and wealth categories. Better-off households followed by medium households had the highest LWP, whereas poor households had the lowest LWP. The variation in LWP among wealth categories could be explained by the differences in the ownership of livestock and availability of family labor. Regression results showed that the age of the household head, the size of the livestock holding and availability of family labor affected LWP positively. The results suggest that water use efficiency could be improved by alleviating resource constraints such as access to farm labor and livestock assets, oxen in particular.

A low-cost, tablet-based option for prehospital neurologic assessment: The iTREAT Study.

PubMed

Chapman Smith, Sherita N; Govindarajan, Prasanthi; Padrick, Matthew M; Lippman, Jason M; McMurry, Timothy L; Resler, Brian L; Keenan, Kevin; Gunnell, Brian S; Mehndiratta, Prachi; Chee, Christina Y; Cahill, Elizabeth A; Dietiker, Cameron; Cattell-Gordon, David C; Smith, Wade S; Perina, Debra G; Solenski, Nina J; Worrall, Bradford B; Southerland, Andrew M

2016-07-05

In this 2-center study, we assessed the technical feasibility and reliability of a low cost, tablet-based mobile telestroke option for ambulance transport and hypothesized that the NIH Stroke Scale (NIHSS) could be performed with similar reliability between remote and bedside examinations. We piloted our mobile telemedicine system in 2 geographic regions, central Virginia and the San Francisco Bay Area, utilizing commercial cellular networks for videoconferencing transmission. Standardized patients portrayed scripted stroke scenarios during ambulance transport and were evaluated by independent raters comparing bedside to remote mobile telestroke assessments. We used a mixed-effects regression model to determine intraclass correlation of the NIHSS between bedside and remote examinations (95% confidence interval). We conducted 27 ambulance runs at both sites and successfully completed the NIHSS for all prehospital assessments without prohibitive technical interruption. The mean difference between bedside (face-to-face) and remote (video) NIHSS scores was 0.25 (1.00 to -0.50). Overall, correlation of the NIHSS between bedside and mobile telestroke assessments was 0.96 (0.92-0.98). In the mixed-effects regression model, there were no statistically significant differences accounting for method of evaluation or differences between sites. Utilizing a low-cost, tablet-based platform and commercial cellular networks, we can reliably perform prehospital neurologic assessments in both rural and urban settings. Further research is needed to establish the reliability and validity of prehospital mobile telestroke assessment in live patients presenting with acute neurologic symptoms. © 2016 American Academy of Neurology.

A low-cost, tablet-based option for prehospital neurologic assessment

PubMed Central

Chapman Smith, Sherita N.; Govindarajan, Prasanthi; Padrick, Matthew M.; Lippman, Jason M.; McMurry, Timothy L.; Resler, Brian L.; Keenan, Kevin; Gunnell, Brian S.; Mehndiratta, Prachi; Chee, Christina Y.; Cahill, Elizabeth A.; Dietiker, Cameron; Cattell-Gordon, David C.; Smith, Wade S.; Perina, Debra G.; Solenski, Nina J.; Worrall, Bradford B.

2016-01-01

Objectives: In this 2-center study, we assessed the technical feasibility and reliability of a low cost, tablet-based mobile telestroke option for ambulance transport and hypothesized that the NIH Stroke Scale (NIHSS) could be performed with similar reliability between remote and bedside examinations. Methods: We piloted our mobile telemedicine system in 2 geographic regions, central Virginia and the San Francisco Bay Area, utilizing commercial cellular networks for videoconferencing transmission. Standardized patients portrayed scripted stroke scenarios during ambulance transport and were evaluated by independent raters comparing bedside to remote mobile telestroke assessments. We used a mixed-effects regression model to determine intraclass correlation of the NIHSS between bedside and remote examinations (95% confidence interval). Results: We conducted 27 ambulance runs at both sites and successfully completed the NIHSS for all prehospital assessments without prohibitive technical interruption. The mean difference between bedside (face-to-face) and remote (video) NIHSS scores was 0.25 (1.00 to −0.50). Overall, correlation of the NIHSS between bedside and mobile telestroke assessments was 0.96 (0.92–0.98). In the mixed-effects regression model, there were no statistically significant differences accounting for method of evaluation or differences between sites. Conclusions: Utilizing a low-cost, tablet-based platform and commercial cellular networks, we can reliably perform prehospital neurologic assessments in both rural and urban settings. Further research is needed to establish the reliability and validity of prehospital mobile telestroke assessment in live patients presenting with acute neurologic symptoms. PMID:27281534

Parental report of the early development of children with regressive autism: the delays-plus-regression phenotype.

PubMed

Ozonoff, Sally; Williams, Brenda J; Landa, Rebecca

2005-12-01

Most children with autism demonstrate developmental abnormalities in their first year, whereas others display regression after mostly normal development. Few studies have examined the early development of the latter group. This study developed a retrospective measure, the Early Development Questionnaire (EDQ), to collect specific, parent-reported information about development in the first 18 months. Based on their EDQ scores, 60 children with autism between the ages of 3 and 9 were divided into three groups: an early onset group (n = 29), a definite regression group (n = 23), and a heterogeneous mixed group (n = 8). Significant differences in early social development were found between the early onset and regression groups. However, over 50 percent of the children who experienced a regression demonstrated some early social deficits during the first year of life, long before regression and the apparent onset of autism. This group, tentatively labeled 'delays-plus-regression', deserves further study.

Transdermal Rivastigmine Delivery for Alzheimer Disease: Amenability of Exposure Predictions of Rivastigmine and Metabolite, NAP226-90, by Linear Regression Model Using Limited Samples.

PubMed

Srinivas, Nuggehally R

2016-01-01

Although an optimized delivery of rivastigmine for management of Alzhiemer disease (AD) is provided by the transdermal patch, it is critical to establish a limited sampling strategy for the measurement of exposure of rivastigmine/NAP226-90. The relationship Cmax versus AUC0-24h for rivastigmine/NAP226-90 was established by regression models. The derived regression equations enabled the prediction AUC0-24h for rivastigmine and NAP226-90. Models were evaluated using statistical criteria. Mixed model was used to predict AUC0-24h for rivastigmine/NAP226-90 from time points such as 8 (C8h), 12 (C12h), and 18 (C18h) hours. Excellent correlation was established for between Cmax and AUC0-24h for rivastigmine and NAP226-90. AUC0-24h predictions of either rivastigmine or NAP226-90 were within 0.8- to 1.25-fold difference. The RMSE in the AUC0-24h predictions ranged from 17.6% to 21.9%, and the R for prediction were greater than 0.96 for both rivastigmine and NAP226-90. Use of mixed model for C8h, C12h, and C18h resulted in AUC0-24h within 1.5-fold difference for rivastigmine or NAP226-90. Cmax of rivastigmine and NAP226-90 was highly correlated with the corresponding AUC0-24h values confirming the role of a time point closer to Cmax for an effective AUC measurement of rivastigmine or the metabolite.

Conservative management or gamma knife radiosurgery for vestibular schwannoma: tumor growth, symptoms, and quality of life.

PubMed

Breivik, Cathrine Nansdal; Nilsen, Roy Miodini; Myrseth, Erling; Pedersen, Paal Henning; Varughese, Jobin K; Chaudhry, Aqeel Asghar; Lund-Johansen, Morten

2013-07-01

There are few reports about the course of vestibular schwannoma (VS) patients following gamma knife radiosurgery (GKRS) compared with the course following conservative management (CM). In this study, we present prospectively collected data of 237 patients with unilateral VS extending outside the internal acoustic canal who received either GKRS (113) or CM (124). The aim was to measure the effect of GKRS compared with the natural course on tumor growth rate and hearing loss. Secondary end points were postinclusion additional treatment, quality of life (QoL), and symptom development. The patients underwent magnetic resonance imaging scans, clinical examination, and QoL assessment by SF-36 questionnaire. Statistics were performed by using Spearman correlation coefficient, Kaplan-Meier plot, Poisson regression model, mixed linear regression models, and mixed logistic regression models. Mean follow-up time was 55.0 months (26.1 standard deviation, range 10-132). Thirteen patients were lost to follow-up. Serviceable hearing was lost in 54 of 71 (76%) (CM) and 34 of 53 (64%) (GKRS) patients during the study period (not significant, log-rank test). There was a significant reduction in tumor volume over time in the GKRS group. The need for treatment following initial GKRS or CM differed at highly significant levels (log-rank test, P < .001). Symptom and QoL development did not differ significantly between the groups. In VS patients, GKRS reduces the tumor growth rate and thereby the incidence rate of new treatment about tenfold. Hearing is lost at similar rates in both groups. Symptoms and QoL seem not to be significantly affected by GKRS.

Effect of immigration background and country-of-origin contextual factors on adolescent substance use in Spain.

PubMed

Sarasa-Renedo, Ana; Sordo, Luis; Pulido, José; Guitart, Anna; González-González, Rocío; Hoyos, Juan; Bravo, María J; Barrio, Gregorio

2015-08-01

The effects of adolescent- and parental-birthplace and country-of-origin contextual factors on substance use among adolescents with recent immigrant background (ARIBs) are poorly understood. We aimed to assess these effects and identify the main mediating factors in Spain. Participants were 12,432 ARIBs (≥1 foreign-born parent) and 75,511 autochthonous adolescents from pooled 2006-2010 school surveys. Outcomes were prevalence of use of alcohol, tobacco, cannabis, stimulants and sedative-hypnotics. ARIBs were classified by adolescent birthplace (Spain/abroad), whether they had mixed-parents (one Spanish-born and one foreign-born), and country-of-origin characteristics. Adjusted prevalence ratios (aPRs) and percent change expressing disparities in risk were estimated using Poisson regression with robust variance. Compared to autochthonous adolescents, foreign-born ARIBs without mixed-parents showed significant aPRs <1 for all substances, which generally approached 1 in Spanish-born ARIBs with mixed-parents. The main factors mediating ARIBs' lower risk were less frequent socialization in leisure environments and less association with peers who use such substances. ARIBs' lower risk depended more on country-of-origin characteristics and not having mixed-parents than being foreign-born. Tobacco, cannabis and stimulant use in ARIBs increased with increasing population use of these substances in the country-of-origin. ARIBs from the non-Muslim-regions had a lower risk of using alcohol and higher risk of using sedative-hypnotics than those from the Muslim-region. Among ARIBs in Spain, parental transmission of norms and values could influence substance use as much as or more than exposure to the Spanish context. Future research should better assess effects of adolescent- and parental-birthplace and country-of-origin contextual factors on substance use. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Discovering human germ cell mutagens with whole genome sequencing: Insights from power calculations reveal the importance of controlling for between-family variability.

PubMed

Webster, R J; Williams, A; Marchetti, F; Yauk, C L

2018-07-01

Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Modeling Stationary Lithium-Ion Batteries for Optimization and Predictive Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Kyri A; Shi, Ying; Christensen, Dane T

Accurately modeling stationary battery storage behavior is crucial to understand and predict its limitations in demand-side management scenarios. In this paper, a lithium-ion battery model was derived to estimate lifetime and state-of-charge for building-integrated use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. In order to achieve these goals, a mixed modeling approach was taken, which incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. A comparison of the proposed battery model output to actual data from the manufacturer validates the modelingmore » approach taken in the paper. Additionally, a dynamic test case demonstrates the effects of using regression models to represent internal resistance and capacity fading.« less

Modeling Stationary Lithium-Ion Batteries for Optimization and Predictive Control: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raszmann, Emma; Baker, Kyri; Shi, Ying

Accurately modeling stationary battery storage behavior is crucial to understand and predict its limitations in demand-side management scenarios. In this paper, a lithium-ion battery model was derived to estimate lifetime and state-of-charge for building-integrated use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. In order to achieve these goals, a mixed modeling approach was taken, which incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. A comparison of the proposed battery model output to actual data from the manufacturer validates the modelingmore » approach taken in the paper. Additionally, a dynamic test case demonstrates the effects of using regression models to represent internal resistance and capacity fading.« less

Oil Extraction and Indigenous Livelihoods in the Northern Ecuadorian Amazon

PubMed Central

Bozigar, Matthew; Gray, Clark L.; Bilsborrow, Richard E.

2015-01-01

Globally, the extraction of minerals and fossil fuels is increasingly penetrating into isolated regions inhabited by indigenous peoples, potentially undermining their livelihoods and well-being. To provide new insight to this issue, we draw on a unique longitudinal dataset collected in the Ecuadorian Amazon over an 11-year period from 484 indigenous households with varying degrees of exposure to oil extraction. Fixed and random effects regression models of the consequences of oil activities for livelihood outcomes reveal mixed and multidimensional effects. These results challenge common assumptions about these processes and are only partly consistent with hypotheses drawn from the Dutch disease literature. PMID:26543302

Estimating surface pCO2 in the northern Gulf of Mexico: Which remote sensing model to use?

NASA Astrophysics Data System (ADS)

Chen, Shuangling; Hu, Chuanmin; Cai, Wei-Jun; Yang, Bo

2017-12-01

Various approaches and models have been proposed to remotely estimate surface pCO2 in the ocean, with variable performance as they were designed for different environments. Among these, a recently developed mechanistic semi-analytical approach (MeSAA) has shown its advantage for its explicit inclusion of physical and biological forcing in the model, yet its general applicability is unknown. Here, with extensive in situ measurements of surface pCO2, the MeSAA, originally developed for the summertime East China Sea, was tested in the northern Gulf of Mexico (GOM) where river plumes dominate water's biogeochemical properties during summer. Specifically, the MeSAA-predicted surface pCO2 was estimated by combining the dominating effects of thermodynamics, river-ocean mixing and biological activities on surface pCO2. Firstly, effects of thermodynamics and river-ocean mixing (pCO2@Hmixing) were estimated with a two-endmember mixing model, assuming conservative mixing. Secondly, pCO2 variations caused by biological activities (ΔpCO2@bio) was determined through an empirical relationship between sea surface temperature (SST)-normalized pCO2 and MODIS (Moderate Resolution Imaging Spectroradiometer) 8-day composite chlorophyll concentration (CHL). The MeSAA-modeled pCO2 (sum of pCO2@Hmixing and ΔpCO2@bio) was compared with the field-measured pCO2. The Root Mean Square Error (RMSE) was 22.94 μatm (5.91%), with coefficient of determination (R2) of 0.25, mean bias (MB) of - 0.23 μatm and mean ratio (MR) of 1.001, for pCO2 ranging between 316 and 452 μatm. To improve the model performance, a locally tuned MeSAA was developed through the use of a locally tuned ΔpCO2@bio term. A multi-variate empirical regression model was also developed using the same dataset. Both the locally tuned MeSAA and the regression models showed improved performance comparing to the original MeSAA, with R2 of 0.78 and 0.84, RMSE of 12.36 μatm (3.14%) and 10.66 μatm (2.68%), MB of 0.00 μatm and - 0.10 μatm, MR of 1.001 and 1.000, respectively. A sensitivity analysis was conducted to study the uncertainties in the predicted pCO2 as a result of the uncertainties in the input variables of each model. Although the MeSAA was more sensitive to variations in SST and CHL than in sea surface salinity (SSS), and the locally tuned MeSAA and the empirical regression models were more sensitive to changes in SST and SSS than in CHL, generally for these three models the bias induced by the uncertainties in the empirically derived parameters (river endmember total alkalinity (TA) and dissolved inorganic carbon (DIC), biological coefficient of the MeSAA and locally tuned MeSAA models) and environmental variables (SST, SSS, CHL) was within or close to the uncertainty of each model. While all these three models showed that surface pCO2 was positively correlated to SST, the MeSAA showed negative correlation between surface pCO2 and SSS and CHL but the locally tuned MeSAA and the empirical regression showed the opposite. These results suggest that the locally tuned MeSAA worked better in the river-dominated northern GOM than the original MeSAA, with slightly worse statistics but more meaningful physical and biogeochemical interpretations than the empirical regression model. Because data from abnormal upwelling were not used to train the models, they are not applicable for waters with strong upwelling, yet the empirical regression approach showed ability to be further tuned to adapt to such cases.

The effects of climate change on harp seals (Pagophilus groenlandicus).

PubMed

Johnston, David W; Bowers, Matthew T; Friedlaender, Ari S; Lavigne, David M

2012-01-01

Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data.

The Effects of Climate Change on Harp Seals (Pagophilus groenlandicus)

PubMed Central

Johnston, David W.; Bowers, Matthew T.; Friedlaender, Ari S.; Lavigne, David M.

2012-01-01

Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data. PMID:22238591

Antibiotic rotation strategies to reduce antimicrobial resistance in Gram-negative bacteria in European intensive care units: study protocol for a cluster-randomized crossover controlled trial.

PubMed

van Duijn, Pleun J; Bonten, Marc J M

2014-07-10

Intensive care units (ICU) are epicenters for the emergence of antibiotic-resistant Gram-negative bacteria (ARGNB) because of high rates of antibiotic usage, rapid patient turnover, immunological susceptibility of acutely ill patients, and frequent contact between healthcare workers and patients, facilitating cross-transmission.Antibiotic stewardship programs are considered important to reduce antibiotic resistance, but the effectiveness of strategies such as, for instance, antibiotic rotation, have not been determined rigorously. Interpretation of available studies on antibiotic rotation is hampered by heterogeneity in implemented strategies and suboptimal study designs. In this cluster-randomized, crossover trial the effects of two antibiotic rotation strategies, antibiotic mixing and cycling, on the prevalence of ARGNB in ICUs are determined. Antibiotic mixing aims to create maximum antibiotic heterogeneity, and cycling aims to create maximum antibiotic homogeneity during consecutive periods. This is an open cluster-randomized crossover study of mixing and cycling of antibiotics in eight ICUs in five European countries. During cycling (9 months) third- or fourth-generation cephalosporins, piperacillin-tazobactam and carbapenems will be rotated during consecutive 6-week periods as the primary empiric treatment in patients suspected of infection caused by Gram-negative bacteria. During mixing (9 months), the same antibiotics will be rotated for each consecutive antibiotic course. Both intervention periods will be preceded by a baseline period of 4 months. ICUs will be randomized to consecutively implement either the mixing and then cycling strategy, or vice versa. The primary outcome is the ICU prevalence of ARGNB, determined through monthly point-prevalence screening of oropharynx and perineum. Secondary outcomes are rates of acquisition of ARGNB, bacteremia and appropriateness of therapy, length of stay in the ICU and ICU mortality. Results will be adjusted for intracluster correlation, and patient- and ICU-level variables of case-mix and infection-prevention measures using advanced regression modeling. This trial will determine the effects of antibiotic mixing and cycling on the unit-wide prevalence of ARGNB in ICUs. ClinicalTrials.gov NCT01293071 December 2010.

The Relationship Between Oxygen Reserve Index and Arterial Partial Pressure of Oxygen During Surgery

PubMed Central

Dorotta, Ihab L.; Wells, Briana; Juma, David; Applegate, Patricia M.

2016-01-01

BACKGROUND: The use of intraoperative pulse oximetry (Spo2) enhances hypoxia detection and is associated with fewer perioperative hypoxic events. However, Spo2 may be reported as 98% when arterial partial pressure of oxygen (Pao2) is as low as 70 mm Hg. Therefore, Spo2 may not provide advance warning of falling arterial oxygenation until Pao2 approaches this level. Multiwave pulse co-oximetry can provide a calculated oxygen reserve index (ORI) that may add to information from pulse oximetry when Spo2 is >98%. This study evaluates the ORI to Pao2 relationship during surgery. METHODS: We studied patients undergoing scheduled surgery in which arterial catheterization and intraoperative arterial blood gas analysis were planned. Data from multiple pulse co-oximetry sensors on each patient were continuously collected and stored on a research computer. Regression analysis was used to compare ORI with Pao2 obtained from each arterial blood gas measurement and changes in ORI with changes in Pao2 from sequential measurements. Linear mixed-effects regression models for repeated measures were then used to account for within-subject correlation across the repeatedly measured Pao2 and ORI and for the unequal time intervals of Pao2 determination over elapsed surgical time. Regression plots were inspected for ORI values corresponding to Pao2 of 100 and 150 mm Hg. ORI and Pao2 were compared using mixed-effects models with a subject-specific random intercept. RESULTS: ORI values and Pao2 measurements were obtained from intraoperative data collected from 106 patients. Regression analysis showed that the ORI to Pao2 relationship was stronger for Pao2 to 240 mm Hg (r2 = 0.536) than for Pao2 over 240 mm Hg (r2 = 0.0016). Measured Pao2 was ≥100 mm Hg for all ORI over 0.24. Measured Pao2 was ≥150 mm Hg in 96.6% of samples when ORI was over 0.55. A random intercept variance component linear mixed-effects model for repeated measures indicated that Pao2 was significantly related to ORI (β[95% confidence interval] = 0.002 [0.0019–0.0022]; P < 0.0001). A similar analysis indicated a significant relationship between change in Pao2 and change in ORI (β [95% confidence interval] = 0.0044 [0.0040–0.0048]; P < 0.0001). CONCLUSIONS: These findings suggest that ORI >0.24 can distinguish Pao2 ≥100 mm Hg when Spo2 is over 98%. Similarly, ORI > 0.55 appears to be a threshold to distinguish Pao2 ≥150 mm Hg. The usefulness of these values should be evaluated prospectively. Decreases in ORI to near 0.24 may provide advance indication of falling Pao2 approaching 100 mm Hg when Spo2 is >98%. The clinical utility of interventions based on continuous ORI monitoring should be studied prospectively. PMID:27007078

The Relationship Between Oxygen Reserve Index and Arterial Partial Pressure of Oxygen During Surgery.

PubMed

Applegate, Richard L; Dorotta, Ihab L; Wells, Briana; Juma, David; Applegate, Patricia M

2016-09-01

The use of intraoperative pulse oximetry (SpO2) enhances hypoxia detection and is associated with fewer perioperative hypoxic events. However, SpO2 may be reported as 98% when arterial partial pressure of oxygen (PaO2) is as low as 70 mm Hg. Therefore, SpO2 may not provide advance warning of falling arterial oxygenation until PaO2 approaches this level. Multiwave pulse co-oximetry can provide a calculated oxygen reserve index (ORI) that may add to information from pulse oximetry when SpO2 is >98%. This study evaluates the ORI to PaO2 relationship during surgery. We studied patients undergoing scheduled surgery in which arterial catheterization and intraoperative arterial blood gas analysis were planned. Data from multiple pulse co-oximetry sensors on each patient were continuously collected and stored on a research computer. Regression analysis was used to compare ORI with PaO2 obtained from each arterial blood gas measurement and changes in ORI with changes in PaO2 from sequential measurements. Linear mixed-effects regression models for repeated measures were then used to account for within-subject correlation across the repeatedly measured PaO2 and ORI and for the unequal time intervals of PaO2 determination over elapsed surgical time. Regression plots were inspected for ORI values corresponding to PaO2 of 100 and 150 mm Hg. ORI and PaO2 were compared using mixed-effects models with a subject-specific random intercept. ORI values and PaO2 measurements were obtained from intraoperative data collected from 106 patients. Regression analysis showed that the ORI to PaO2 relationship was stronger for PaO2 to 240 mm Hg (r = 0.536) than for PaO2 over 240 mm Hg (r = 0.0016). Measured PaO2 was ≥100 mm Hg for all ORI over 0.24. Measured PaO2 was ≥150 mm Hg in 96.6% of samples when ORI was over 0.55. A random intercept variance component linear mixed-effects model for repeated measures indicated that PaO2 was significantly related to ORI (β[95% confidence interval] = 0.002 [0.0019-0.0022]; P < 0.0001). A similar analysis indicated a significant relationship between change in PaO2 and change in ORI (β [95% confidence interval] = 0.0044 [0.0040-0.0048]; P < 0.0001). These findings suggest that ORI >0.24 can distinguish PaO2 ≥100 mm Hg when SpO2 is over 98%. Similarly, ORI > 0.55 appears to be a threshold to distinguish PaO2 ≥150 mm Hg. The usefulness of these values should be evaluated prospectively. Decreases in ORI to near 0.24 may provide advance indication of falling PaO2 approaching 100 mm Hg when SpO2 is >98%. The clinical utility of interventions based on continuous ORI monitoring should be studied prospectively.

Systematic Review and Meta-Analysis: Dose-Response Relationship of Selective Serotonin Reuptake Inhibitors in Major Depressive Disorder.

PubMed

Jakubovski, Ewgeni; Varigonda, Anjali L; Freemantle, Nicholas; Taylor, Matthew J; Bloch, Michael H

2016-02-01

Previous studies suggested that the treatment response to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder follows a flat response curve within the therapeutic dose range. The present study was designed to clarify the relationship between dosage and treatment response in major depressive disorder. The authors searched PubMed for randomized placebo-controlled trials examining the efficacy of SSRIs for treating adults with major depressive disorder. Trials were also required to assess improvement in depression severity at multiple time points. Additional data were collected on treatment response and all-cause and side effect-related discontinuation. All medication doses were transformed into imipramine-equivalent doses. The longitudinal data were analyzed with a mixed-regression model. Endpoint and tolerability analyses were analyzed using meta-regression and stratified subgroup analysis by predefined SSRI dose categories in order to assess the effect of SSRI dosing on the efficacy and tolerability of SSRIs for major depressive disorder. Forty studies involving 10,039 participants were included. Longitudinal modeling (dose-by-time interaction=0.0007, 95% CI=0.0001-0.0013) and endpoint analysis (meta-regression: β=0.00053, 95% CI=0.00018-0.00088, z=2.98) demonstrated a small but statistically significant positive association between SSRI dose and efficacy. Higher doses of SSRIs were associated with an increased likelihood of dropouts due to side effects (meta-regression: β=0.00207, 95% CI=0.00071-0.00342, z=2.98) and decreased likelihood of all-cause dropout (meta-regression: β=-0.00093, 95% CI=-0.00165 to -0.00021, z=-2.54). Higher doses of SSRIs appear slightly more effective in major depressive disorder. This benefit appears to plateau at around 250 mg of imipramine equivalents (50 mg of fluoxetine). The slightly increased benefits of SSRIs at higher doses are somewhat offset by decreased tolerability at high doses.

Skipping breakfast, overconsumption of soft drinks and screen media: longitudinal analysis of the combined influence on weight development in primary schoolchildren.

PubMed

Traub, Meike; Lauer, Romy; Kesztyüs, Tibor; Wartha, Olivia; Steinacker, Jürgen Michael; Kesztyüs, Dorothea

2018-03-16

Regular breakfast and well-balanced soft drink, and screen media consumption are associated with a lower risk of overweight and obesity in schoolchildren. The aim of this research is the combined examination of these three parameters as influencing factors for longitudinal weight development in schoolchildren in order to adapt targeted preventive measures. In the course of the Baden-Württemberg Study, Germany, data from direct measurements (baseline (2010) and follow-up (2011)) at schools was available for 1733 primary schoolchildren aged 7.08 ± 0.6 years (50.8% boys). Anthropometric measurements of the children were taken according to ISAK-standards (International Standard for Anthropometric Assessment) by trained staff. Health and lifestyle characteristics of the children and their parents were assessed in questionnaires. A linear mixed effects regression analysis was conducted to examine influences on changes in waist-to-height-ratio (WHtR), weight, and body mass index (BMI) measures. A generalised linear mixed effects regression analysis was performed to identify the relationship between breakfast, soft drink and screen media consumption with the prevalence of overweight, obesity and abdominal obesity at follow-up. According to the regression analyses, skipping breakfast led to increased changes in WHtR, weight and BMI measures. Skipping breakfast and the overconsumption of screen media at baseline led to higher odds of abdominal obesity and overweight at follow-up. No significant association between soft drink consumption and weight development was found. Targeted prevention for healthy weight status and development in primary schoolchildren should aim towards promoting balanced breakfast habits and a reduction in screen media consumption. Future research on soft drink consumption is needed. Health promoting interventions should synergistically involve children, parents, and schools. The Baden-Württemberg Study is registered at the German Clinical Trials Register (DRKS) under the DRKS-ID: DRKS00000494 .

Determination of GMPE functional form for an active region with limited strong motion data: application to the Himalayan region

NASA Astrophysics Data System (ADS)

Bajaj, Ketan; Anbazhagan, P.

2018-01-01

Advancement in the seismic networks results in formulation of different functional forms for developing any new ground motion prediction equation (GMPE) for a region. Till date, various guidelines and tools are available for selecting a suitable GMPE for any seismic study area. However, these methods are efficient in quantifying the GMPE but not for determining a proper functional form and capturing the epistemic uncertainty associated with selection of GMPE. In this study, the compatibility of the recent available functional forms for the active region is tested for distance and magnitude scaling. Analysis is carried out by determining the residuals using the recorded and the predicted spectral acceleration values at different periods. Mixed effect regressions are performed on the calculated residuals for determining the intra- and interevent residuals. Additionally, spatial correlation is used in mixed effect regression by changing its likelihood function. Distance scaling and magnitude scaling are respectively examined by studying the trends of intraevent residuals with distance and the trend of the event term with magnitude. Further, these trends are statistically studied for a respective functional form of a ground motion. Additionally, genetic algorithm and Monte Carlo method are used respectively for calculating the hinge point and standard error for magnitude and distance scaling for a newly determined functional form. The whole procedure is applied and tested for the available strong motion data for the Himalayan region. The functional form used for testing are five Himalayan GMPEs, five GMPEs developed under NGA-West 2 project, two from Pan-European, and one from Japan region. It is observed that bilinear functional form with magnitude and distance hinged at 6.5 M w and 300 km respectively is suitable for the Himalayan region. Finally, a new regression coefficient for peak ground acceleration for a suitable functional form that governs the attenuation characteristic of the Himalayan region is derived.

Spatiotemporal Modeling of Ozone Levels in Quebec (Canada): A Comparison of Kriging, Land-Use Regression (LUR), and Combined Bayesian Maximum Entropy–LUR Approaches

PubMed Central

Adam-Poupart, Ariane; Brand, Allan; Fournier, Michel; Jerrett, Michael

2014-01-01

Background: Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide. Objectives: We sought to compare the accuracy of three spatiotemporal models to predict summer ground-level O3 in Quebec, Canada. Methods: We developed a land-use mixed-effects regression (LUR) model based on readily available data (air quality and meteorological monitoring data, road networks information, latitude), a Bayesian maximum entropy (BME) model incorporating both O3 monitoring station data and the land-use mixed model outputs (BME-LUR), and a kriging method model based only on available O3 monitoring station data (BME kriging). We performed leave-one-station-out cross-validation and visually assessed the predictive capability of each model by examining the mean temporal and spatial distributions of the average estimated errors. Results: The BME-LUR was the best predictive model (R2 = 0.653) with the lowest root mean-square error (RMSE ;7.06 ppb), followed by the LUR model (R2 = 0.466, RMSE = 8.747) and the BME kriging model (R2 = 0.414, RMSE = 9.164). Conclusions: Our findings suggest that errors of estimation in the interpolation of O3 concentrations with BME can be greatly reduced by incorporating outputs from a LUR model developed with readily available data. Citation: Adam-Poupart A, Brand A, Fournier M, Jerrett M, Smargiassi A. 2014. Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy–LUR approaches. Environ Health Perspect 122:970–976; http://dx.doi.org/10.1289/ehp.1306566 PMID:24879650

Investigation on the effect of diaphragm on the combustion characteristics of solid-fuel ramjet

NASA Astrophysics Data System (ADS)

Gong, Lunkun; Chen, Xiong; Yang, Haitao; Li, Weixuan; Zhou, Changsheng

2017-10-01

The flow field characteristics and the regression rate distribution of solid-fuel ramjet with three-hole diaphragm were investigated by numerical and experimental methods. The experimental data were obtained by burning high-density polyethylene using a connected-pipe facility to validate the numerical model and analyze the combustion efficiency of the solid-fuel ramjet. The three-dimensional code developed in the present study adopted three-order MUSCL and central difference schemes, AUSMPW + flux vector splitting method, and second-order moment turbulence-chemistry model, together with k-ω shear stress transport (SST) turbulence model. The solid fuel surface temperature was calculated with fluid-solid heat coupling method. The numerical results show that strong circumferential flow exists in the region upstream of the diaphragm. The diaphragm can enhance the regression rate of the solid fuel in the region downstream of the diaphragm significantly, which mainly results from the increase of turbulent viscosity. As the diaphragm port area decreases, the regression rate of the solid fuel downstream of the diaphragm increases. The diaphragm can result in more sufficient mixing between the incoming air and fuel pyrolysis gases, while inevitably producing some pressure loss. The experimental results indicate that the effect of the diaphragm on the combustion efficiency of hydrocarbon fuels is slightly negative. It is conjectured that the diaphragm may have some positive effects on the combustion efficiency of the solid fuel with metal particles.

Tumor regression achieved by encapsulating a moderately soluble drug into a polymeric thermogel

PubMed Central

Ci, Tianyuan; Chen, Liang; Yu, Lin; Ding, Jiandong

2014-01-01

For cancer chemotherapy, a tumor regression without any surgical resection and severe side effects is greatly preferred to merely slowing down the growth of tumors. Here, we report a formulation composed of irinotecan (IRN) and poly(D,L-lactide-co-glycolide)-b-poly(ethylene glycol)-b-poly(D,L-lactide-co-glycolide) (PLGA-PEG-PLGA). IRN is a clinically used antitumor drug with active and inactive chemical forms in equilibrium, and the major form at physiological conditions is inactive but still has side effects. The aqueous solution of the PLGA-PEG-PLGA is a sol at room temperature and physically gels at body temperature, forming a thermogel. We successfully mixed this moderately soluble drug into the amphiphilic copolymer aqueous solution for the first time. The mixture was subcutaneously injected into nude mice with xenografted SW620 human colon tumors. Excellent in vivo antitumor efficacy was observed in the group that received the IRN-loaded thermogel. The tumor was significantly regressed after being treated with the IRN/thermogel, and the side effects (blood toxicity and body weight decrease) were very mild. These results might be attributed to the ideal sustained release profile and period of release of the drug from the thermogel and to the significant enhancement of the fraction of the active form of the drug by the thermogel. PMID:24980734

Tumor regression achieved by encapsulating a moderately soluble drug into a polymeric thermogel

NASA Astrophysics Data System (ADS)

Ci, Tianyuan; Chen, Liang; Yu, Lin; Ding, Jiandong

2014-07-01

For cancer chemotherapy, a tumor regression without any surgical resection and severe side effects is greatly preferred to merely slowing down the growth of tumors. Here, we report a formulation composed of irinotecan (IRN) and poly(D,L-lactide-co-glycolide)-b-poly(ethylene glycol)-b-poly(D,L-lactide-co-glycolide) (PLGA-PEG-PLGA). IRN is a clinically used antitumor drug with active and inactive chemical forms in equilibrium, and the major form at physiological conditions is inactive but still has side effects. The aqueous solution of the PLGA-PEG-PLGA is a sol at room temperature and physically gels at body temperature, forming a thermogel. We successfully mixed this moderately soluble drug into the amphiphilic copolymer aqueous solution for the first time. The mixture was subcutaneously injected into nude mice with xenografted SW620 human colon tumors. Excellent in vivo antitumor efficacy was observed in the group that received the IRN-loaded thermogel. The tumor was significantly regressed after being treated with the IRN/thermogel, and the side effects (blood toxicity and body weight decrease) were very mild. These results might be attributed to the ideal sustained release profile and period of release of the drug from the thermogel and to the significant enhancement of the fraction of the active form of the drug by the thermogel.

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed Central

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-01-01

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. PMID:28952708

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-09-27

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

Composition and structure of Pinus koraiensis mixed forest respond to spatial climatic changes.

PubMed

Zhang, Jingli; Zhou, Yong; Zhou, Guangsheng; Xiao, Chunwang

2014-01-01

Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain. Field survey was conducted in the natural Pinus koraiensis mixed forests along a latitudinal gradient and an elevational gradient in Northeast China. In order to build the mathematical models for simulating the relationships of compositional and structural attributes of the Pinus koraiensis mixed forest with climatic and non-climatic factors, stepwise linear regression analyses were performed, incorporating 14 dependent variables and the linear and quadratic components of 9 factors. All the selected new models were computed under the +2°C and +10% precipitation and +4°C and +10% precipitation scenarios. The Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month were observed to be key climatic factors controlling the stand densities and total basal areas of Pinus koraiensis mixed forest. Increased summer temperatures and precipitations strongly enhanced the stand densities and total basal areas of broadleaf trees but had little effect on Pinus koraiensis under the +2°C and +10% precipitation scenario and +4°C and +10% precipitation scenario. These results show that the Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month are key climatic factors which shape the composition and structure of Pinus koraiensis mixed forest. Although the Pinus koraiensis would persist, the current forests dominated by Pinus koraiensis in the region would all shift and become broadleaf-dominated forests due to the dramatic increase of broadleaf trees under the future global warming and increased precipitation.

Variability in case-mix adjusted in-hospital cardiac arrest rates.

PubMed

Merchant, Raina M; Yang, Lin; Becker, Lance B; Berg, Robert A; Nadkarni, Vinay; Nichol, Graham; Carr, Brendan G; Mitra, Nandita; Bradley, Steven M; Abella, Benjamin S; Groeneveld, Peter W

2012-02-01

It is unknown how in-hospital cardiac arrest (IHCA) rates vary across hospitals and predictors of variability. Measure variability in IHCA across hospitals and determine if hospital-level factors predict differences in case-mix adjusted event rates. Get with the Guidelines Resuscitation (GWTG-R) (n=433 hospitals) was used to identify IHCA events between 2003 and 2007. The American Hospital Association survey, Medicare, and US Census were used to obtain detailed information about GWTG-R hospitals. Adult patients with IHCA. Case-mix-adjusted predicted IHCA rates were calculated for each hospital and variability across hospitals was compared. A regression model was used to predict case-mix adjusted event rates using hospital measures of volume, nurse-to-bed ratio, percent intensive care unit beds, palliative care services, urban designation, volume of black patients, income, trauma designation, academic designation, cardiac surgery capability, and a patient risk score. We evaluated 103,117 adult IHCAs at 433 US hospitals. The case-mix adjusted IHCA event rate was highly variable across hospitals, median 1/1000 bed days (interquartile range: 0.7 to 1.3 events/1000 bed days). In a multivariable regression model, case-mix adjusted IHCA event rates were highest in urban hospitals [rate ratio (RR), 1.1; 95% confidence interval (CI), 1.0-1.3; P=0.03] and hospitals with higher proportions of black patients (RR, 1.2; 95% CI, 1.0-1.3; P=0.01) and lower in larger hospitals (RR, 0.54; 95% CI, 0.45-0.66; P<0.0001). Case-mix adjusted IHCA event rates varied considerably across hospitals. Several hospital factors associated with higher IHCA event rates were consistent with factors often linked with lower hospital quality of care.

Evaluation of putative allelochemicals in rice root exudates for their role in the suppression of arrowhead root growth.

PubMed

Seal, Alexa N; Haig, Terry; Pratley, James E

2004-08-01

In previous studies, 15 putative allelopathic compounds detected in rice root exudates were quantified by GC/MS/MS. In this study, multiple regression analysis on these compounds determined that five selected phenolics, namely caffeic, p-hydroxybenzoic, vanillic, syringic, and p-coumaric acids, from rice exudates were best correlated with the observed allelopathic effect on arrowhead (Sagittaria montevidensis) root growth. Despite this positive association, determination of the phenolic acid dose-response curve established that the amount quantified in the exudates was much lower than the required threshold concentration for arrowhead inhibition. A similar dose-response curve resulted from a combination of all 15 quantified compounds. Significant differences between the amounts of trans-ferulic acid, abietic acid, and an indole also existed between allelopathic and non-allelopathic rice cultivars. The potential roles of these three compounds in rice allelopathy were examined by chemoassay. Overall, neither the addition of trans-ferulic acid nor 5-hydroxyindole-3-acetic acid to the phenolic mix significantly contributed to phytotoxicity, although at higher concentrations, trans-ferulic acid appeared to act antagonistically to the phytotoxic effects of the phenolic mix. The addition of abietic acid also decreased the inhibitory effect of the phenolic mix. These studies indicate that the compounds quantified are not directly responsible for the observed allelopathic response. It is possible that the amount of phenolic acids may be indirectly related to the chemicals finally responsible for the observed allelopathic effect.

Is Private Production of Public Services Cheaper Than Public Production? A Meta-Regression Analysis of Solid Waste and Water Services

ERIC Educational Resources Information Center

Bel, Germa; Fageda, Xavier; Warner, Mildred E.

2010-01-01

Privatization of local government services is assumed to deliver cost savings, but empirical evidence for this from around the world is mixed. We conduct a meta-regression analysis of all econometric studies examining privatization of water distribution and solid waste collection services and find no systematic support for lower costs with private…

Numerical simulation of Forchheimer flow to a partially penetrating well with a mixed-type boundary condition

NASA Astrophysics Data System (ADS)

Mathias, Simon A.; Wen, Zhang

2015-05-01

This article presents a numerical study to investigate the combined role of partial well penetration (PWP) and non-Darcy effects concerning the performance of groundwater production wells. A finite difference model is developed in MATLAB to solve the two-dimensional mixed-type boundary value problem associated with flow to a partially penetrating well within a cylindrical confined aquifer. Non-Darcy effects are incorporated using the Forchheimer equation. The model is verified by comparison to results from existing semi-analytical solutions concerning the same problem but assuming Darcy's law. A sensitivity analysis is presented to explore the problem of concern. For constant pressure production, Non-Darcy effects lead to a reduction in production rate, as compared to an equivalent problem solved using Darcy's law. For fully penetrating wells, this reduction in production rate becomes less significant with time. However, for partially penetrating wells, the reduction in production rate persists for much larger times. For constant production rate scenarios, the combined effect of PWP and non-Darcy flow takes the form of a constant additional drawdown term. An approximate solution for this loss term is obtained by performing linear regression on the modeling results.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Quantitative Analysis of Single and Mix Food Antiseptics Basing on SERS Spectra with PLSR Method

NASA Astrophysics Data System (ADS)

Hou, Mengjing; Huang, Yu; Ma, Lingwei; Zhang, Zhengjun

2016-06-01

Usage and dosage of food antiseptics are very concerned due to their decisive influence in food safety. Surface-enhanced Raman scattering (SERS) effect was employed in this research to realize trace potassium sorbate (PS) and sodium benzoate (SB) detection. HfO2 ultrathin film-coated Ag NR array was fabricated as SERS substrate. Protected by HfO2 film, the SERS substrate possesses good acid resistance, which enables it to be applicable in acidic environment where PS and SB work. Regression relationship between SERS spectra of 0.3~10 mg/L PS solution and their concentration was calibrated by partial least squares regression (PLSR) method, and the concentration prediction performance was quite satisfactory. Furthermore, mixture solution of PS and SB was also quantitatively analyzed by PLSR method. Spectrum data of characteristic peak sections corresponding to PS and SB was used to establish the regression models of these two solutes, respectively, and their concentrations were determined accurately despite their characteristic peak sections overlapping. It is possible that the unique modeling process of PLSR method prevented the overlapped Raman signal from reducing the model accuracy.

The Effectiveness of a Computer-Tailored E-Learning Program for Practice Nurses to Improve Their Adherence to Smoking Cessation Counseling Guidelines: Randomized Controlled Trial.

PubMed

de Ruijter, Dennis; Candel, Math; Smit, Eline Suzanne; de Vries, Hein; Hoving, Ciska

2018-05-22

Improving practice nurses' (PN) adherence to smoking cessation counseling guidelines will benefit the quality of smoking cessation care and will potentially lead to higher smoking abstinence rates. However, support programs to aid PNs in improving their guideline uptake and adherence do not exist yet. The aim of this study was to assess the effects of a novel computer-tailored electronic learning (e-learning) program on PNs' smoking cessation guideline adherence. A Web-based randomized controlled trial (RCT) was conducted in which an intervention group (N=147) with full access to the e-learning program for 6 months was compared with a control group (N=122) without access. Data collection was fully automated at baseline and 6-month follow-up via online questionnaires, assessing PNs' demographics, work-related factors, potential behavioral predictors based on the I-Change model, and guideline adherence. PNs also completed counseling checklists to retrieve self-reported counseling activities for each consultation with a smoker (N=1175). To assess the program's effectiveness in improving PNs' guideline adherence (ie, overall adherence and adherence to individual counseling guideline steps), mixed linear and logistic regression analyses were conducted, thus accommodating for the smokers being nested within PNs. Potential effect moderation by work-related factors and behavioral predictors was also examined. After 6 months, 121 PNs in the intervention group (82.3%, 121/147) and 103 in the control group (84.4%, 103/122) completed the follow-up questionnaire. Mixed linear regression analysis revealed that counseling experience moderated the program's effect on PNs' overall guideline adherence (beta=.589; 95% CI 0.111-1.068; P Holm-Bonferroni =.048), indicating a positive program effect on adherence for PNs with a more than average level of counseling experience. Mixed logistic regression analyses regarding adherence to individual guideline steps revealed a trend toward moderating effects of baseline levels of behavioral predictors and counseling experience. More specifically, for PNs with less favorable scores on behavioral predictors (eg, low baseline self-efficacy) and high levels of counseling experience, the program significantly increased adherence. Results from our RCT showed that among PNs with more than average counseling experience, the e-learning program resulted in significantly better smoking cessation guideline adherence. Experienced PNs might have been better able to translate the content of our e-learning program into practically applicable counseling strategies compared with less experienced colleagues. Less favorable baseline levels of behavioral predictors among PNs possibly contributed to this effect, as there was more room for improvement by consulting the tailored content of the e-learning program. To further substantiate the effectiveness of e-learning programs on guideline adherence by health care professionals (HCPs), it is important to assess how to support a wider range of HCPs. Netherlands Trial Register NTR4436; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4436 (Archived by WebCite at http://www.webcitation.org/6zJQuSRq0). ©Dennis de Ruijter, Math Candel, Eline Suzanne Smit, Hein de Vries, Ciska Hoving. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.05.2018.

BDNF Val66Met predicts cognitive decline in the Wisconsin Registry for Alzheimer's Prevention

PubMed Central

Boots, Elizabeth A.; Schultz, Stephanie A.; Clark, Lindsay R.; Racine, Annie M.; Darst, Burcu F.; Koscik, Rebecca L.; Carlsson, Cynthia M.; Gallagher, Catherine L.; Hogan, Kirk J.; Bendlin, Barbara B.; Asthana, Sanjay; Sager, Mark A.; Hermann, Bruce P.; Christian, Bradley T.; Dubal, Dena B.; Engelman, Corinne D.; Johnson, Sterling C.

2017-01-01

Objective: To examine the influence of the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism on longitudinal cognitive trajectories in a large, cognitively healthy cohort enriched for Alzheimer disease (AD) risk and to understand whether β-amyloid (Aβ) burden plays a moderating role in this relationship. Methods: One thousand twenty-three adults (baseline age 54.94 ± 6.41 years) enrolled in the Wisconsin Registry for Alzheimer's Prevention underwent BDNF genotyping and cognitive assessment at up to 5 time points (average follow-up 6.92 ± 3.22 years). A subset (n = 140) underwent 11C-Pittsburgh compound B (PiB) scanning. Covariate-adjusted mixed-effects regression models were used to elucidate the effect of BDNF on cognitive trajectories in 4 cognitive domains, including verbal learning and memory, speed and flexibility, working memory, and immediate memory. Secondary mixed-effects regression models were conducted to examine whether Aβ burden, indexed by composite PiB load, modified any observed BDNF-related cognitive trajectories. Results: Compared to BDNF Val/Val homozygotes, Met carriers showed steeper decline in verbal learning and memory (p = 0.002) and speed and flexibility (p = 0.017). In addition, Aβ burden moderated the relationship between BDNF and verbal learning and memory such that Met carriers with greater Aβ burden showed even steeper cognitive decline (p = 0.033). Conclusions: In a middle-aged cohort with AD risk, carriage of the BDNF Met allele was associated with steeper decline in episodic memory and executive function. This decline was exacerbated by greater Aβ burden. These results suggest that the BDNF Val66Met polymorphism may play an important role in cognitive decline and could be considered as a target for novel AD therapeutics. PMID:28468845

Establishing a composite endpoint for measuring the effectiveness of geriatric interventions based on older persons' and informal caregivers' preference weights: a vignette study.

PubMed

Hofman, Cynthia S; Makai, Peter; Boter, Han; Buurman, Bianca M; de Craen, Anton J M; Olde Rikkert, Marcel G M; Donders, Rogier A R T; Melis, René J F

2014-04-18

The Older Persons and Informal Caregivers Survey Minimal Dataset's (TOPICS-MDS) questionnaire which measures relevant outcomes for elderly people was successfully incorporated into over 60 research projects of the Dutch National Care for the Elderly Programme. A composite endpoint (CEP) for this instrument would be helpful to compare effectiveness of the various intervention projects. Therefore, our aim is to establish a CEP for the TOPICS-MDS questionnaire, based on the preferences of elderly persons and informal caregivers. A vignette study was conducted with 200 persons (124 elderly and 76 informal caregivers) as raters. The vignettes described eight TOPICS-MDS outcomes of older persons (morbidity, functional limitations, emotional well-being, pain experience, cognitive functioning, social functioning, self-perceived health and self-perceived quality of life) and the raters assessed the general well-being (GWB) of these vignette cases on a numeric rating scale (0-10). Mixed linear regression analyses were used to derive the preference weights of the TOPICS-MDS outcomes (dependent variable: GWB scores; fixed factors: the eight outcomes; unstandardized coefficients: preference weights). The mixed regression model that combined the eight outcomes showed that the weights varied from 0.01 for social functioning to 0.16 for self-perceived health. A model that included "informal caregiver" showed that the interactions between this variable and each of the eight outcomes were not significant (p > 0.05). A preference-weighted CEP for TOPICS-MDS questionnaire was established based on the preferences of older persons and informal caregivers. With this CEP optimal comparing the effectiveness of interventions in older persons can be realized.

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials.

PubMed

Theofilatos, Athanasios

2017-06-01

The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

BDNF Val66Met predicts cognitive decline in the Wisconsin Registry for Alzheimer's Prevention.

PubMed

Boots, Elizabeth A; Schultz, Stephanie A; Clark, Lindsay R; Racine, Annie M; Darst, Burcu F; Koscik, Rebecca L; Carlsson, Cynthia M; Gallagher, Catherine L; Hogan, Kirk J; Bendlin, Barbara B; Asthana, Sanjay; Sager, Mark A; Hermann, Bruce P; Christian, Bradley T; Dubal, Dena B; Engelman, Corinne D; Johnson, Sterling C; Okonkwo, Ozioma C

2017-05-30

To examine the influence of the brain-derived neurotrophic factor ( BDNF ) Val66Met polymorphism on longitudinal cognitive trajectories in a large, cognitively healthy cohort enriched for Alzheimer disease (AD) risk and to understand whether β-amyloid (Aβ) burden plays a moderating role in this relationship. One thousand twenty-three adults (baseline age 54.94 ± 6.41 years) enrolled in the Wisconsin Registry for Alzheimer's Prevention underwent BDNF genotyping and cognitive assessment at up to 5 time points (average follow-up 6.92 ± 3.22 years). A subset (n = 140) underwent 11 C-Pittsburgh compound B (PiB) scanning. Covariate-adjusted mixed-effects regression models were used to elucidate the effect of BDNF on cognitive trajectories in 4 cognitive domains, including verbal learning and memory, speed and flexibility, working memory, and immediate memory. Secondary mixed-effects regression models were conducted to examine whether Aβ burden, indexed by composite PiB load, modified any observed BDNF -related cognitive trajectories. Compared to BDNF Val/Val homozygotes, Met carriers showed steeper decline in verbal learning and memory ( p = 0.002) and speed and flexibility ( p = 0.017). In addition, Aβ burden moderated the relationship between BDNF and verbal learning and memory such that Met carriers with greater Aβ burden showed even steeper cognitive decline ( p = 0.033). In a middle-aged cohort with AD risk, carriage of the BDNF Met allele was associated with steeper decline in episodic memory and executive function. This decline was exacerbated by greater Aβ burden. These results suggest that the BDNF Val66Met polymorphism may play an important role in cognitive decline and could be considered as a target for novel AD therapeutics. © 2017 American Academy of Neurology.

Analyzing Health-Related Quality of Life Data to Estimate Parameters for Cost-Effectiveness Models: An Example Using Longitudinal EQ-5D Data from the SHIFT Randomized Controlled Trial.

PubMed

Griffiths, Alison; Paracha, Noman; Davies, Andrew; Branscombe, Neil; Cowie, Martin R; Sculpher, Mark

2017-03-01

The aim of this article is to discuss methods used to analyze health-related quality of life (HRQoL) data from randomized controlled trials (RCTs) for decision analytic models. The analysis presented in this paper was used to provide HRQoL data for the ivabradine health technology assessment (HTA) submission in chronic heart failure. We have used a large, longitudinal EuroQol five-dimension questionnaire (EQ-5D) dataset from the Systolic Heart Failure Treatment with the I f Inhibitor Ivabradine Trial (SHIFT) (clinicaltrials.gov: NCT02441218) to illustrate issues and methods. HRQoL weights (utility values) were estimated from a mixed regression model developed using SHIFT EQ-5D data (n = 5313 patients). The regression model was used to predict HRQoL outcomes according to treatment, patient characteristics, and key clinical outcomes for patients with a heart rate ≥75 bpm. Ivabradine was associated with an HRQoL weight gain of 0.01. HRQoL weights differed according to New York Heart Association (NYHA) class (NYHA I-IV, no hospitalization: standard care 0.82-0.46; ivabradine 0.84-0.47). A reduction in HRQoL weight was associated with hospitalizations within 30 days of an HRQoL assessment visit, with this reduction varying by NYHA class [-0.07 (NYHA I) to -0.21 (NYHA IV)]. The mixed model explained variation in EQ-5D data according to key clinical outcomes and patient characteristics, providing essential information for long-term predictions of patient HRQoL in the cost-effectiveness model. This model was also used to estimate the loss in HRQoL associated with hospitalizations. In SHIFT many hospitalizations did not occur close to EQ-5D visits; hence, any temporary changes in HRQoL associated with such events would not be captured fully in observed RCT evidence, but could be predicted in our cost-effectiveness analysis using the mixed model. Given the large reduction in hospitalizations associated with ivabradine this was an important feature of the analysis. The Servier Research Group.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

PubMed Central

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables. PMID:29713298

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

PubMed

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables.

Searching for a neurologic injury's Wechsler Adult Intelligence Scale-Third Edition profile.

PubMed

Gonçalves, Marta A; Moura, Octávio; Castro-Caldas, Alexandre; Simões, Mário R

2017-01-01

This study aimed to investigate the presence of a Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) cognitive profile in a Portuguese neurologic injured sample. The Portuguese WAIS-III was administered to 81 mixed neurologic patients and 81 healthy matched controls selected from the Portuguese standardization sample. Although the mixed neurologic injury group performed significantly lower than the healthy controls for the majority of the WAIS-III scores (i.e., composite measures, discrepancies, and subtests), the mean scores were within the normal range and, therefore, at risk of being unobserved in a clinical evaluation. ROC curves analysis showed poor to acceptable diagnostic accuracy for the WAIS-III composite measures and subtests (Working Memory Index and Digit Span revealed the highest accuracy for discriminating between participants, respectively). Multiple regression analysis showed that both literacy and the presence of brain injury were significant predictors for all of the composite measures. In addition, multiple regression analysis also showed that literacy, age of injury onset, and years of survival predicted all seven composite measures for the mixed neurologic injured group. Despite the failure to find a WAIS-III cognitive profile for mixed neurologic patients, the results showed a significant influence of brain lesion and literacy in the performance of the WAIS-III.

Rivastigmine for mild cognitive impairment in Parkinson disease: a placebo-controlled study.

PubMed

Mamikonyan, Eugenia; Xie, Sharon X; Melvin, Emilie; Weintraub, Daniel

2015-06-01

Mild cognitive impairment (MCI) in Parkinson's disease (PD) may be associated with subtle functional impairment and worse quality of life. The objective of this study was to determine the efficacy and tolerability of rivastigmine for PD-MCI. Patients with PD-MCI (n = 28) were enrolled in a 24-week, randomized, double-blind, placebo-controlled, crossover, single-site study of the rivastigmine transdermal patch. The primary outcome measure was the Alzheimer's Disease Cooperative Study-Clinical Global Impression of Change (ADCS-CGIC). Secondary outcomes included the Montreal Cognitive Assessment (MoCA), Dementia Rating Scale-2 (DRS-2), Neurotrax computerized cognitive battery, the Everyday Cognition Battery (ECB), and the Parkinson's Disease Questionnaire (PDQ-8). Twenty-six participants (92.9%) completed both study phase assessments, and 23 (82.1%) completed both phases on study medication. The CGIC response rate demonstrated a trend effect in favor of rivastigmine (regression coefficient for interaction term in linear mixed-effects model = 0.44, F[df] = 3.01 [1, 24], P = 0.096). For secondary outcomes, a significant rivastigmine effect on the ECB (regression coefficient = -2.41, F[df] = 5.81 [1, 22.05], P = 0.03) was seen, but no treatment effect was found on any cognitive measures. Trend effects also occurred in favor of rivastigmine on the PDQ-8 (regression coefficient = 4.55, F[df] = 3.93 [1, 14. 79], P = 0.09) and the State Anxiety Inventory (regression coefficient = -1.24, F[df] = 3.17 [1, 33], P = 0.08). Rivastigmine in PD-MCI showed a trend effect for improvements on a global rating of cognition, disease-related health status, and anxiety severity, and significant improvement on a performance-based measure of cognitive abilities. © 2015 International Parkinson and Movement Disorder Society. © 2015 International Parkinson and Movement Disorder Society.

Subjective Social Status and Self-Reported Health Among US-born and Immigrant Latinos.

PubMed

Garza, Jeremiah R; Glenn, Beth A; Mistry, Rashmita S; Ponce, Ninez A; Zimmerman, Frederick J

2017-02-01

Subjective social status is associated with a range of health outcomes. Few studies have tested the relevance of subjective social status among Latinos in the U.S.; those that have yielded mixed results. Data come from the Latino subsample of the 2003 National Latino and Asian American Study (N = 2554). Regression models adjusted for socioeconomic and demographic factors. Stratified analyses tested whether nativity status modifies the effect of subjective social status on health. Subjective social status was associated with better health. Income and education mattered more for health than subjective social status among U.S.-born Latinos. However, the picture was mixed among immigrant Latinos, with subjective social status more strongly predictive than income but less so than education. Subjective social status may tap into stressful immigrant experiences that affect one's perceived self-worth and capture psychosocial consequences and social disadvantage left out by conventional socioeconomic measures.

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

Quantification of dead vegetation fraction in mixed pastures using AisaFENIX imaging spectroscopy data

NASA Astrophysics Data System (ADS)

Pullanagari, R. R.; Kereszturi, G.; Yule, I. J.

2017-06-01

New Zealand farming relies heavily on grazed pasture for feeding livestock; therefore it is important to provide high quality palatable grass in order to maintain profitable and sustainable grassland management. The presence of non-photosynthetic vegetation (NPV) such as dead vegetation in pastures severely limits the quality and productivity of pastures. Quantifying the fraction of dead vegetation in mixed pastures is a great challenge even with remote sensing approaches. In this study, a high spatial resolution with pixel resolution of 1 m and spectral resolution of 3.5-5.6 nm imaging spectroscopy data from AisaFENIX (380-2500 nm) was used to assess the fraction of dead vegetation component in mixed pastures on a hill country farm in New Zealand. We used different methods to retrieve dead vegetation fraction from the spectra; narrow band vegetation indices, full spectrum based partial least squares (PLS) regression and feature selection based PLS regression. Among all approaches, feature selection based PLS model exhibited better performance in terms of prediction accuracy (R2CV = 0.73, RMSECV = 6.05, RPDCV = 2.25). The results were consistent with validation data, and also performed well on the external test data (R2 = 0.62, RMSE = 8.06, RPD = 2.06). In addition, statistical tests were conducted to ascertain the effect of topographical variables such as slope and aspect on the accumulation of the dead vegetation fraction. Steep slopes (>25°) had a significantly (p < 0.05) higher amount of dead vegetation. In contrast, aspect showed non-significant impact on dead vegetation accumulation. The results from the study indicate that AisaFENIX imaging spectroscopy data could be a useful tool for mapping the dead vegetation fraction accurately.

Experimental and numerical investigation on the ignition and combustion stability in solid fuel ramjet with swirling flow

NASA Astrophysics Data System (ADS)

Musa, Omer; Xiong, Chen; Changsheng, Zhou

2017-08-01

The present article investigates experimentally and numerically the ignition and flame stability of high-density polyethylene solid fuel with incoming swirling air through a solid fuel ramjet (SFRJ). A new design of swirler is proposed and used in this work. Experiments on connected pipes test facility were performed for SFRJ with and without swirl. An in-house code has been developed to simulate unsteady, turbulent, reacting, swirling flow in the SFRJ. Four different swirl intensities are utilized to study experimentally and numerically the effect of swirl number on the transient regression, ignition of the solid fuel in a hot-oxidizing flow and combustion phenomenon in the SFRJ. The results showed that using swirl flow decreases the ignition time delay, recirculation zone length, and the distance between the flame and the wall, meanwhile, increases the residence time, heat transfer, regression rate and mixing degree, thus, improving the combustion efficiency and stability.

Dysglycemia, Glycemic Variability, and Outcome After Cardiac Arrest and Temperature Management at 33°C and 36°C.

PubMed

Borgquist, Ola; Wise, Matt P; Nielsen, Niklas; Al-Subaie, Nawaf; Cranshaw, Julius; Cronberg, Tobias; Glover, Guy; Hassager, Christian; Kjaergaard, Jesper; Kuiper, Michael; Smid, Ondrej; Walden, Andrew; Friberg, Hans

2017-08-01

Dysglycemia and glycemic variability are associated with poor outcomes in critically ill patients. Targeted temperature management alters blood glucose homeostasis. We investigated the association between blood glucose concentrations and glycemic variability and the neurologic outcomes of patients randomized to targeted temperature management at 33°C or 36°C after cardiac arrest. Post hoc analysis of the multicenter TTM-trial. Primary outcome of this analysis was neurologic outcome after 6 months, referred to as "Cerebral Performance Category." Thirty-six sites in Europe and Australia. All 939 patients with out-of-hospital cardiac arrest of presumed cardiac cause that had been included in the TTM-trial. Targeted temperature management at 33°C or 36°C. Nonparametric tests as well as multiple logistic regression and mixed effects logistic regression models were used. Median glucose concentrations on hospital admission differed significantly between Cerebral Performance Category outcomes (p < 0.0001). Hyper- and hypoglycemia were associated with poor neurologic outcome (p = 0.001 and p = 0.054). In the multiple logistic regression models, the median glycemic level was an independent predictor of poor Cerebral Performance Category (Cerebral Performance Category, 3-5) with an odds ratio (OR) of 1.13 in the adjusted model (p = 0.008; 95% CI, 1.03-1.24). It was also a predictor in the mixed model, which served as a sensitivity analysis to adjust for the multiple time points. The proportion of hyperglycemia was higher in the 33°C group compared with the 36°C group. Higher blood glucose levels at admission and during the first 36 hours, and higher glycemic variability, were associated with poor neurologic outcome and death. More patients in the 33°C treatment arm had hyperglycemia.

No increase in small-solute transport in peritoneal dialysis patients treated without hypertonic glucose for fifty-four months.

PubMed

Pagniez, Dominique; Duhamel, Alain; Boulanger, Eric; Lessore de Sainte Foy, Celia; Beuscart, Jean-Baptiste

2017-08-31

Glucose is widely used as an osmotic agent in peritoneal dialysis (PD), but exerts untoward effects on the peritoneum. The potential protective effect of a reduced exposure to hypertonic glucose has never been investigated. The cohort of PD patients attending our center which tackled the challenge of a restricted use of hypertonic glucose solutions has been prospectively followed since 1992. Small-solute transport was assessed using an equivalent of the glucose peritoneal equilibration test after 6 months, and then every year. Study was stopped on July 1st, 2008, before use of biocompatible solutions. Repeated measures in patients treated with PD for 54 months were analyzed by using (1) the slopes of the linear regression for D 4 /D 0 ratios over time computed for each individual, and (2) a linear mixed model. In the study period, 44 patients were treated for a total of 2376 months, 2058 without hypertonic glucose. There was one episode of peritoneal infection every 18 patient-months. The mean of slopes of the linear regression for D 4 /D 0 ratios was found to be significantly positive (Student's test, p < .001) and the results of the mixed model reflected a similar significant increase for D 4 /D 0 ratios over time. These results reflected a significant decrease of small-solute transport. In this large series, minimizing the use of hypertonic glucose solutions was associated in patients on long term PD with an overall decrease of small-solute transport within 54 months, despite a high rate of peritoneal infection.

Socio-Economic Status and Peritonitis in Australian Non-Indigenous Peritoneal Dialysis Patients

PubMed Central

Tang, Wen; Grace, Blair; McDonald, Stephen P.; Hawley, Carmel M.; Badve, Sunil V.; Boudville, Neil C.; Brown, Fiona G.; Clayton, Philip A.; Johnson, David W.

2015-01-01

♦ Background: The aim of the present study was to investigate the relationship between socio-economic status (SES) and peritoneal dialysis (PD)-related peritonitis. ♦ Methods: Associations between area SES and peritonitis risk and outcomes were examined in all non-indigenous patients who received PD in Australia between 1 October 2003 and 31 December 2010 (peritonitis outcomes). SES was assessed by deciles of postcode-based Australian Socio-Economic Indexes for Areas (SEIFA), including Index of Relative Socio-economic Disadvantage (IRSD), Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), Index of Economic Resources (IER) and Index of Education and Occupation (IEO). ♦ Results: 7,417 patients were included in the present study. Mixed-effects Poisson regression demonstrated that incident rate ratios for peritonitis were generally lower in the higher SEIFA-based deciles compared with the reference (decile 1), although the reductions were only statistically significant in some deciles (IRSAD deciles 2 and 4 – 9; IRSD deciles 4 – 6; IER deciles 4 and 6; IEO deciles 3 and 6). Mixed-effects logistic regression showed that lower probabilities of hospitalization were predicted by relatively higher SES, and lower probabilities of peritonitis-associated death were predicted by less SES disadvantage status and greater access to economic resources. No association was observed between SES and the risks of peritonitis cure, catheter removal and permanent hemodialysis (HD) transfer. ♦ Conclusions: In Australia, where there is universal free healthcare, higher SES was associated with lower risks of peritonitis-associated hospitalization and death, and a lower risk of peritonitis in some categories. PMID:24497587

Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy-LUR approaches.

PubMed

Adam-Poupart, Ariane; Brand, Allan; Fournier, Michel; Jerrett, Michael; Smargiassi, Audrey

2014-09-01

Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide. We sought to compare the accuracy of three spatiotemporal models to predict summer ground-level O3 in Quebec, Canada. We developed a land-use mixed-effects regression (LUR) model based on readily available data (air quality and meteorological monitoring data, road networks information, latitude), a Bayesian maximum entropy (BME) model incorporating both O3 monitoring station data and the land-use mixed model outputs (BME-LUR), and a kriging method model based only on available O3 monitoring station data (BME kriging). We performed leave-one-station-out cross-validation and visually assessed the predictive capability of each model by examining the mean temporal and spatial distributions of the average estimated errors. The BME-LUR was the best predictive model (R2 = 0.653) with the lowest root mean-square error (RMSE ;7.06 ppb), followed by the LUR model (R2 = 0.466, RMSE = 8.747) and the BME kriging model (R2 = 0.414, RMSE = 9.164). Our findings suggest that errors of estimation in the interpolation of O3 concentrations with BME can be greatly reduced by incorporating outputs from a LUR model developed with readily available data.

Comparison of four methods for deriving hospital standardised mortality ratios from a single hierarchical logistic regression model.

PubMed

Mohammed, Mohammed A; Manktelow, Bradley N; Hofer, Timothy P

2016-04-01

There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data - patients nested within hospitals - and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocated for deriving standardised mortality ratios from a hierarchical logistic regression model, but their agreement is not known and neither do we know which is to be preferred. We found significant differences between the four types of standardised mortality ratios because they reflect a range of underlying conceptual issues. The most subtle issue is the distinction between asking how an average patient fares in different hospitals versus how patients at a given hospital fare at an average hospital. Since the answers to these questions are not the same and since the choice between these two approaches is not obvious, the extent to which profiling hospitals on mortality can be undertaken safely and reliably, without resolving these methodological issues, remains questionable. © The Author(s) 2012.

Serum estradiol does not differentiate stress, mixed and urge incontinent women around menopause. A report from the Women's Health in the Lund Area (WHILA) study.

PubMed

Hamer, Maria Andrada; Källén, Karin; Lidfeldt, Jonas; Samsioe, Göran; Teleman, Pia

2011-11-01

To outline serum estradiol levels in perimenopausal women with stress, mixed or urge incontinence. We believe the majority of urgency symptoms in perimenopausal women to be caused by a pelvic floor dysfunction and a hypermobility of the bladder neck. If this is the case, there would be no difference in estradiol levels between the groups. University hospital. In the observational Women's Health in the Lund Area study, a subset of 400/2221 women reporting urinary incontinence completed a detailed questionnaire regarding lower urinary tract symptoms and had their serum steroid hormone levels measured. Statistical analyses were made by Chi-square test, nonparametrical tests, ANOVA, multi- and univariate logistic regression analysis. Stress incontinence was reported by 196, mixed incontinence by 153 and urge incontinence by 43 women; in 369, serumestradiol values were available. Serum estradiol did not differ significantly between stress incontinent (median 49.5 pmo/l, range 2.63-875.4), urge incontinent (median 31.6 pmol/l, range 2.63-460.7) or mixed incontinent women (median 35.5 pmol/l, range 2.63-787.9, p=0.62). Logistic regression analysis correcting for age, parity, hormonal status, smoking, hysterectomy and BMI also failed to show any difference in estradiol levels between the groups (p=0.41-0.58). No significant differences in serum estradiol levels between stress, mixed or urge incontinent perimenopausal women could be demonstrated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Content-specificity in verbal recall: a randomized controlled study.

PubMed

Zirk-Sadowski, Jan; Szucs, Denes; Holmes, Joni

2013-01-01

In this controlled experiment we examined whether there are content effects in verbal short-term memory and working memory for verbal stimuli. Thirty-seven participants completed forward and backward digit and letter recall tasks, which were constructed to control for distance effects between stimuli. A maximum-likelihood mixed-effects logistic regression revealed main effects of direction of recall (forward vs backward) and content (digits vs letters). There was an interaction between type of recall and content, in which the recall of digits was superior to the recall of letters in verbal short-term memory but not in verbal working memory. These results demonstrate that the recall of information from verbal short-term memory is content-specific, whilst the recall of information from verbal working memory is content-general.

Patient satisfaction with ambulatory care in Germany: effects of patient- and medical practice-related factors.

PubMed

Auras, Silke; Ostermann, Thomas; de Cruppé, Werner; Bitzer, Eva-Maria; Diel, Franziska; Geraedts, Max

2016-12-01

The study aimed to illustrate the effect of the patients' sex, age, self-rated health and medical practice specialization on patient satisfaction. Secondary analysis of patient survey data using multilevel analysis (generalized linear mixed model, medical practice as random effect) using a sequential modelling strategy. We examined the effects of the patients' sex, age, self-rated health and medical practice specialization on four patient satisfaction dimensions: medical practice organization, information, interaction, professional competence. The study was performed in 92 German medical practices providing ambulatory care in general medicine, internal medicine or gynaecology. In total, 9888 adult patients participated in a patient survey using the validated 'questionnaire on satisfaction with ambulatory care-quality from the patient perspective [ZAP]'. We calculated four models for each satisfaction dimension, revealing regression coefficients with 95% confidence intervals (CIs) for all independent variables, and using Wald Chi-Square statistic for each modelling step (model validity) and LR-Tests to compare the models of each step with the previous model. The patients' sex and age had a weak effect (maximum regression coefficient 1.09, CI 0.39; 1.80), and the patients' self-rated health had the strongest positive effect (maximum regression coefficient 7.66, CI 6.69; 8.63) on satisfaction ratings. The effect of medical practice specialization was heterogeneous. All factors studied, specifically the patients' self-rated health, affected patient satisfaction. Adjustment should always be considered because it improves the comparability of patient satisfaction in medical practices with atypically varying patient populations and increases the acceptance of comparisons. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Comparison and Contrast of Two General Functional Regression Modeling Frameworks

PubMed Central

Morris, Jeffrey S.

2017-01-01

In this article, Greven and Scheipl describe an impressively general framework for performing functional regression that builds upon the generalized additive modeling framework. Over the past number of years, my collaborators and I have also been developing a general framework for functional regression, functional mixed models, which shares many similarities with this framework, but has many differences as well. In this discussion, I compare and contrast these two frameworks, to hopefully illuminate characteristics of each, highlighting their respecitve strengths and weaknesses, and providing recommendations regarding the settings in which each approach might be preferable. PMID:28736502

Comparison and Contrast of Two General Functional Regression Modeling Frameworks.

PubMed

Morris, Jeffrey S

2017-02-01

In this article, Greven and Scheipl describe an impressively general framework for performing functional regression that builds upon the generalized additive modeling framework. Over the past number of years, my collaborators and I have also been developing a general framework for functional regression, functional mixed models, which shares many similarities with this framework, but has many differences as well. In this discussion, I compare and contrast these two frameworks, to hopefully illuminate characteristics of each, highlighting their respecitve strengths and weaknesses, and providing recommendations regarding the settings in which each approach might be preferable.

The understanding and experience of mixed emotions in 3-5-year-old children.

PubMed

Smith, Joshua P; Glass, Daniel J; Fireman, Gary

2015-01-01

The term mixed emotions refers to the presence of two opposite-valence emotions toward a single target. Identifying when children begin to report experiencing and understanding mixed emotions is critical in identifying how skills such as adaptive functioning, coping strategies, environmental understanding, and socioemotional competence emerge. Prior research has shown that children as young as 5 years old can understand and experience mixed emotion, but perhaps appropriately sensitive methodologies can reveal these abilities in younger children. The present study evaluated 57 children between 3 and 5 years old for mixed emotion experience and understanding using an animated video clip in which a character experiences a mixed emotional episode. Ordinal logistic regression was utilized to examine the relation of gender, attention, and understanding of content to experience and understanding of mixed emotion. While only 12% of children reported experiencing mixed emotion while watching the clip, 49% of children-some as young as 3 years old-were able to recognize the mixed emotional experience of the character. Thus, mixed emotion understanding emerges earlier than previously identified and the expression of understanding may develop independently of the ability to report mixed emotion experience. These findings are discussed in relation to cognitive and developmental considerations.

The Impact of Pay on Navy Physician Retention in a Health Care Reform Environment.

DTIC Science & Technology

1998-03-01

Analyses 33 6. Generalist Physician Supply Under Alternative Specialty Mix 33 7. Specialist Physician Supply Under Alternative Specialty Mix 34 8...Fiscal Years 1992 to 1997 40 5. Comparison of proposed alternative pay plans 54 6. Evaluation of expected outcomes of alternative pay plans 55 7...Explanatory variables with the expected sign of regression coefficient 76 8. Comparison of Navy physicians’ pay to alternative civilian pay for selected

Using the simplified case mix tool (sCMT) to identify cost in special care dental services to support commissioning.

PubMed

Duane, B G; Freeman, R; Richards, D; Crosbie, S; Patel, P; White, S; Humphris, G

2017-03-01

To commission dental services for vulnerable (special care) patient groups effectively, consistently and fairly an evidence base is needed of the costs involved. The simplified Case Mixed Tool (sCMT) can assess treatment mode complexity for these patient groups. To determine if the sCMT can be used to identify costs of service provision. Patients (n=495) attending the Sussex Community NHS Trust Special Care Dental Service for care were assessed using the sCMT. sCMT score and costs (staffing, laboratory fees, etc.) besides patient age, whether a new patient and use of general anaesthetic/intravenous sedation. Statistical analysis (adjusted linear regression modelling) compared sCMT score and costs then sensitivity analyses of the costings to age, being a new patient and sedation use were undertaken. Regression tables were produced to present estimates of service costs. Costs increased with sCMT total scale and single item values in a predictable manner in all analyses except for 'cooperation'. Costs increased with the use of IV sedation; with each rising level of the sCMT, and with complexity in every sCMT category, except cooperation. Costs increased with increase in complexity of treatment mode as measured by sCMT scores. Measures such as the sCMT can provide predictions of the resource allocations required when commissioning special care dental services. Copyright© 2017 Dennis Barber Ltd.

Additive or non-additive effect of mixing oak in pine stands on soil properties depends on the tree species in Mediterranean forests.

PubMed

Brunel, Caroline; Gros, Raphael; Ziarelli, Fabio; Farnet Da Silva, Anne Marie

2017-07-15

This study investigated how oak abundance in pine stands (using relative Oak Basal Area %, OBA%) may modulate soil microbial functioning. Forests were composed of sclerophyllous species i.e. Quercus ilex mixed with Pinus halepensis Miller or of Q. pubescens mixed with P. sylvestris. We used a series of plots with OBA% ranging from 0 to 100% in the two types of stand (n=60) and both OLF and A-horizon compartments were analysed. Relations between OBA% and either soil chemical (C and N contents, quality of organic matter via solid-state NMR, pH, CaCO 3 ) or microbial (enzyme activities, basal respiration, biomass and catabolic diversity via BIOLOG) characteristics were described. OBA% increase led to a decrease in the recalcitrant fraction of organic matter (OM) in OLF and promoted microbial growth. Catabolic profiles of microbial communities from A-horizon were significantly modulated in Q. ilex and P. halepensis stand by OBA% and alkyl C to carboxyl C ratio (characteristic of cutin from Q. ilex tissues) and in Q. pubescens and P. sylvestris stands, by OBA% and pH. In A-horizon under Q. ilex and P. halepensis stands, linear regressions were found between catabolic diversity, microbial biomass and OBA% suggesting an additive effect. Conversely, in A-horizon Q. pubescens and P. sylvestris stands, the relationship between OBA% and either cellulase activities, polysaccharides or ammonium contents, suggested a non-additive effect of Q. pubescens and P. sylvestris, enhancing mineralization of the OM labile fraction for plots characterized by an OBA% ranging from 40% to 60%. Mixing oak with pine thus favored microbial dynamics in both type of stands though OBA% print varied with tree species and consequently sustainable soil functioning depend strongly on the composition of mixed stands. Our study indeed revealed that, when evaluating the benefits of forest mixed stand on soil microbial functioning and OM turnover, the identity of tree species has to be considered. Copyright © 2017 Elsevier B.V. All rights reserved.

Utility Estimates of Disease-Specific Health States in Prostate Cancer from Three Different Perspectives.

PubMed

Gries, Katharine S; Regier, Dean A; Ramsey, Scott D; Patrick, Donald L

2017-06-01

To develop a statistical model generating utility estimates for prostate cancer specific health states, using preference weights derived from the perspectives of prostate cancer patients, men at risk for prostate cancer, and society. Utility estimate values were calculated using standard gamble (SG) methodology. Study participants valued 18 prostate-specific health states with the five attributes: sexual function, urinary function, bowel function, pain, and emotional well-being. Appropriateness of model (linear regression, mixed effects, or generalized estimating equation) to generate prostate cancer utility estimates was determined by paired t-tests to compare observed and predicted values. Mixed-corrected standard SG utility estimates to account for loss aversion were calculated based on prospect theory. 132 study participants assigned values to the health states (n = 40 men at risk for prostate cancer; n = 43 men with prostate cancer; n = 49 general population). In total, 792 valuations were elicited (six health states for each 132 participants). The most appropriate model for the classification system was a mixed effects model; correlations between the mean observed and predicted utility estimates were greater than 0.80 for each perspective. Developing a health-state classification system with preference weights for three different perspectives demonstrates the relative importance of main effects between populations. The predicted values for men with prostate cancer support the hypothesis that patients experiencing the disease state assign higher utility estimates to health states and there is a difference in valuations made by patients and the general population.

Bus accident analysis of routes with/without bus priority.

PubMed

Goh, Kelvin Chun Keong; Currie, Graham; Sarvi, Majid; Logan, David

2014-04-01

This paper summarises findings on road safety performance and bus-involved accidents in Melbourne along roads where bus priority measures had been applied. Results from an empirical analysis of the accident types revealed significant reduction in the proportion of accidents involving buses hitting stationary objects and vehicles, which suggests the effect of bus priority in addressing manoeuvrability issues for buses. A mixed-effects negative binomial (MENB) regression and back-propagation neural network (BPNN) modelling of bus accidents considering wider influences on accident rates at a route section level also revealed significant safety benefits when bus priority is provided. Sensitivity analyses done on the BPNN model showed general agreement in the predicted accident frequency between both models. The slightly better performance recorded by the MENB model results suggests merits in adopting a mixed effects modelling approach for accident count prediction in practice given its capability to account for unobserved location and time-specific factors. A major implication of this research is that bus priority in Melbourne's context acts to improve road safety and should be a major consideration for road management agencies when implementing bus priority and road schemes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improved amputation-free survival in unreconstructable critical limb ischemia and its implications for clinical trial design and quality measurement.

PubMed

Benoit, Eric; O'Donnell, Thomas F; Kitsios, Georgios D; Iafrati, Mark D

2012-03-01

Amputation-free survival (AFS), a composite endpoint of mortality and amputation, is the preferred outcome measure in critical limb ischemia (CLI). Given the improvements in systemic management of atherosclerosis and interventional management of limb ischemia over the past 2 decades, we examined whether these outcomes have changed in patients with CLI without revascularization options (no option-critical limb ischemia [NO-CLI]). We reviewed the literature for published 1-year AFS, mortality, and amputation rates from control groups in NO-CLI trials. Summary proportions of events were estimated by conducting a random effects meta-analysis of proportions. To determine whether there had been any change in event rates over time, we performed a random effects meta-regression and a mixed effects logistic regression, both regressed against the variable "final year of recruitment." Eleven trials consisting of 886 patients satisfied search criteria, 7 of which presented AFS data. Summary proportion of events (95% confidence interval) were 0.551 (0.399 to 0.693) for AFS; 0.198 (0.116 to 0.317) for death; and 0.341 (0.209 to 0.487) for amputation. Regression analyses demonstrated that AFS has risen over time as mortality rates have fallen, and these improvements are statistically significant. The decrease in amputation rates failed to reach statistical significance. The lack of published data precluded a quantitative evaluation of any change in the clinical severity or comorbidities in the NO-CLI population. AFS and mortality rates in NO-CLI have improved over the past 2 decades. Due to declining event rates, clinical trials may underestimate treatment effects and thus fail to reach statistical significance unless sample sizes are increased or unless a subgroup with a higher event rate can be identified. Alternatively, comparing outcomes to historical values for quality measurement may overestimate treatment effects. Benchmark values of AFS and morality require periodic review and updating. Copyright © 2012 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power

PubMed Central

Fu, Qiang; George, Linda K.

2018-01-01

Abstract Previous studies have widely reported that the association between socioeconomic status (SES) and childhood overweight and obesity in China is significant and positive, which lends little support to the fundamental-cause perspective. Using multiple waves (1997, 2000, 2004 and 2006) of the China Health and Nutrition Survey (CHNS) (N = 2,556, 2,063, 1,431 and 1,242, respectively) and continuous BMI cut-points obtained from a polynomial method, (mixed-effect) logistic regression analyses show that parental state-sector employment, an important, yet overlooked, indicator of political power during the market transformation has changed from a risk factor for childhood overweight/obesity in 1997 to a protective factor for childhood overweight/obesity in 2006. Results from quantile regression analyses generate the same conclusions and demonstrate that the protective effect of parental state sector employment at high percentiles of BMI is robust under different estimation strategies. By bridging the fundamental causes perspective and theories of market transformation, this research not only documents the effect of political power on childhood overweight/obesity but also calls for the use of multifaceted, culturally-relevant stratification measures in testing the fundamental cause perspective across time and space. PMID:26178452

The impact of green stormwater infrastructure installation on surrounding health and safety.

PubMed

Kondo, Michelle C; Low, Sarah C; Henning, Jason; Branas, Charles C

2015-03-01

We investigated the health and safety effects of urban green stormwater infrastructure (GSI) installments. We conducted a difference-in-differences analysis of the effects of GSI installments on health (e.g., blood pressure, cholesterol and stress levels) and safety (e.g., felonies, nuisance and property crimes, narcotics crimes) outcomes from 2000 to 2012 in Philadelphia, Pennsylvania. We used mixed-effects regression models to compare differences in pre- and posttreatment measures of outcomes for treatment sites (n=52) and randomly chosen, matched control sites (n=186) within multiple geographic extents surrounding GSI sites. Regression-adjusted models showed consistent and statistically significant reductions in narcotics possession (18%-27% less) within 16th-mile, quarter-mile, half-mile (P<.001), and eighth-mile (P<.01) distances from treatment sites and at the census tract level (P<.01). Narcotics manufacture and burglaries were also significantly reduced at multiple scales. Nonsignificant reductions in homicides, assaults, thefts, public drunkenness, and narcotics sales were associated with GSI installation in at least 1 geographic extent. Health and safety considerations should be included in future assessments of GSI programs. Subsequent studies should assess mechanisms of this association.

Use of a tracing task to assess visuomotor performance for evidence of concussion and recuperation.

PubMed

Kelty-Stephen, Damian G; Qureshi Ahmad, Mona; Stirling, Leia

2015-12-01

The likelihood of suffering a concussion while playing a contact sport ranges from 15-45% per year of play. These rates are highly variable as athletes seldom report concussive symptoms, or do not recognize their symptoms. We performed a prospective cohort study (n = 206, aged 10-17) to examine visuomotor tracing to determine the sensitivity for detecting neuromotor components of concussion. Tracing variability measures were investigated for a mean shift with presentation of concussion-related symptoms and a linear return toward baseline over subsequent return visits. Furthermore, previous research relating brain injury to the dissociation of smooth movements into "submovements" led to the expectation that cumulative micropause duration, a measure of motion continuity, might detect likelihood of injury. Separate linear mixed effects regressions of tracing measures indicated that 4 of the 5 tracing measures captured both short-term effects of injury and longer-term effects of recovery with subsequent visits. Cumulative micropause duration has a positive relationship with likelihood of participants having had a concussion. The present results suggest that future research should evaluate how well the coefficients for the tracing parameter in the logistic regression help to detect concussion in novel cases. (c) 2015 APA, all rights reserved).

The Impact of Green Stormwater Infrastructure Installation on Surrounding Health and Safety

PubMed Central

Low, Sarah C.; Henning, Jason; Branas, Charles C.

2015-01-01

Objectives. We investigated the health and safety effects of urban green stormwater infrastructure (GSI) installments. Methods. We conducted a difference-in-differences analysis of the effects of GSI installments on health (e.g., blood pressure, cholesterol and stress levels) and safety (e.g., felonies, nuisance and property crimes, narcotics crimes) outcomes from 2000 to 2012 in Philadelphia, Pennsylvania. We used mixed-effects regression models to compare differences in pre- and posttreatment measures of outcomes for treatment sites (n = 52) and randomly chosen, matched control sites (n = 186) within multiple geographic extents surrounding GSI sites. Results. Regression-adjusted models showed consistent and statistically significant reductions in narcotics possession (18%–27% less) within 16th-mile, quarter-mile, half-mile (P < .001), and eighth-mile (P < .01) distances from treatment sites and at the census tract level (P < .01). Narcotics manufacture and burglaries were also significantly reduced at multiple scales. Nonsignificant reductions in homicides, assaults, thefts, public drunkenness, and narcotics sales were associated with GSI installation in at least 1 geographic extent. Conclusions. Health and safety considerations should be included in future assessments of GSI programs. Subsequent studies should assess mechanisms of this association. PMID:25602887

Heterogeneity in drug abuse among juvenile offenders: is mixture regression more informative than standard regression?

PubMed

Montgomery, Katherine L; Vaughn, Michael G; Thompson, Sanna J; Howard, Matthew O

2013-11-01

Research on juvenile offenders has largely treated this population as a homogeneous group. However, recent findings suggest that this at-risk population may be considerably more heterogeneous than previously believed. This study compared mixture regression analyses with standard regression techniques in an effort to explain how known factors such as distress, trauma, and personality are associated with drug abuse among juvenile offenders. Researchers recruited 728 juvenile offenders from Missouri juvenile correctional facilities for participation in this study. Researchers investigated past-year substance use in relation to the following variables: demographic characteristics (gender, ethnicity, age, familial use of public assistance), antisocial behavior, and mental illness symptoms (psychopathic traits, psychiatric distress, and prior trauma). Results indicated that standard and mixed regression approaches identified significant variables related to past-year substance use among this population; however, the mixture regression methods provided greater specificity in results. Mixture regression analytic methods may help policy makers and practitioners better understand and intervene with the substance-related subgroups of juvenile offenders.

The influence of training characteristics on the effect of exercise training in patients with coronary artery disease: Systematic review and meta-regression analysis.

PubMed

Kraal, Jos J; Vromen, Tom; Spee, Ruud; Kemps, Hareld M C; Peek, Niels

2017-10-15

Although exercise-based cardiac rehabilitation improves exercise capacity of coronary artery disease patients, it is unclear which training characteristic determines this improvement. Total energy expenditure and its constituent training characteristics (training intensity, session frequency, session duration and programme length) vary considerably among clinical trials, making it hard to compare studies directly. Therefore, we performed a systematic review and meta-regression analysis to assess the effect of total energy expenditure and its constituent training characteristics on exercise capacity. We identified randomised controlled trials comparing continuous aerobic exercise training with usual care for patients with coronary artery disease. Studies were included when training intensity, session frequency, session duration and programme length was described, and exercise capacity was reported in peakVO 2 . Energy expenditure was calculated from the four training characteristics. The effect of training characteristics on exercise capacity was determined using mixed effects linear regression analyses. The analyses were performed with and without total energy expenditure as covariate. Twenty studies were included in the analyses. The mean difference in peakVO 2 between the intervention group and control group was 3.97ml·min -1 ·kg -1 (p<0.01, 95% CI 2.86 to 5.07). Total energy expenditure was significantly related to improvement of exercise capacity (effect size 0.91ml·min -1 ·kg -1 per 100J·kg, p<0.01, 95% CI 0.77 to 1.06), no effect was found for its constituent training characteristics after adjustment for total energy expenditure. We conclude that the design of an exercise programme should primarily be aimed at optimising total energy expenditure rather than on one specific training characteristic. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Modeling recall memory for emotional objects in Alzheimer's disease.

PubMed

Sundstrøm, Martin

2011-07-01

To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p < .003). EM was not found for recognition in AD patients due to a ceiling effect. Healthy older adults scored overall higher in recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p < .014) and object status (p < .0001) as gift or non-gift. Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

PharmML in Action: an Interoperable Language for Modeling and Simulation.

PubMed

Bizzotto, R; Comets, E; Smith, G; Yvon, F; Kristensen, N R; Swat, M J

2017-10-01

PharmML is an XML-based exchange format created with a focus on nonlinear mixed-effect (NLME) models used in pharmacometrics, but providing a very general framework that also allows describing mathematical and statistical models such as single-subject or nonlinear and multivariate regression models. This tutorial provides an overview of the structure of this language, brief suggestions on how to work with it, and use cases demonstrating its power and flexibility. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Gender differences in French GPs' activity: the contribution of quantile regressions.

PubMed

Dumontet, Magali; Franc, Carine

2015-05-01

In any fee-for-service system, doctors may be encouraged to increase the number of services (private activity) they provide to receive a higher income. Studying private activity determinants helps to predict doctors' provision of care. In the context of strong feminization and heterogeneity in general practitioners' (GP) behavior, we first aim to measure the effects of the determinants of private activity. Second, we study the evolution of these effects along the private activity distribution. Third, we examine the differences between male and female GPs. From an exhaustive database of French GPs working in private practice in 2008, we performed an ordinary least squares (OLS) regression and quantile regressions (QR) on the GPs' private activity. Among other determinants, we examined the trade-offs within the GPs' household considering his/her marital status, spousal income, and children. While the OLS results showed that female GPs had less private activity than male GPs (-13%), the QR results emphasized a private activity gender gap that increased significantly in the upper tail of the distribution. We also find gender differences in the private activity determinants, including family structure, practice characteristics, and case-mix variables. For instance, having a youngest child under 12 years old had a positive effect on the level of private activity for male GPs and a negative effect for female GPs. The results allow us to understand to what extent the supply of care differs between male and female GPs. In the context of strong feminization, this is essential to consider for organizing and forecasting the GPs' supply of care.

Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions.

PubMed

Fischer, A; Friggens, N C; Berry, D P; Faverdin, P

2018-07-01

The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.

BIODEGRADATION PROBABILITY PROGRAM (BIODEG)

EPA Science Inventory

The Biodegradation Probability Program (BIODEG) calculates the probability that a chemical under aerobic conditions with mixed cultures of microorganisms will biodegrade rapidly or slowly. It uses fragment constants developed using multiple linear and non-linear regressions and d...

Modulation of the relationship between external knee adduction moments and medial joint contact forces across subjects and activities.

PubMed

Trepczynski, Adam; Kutzner, Ines; Bergmann, Georg; Taylor, William R; Heller, Markus O

2014-05-01

The external knee adduction moment (EAM) is often considered a surrogate measure of the distribution of loads across the tibiofemoral joint during walking. This study was undertaken to quantify the relationship between the EAM and directly measured medial tibiofemoral contact forces (Fmed ) in a sample of subjects across a spectrum of activities. The EAM for 9 patients who underwent total knee replacement was calculated using inverse dynamics analysis, while telemetric implants provided Fmed for multiple repetitions of 10 activities, including walking, stair negotiation, sit-to-stand activities, and squatting. The effects of the factors "subject" and "activity" on the relationships between Fmed and EAM were quantified using mixed-effects regression analyses in terms of the root mean square error (RMSE) and the slope of the regression. Across subjects and activities a good correlation between peak EAM and Fmed values was observed, with an overall R(2) value of 0.88. However, the slope of the linear regressions varied between subjects by up to a factor of 2. At peak EAM and Fmed , the RMSE of the regression across all subjects was 35% body weight (%BW), while the maximum error was 127 %BW. The relationship between EAM and Fmed is generally good but varies considerably across subjects and activities. These findings emphasize the limitation of relying solely on the EAM to infer medial joint loading when excessive directed cocontraction of muscles exists and call for further investigations into the soft tissue-related mechanisms that modulate the internal forces at the knee. Copyright © 2014 by the American College of Rheumatology.

Polythermal investigation of viscosity of solution of metal carboxylates in VIK-grade mixed carboxylic acids: Yttrium and gadolinium carboxylates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mezhov, E.A.; Samatov, A.V.; Troyanovskii, L.V.

Kinematic viscosities have been measured for solutions of yttrium and gadolinium carboxylates in grade VIK mixed carboxylic acids (MCA). It has been established that the optimal fluidity of these metal carboxylate solutions for application to articles is reached at 333 K. A regression model has been developed to describe the concentration and temperature dependences of the viscosity of yttrium- and gadolinium-containing MCA solutions. 2 refs., 3 tabs.

Dietary factors and the risk of testicular cancer.

PubMed

Bonner, Matthew R; McCann, Susan E; Moysich, Kirsten B

2002-01-01

The etiology of testicular cancer (TC) remains largely unknown. Few studies have investigated the role diet may play in the etiology of TC. We report on a hospital-based case-control study of TC and selected nutrients and food groups. Cases included 117 patients with primary, incident TC treated at Roswell Park Cancer Institute between 1982 and 1998. A total of 334 hospital controls were frequency matched on age to cases. Cases were categorized by histology (seminoma, nonseminoma, and mixed germ cell TC), and multinomial logistic regression and unconditional logistic regression were used to compute odds ratios (ORs) and 95% confidence intervals (CIs) comparing each histological type with the controls. For nonseminoma and mixed germ cell TC, vitamin E intake was suggestive of reduced risk (OR = 0.51, 95% CI = 0.15-1.76 and OR = 0.36, 95% CI = 0.01-1.31, respectively); for seminoma, it was suggestive of an increased risk (OR = 2.94, 95% CI = 0.99-8.78). Fat intakes were not associated with nonseminoma or mixed germ cell risk; high saturated, animal, and total fat intakes were suggestive of an increase in risk of seminoma. Overall, diet was not associated with TC. However, risk seemed to differ by histology, suggesting that seminoma, nonseminoma, and mixed germ cell TC may have different etiologies. We suggest that future investigations should continue to stratify cases by histology.

A comparison of different ways of including baseline counts in negative binomial models for data from falls prevention trials.

PubMed

Zheng, Han; Kimber, Alan; Goodwin, Victoria A; Pickering, Ruth M

2018-01-01

A common design for a falls prevention trial is to assess falling at baseline, randomize participants into an intervention or control group, and ask them to record the number of falls they experience during a follow-up period of time. This paper addresses how best to include the baseline count in the analysis of the follow-up count of falls in negative binomial (NB) regression. We examine the performance of various approaches in simulated datasets where both counts are generated from a mixed Poisson distribution with shared random subject effect. Including the baseline count after log-transformation as a regressor in NB regression (NB-logged) or as an offset (NB-offset) resulted in greater power than including the untransformed baseline count (NB-unlogged). Cook and Wei's conditional negative binomial (CNB) model replicates the underlying process generating the data. In our motivating dataset, a statistically significant intervention effect resulted from the NB-logged, NB-offset, and CNB models, but not from NB-unlogged, and large, outlying baseline counts were overly influential in NB-unlogged but not in NB-logged. We conclude that there is little to lose by including the log-transformed baseline count in standard NB regression compared to CNB for moderate to larger sized datasets. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effect of prospective reimbursement on nursing home costs.

PubMed Central

Coburn, A F; Fortinsky, R; McGuire, C; McDonald, T P

1993-01-01

OBJECTIVE. This study evaluates the effect of Maine's Medicaid nursing home prospective payment system on nursing home costs and access to care for public patients. DATA SOURCES/STUDY SETTING. The implementation of a facility-specific prospective payment system for nursing homes provided the opportunity for longitudinal study of the effect of that system. Data sources included audited Medicaid nursing home cost reports, quality-of-care data from state facility survey and licensure files, and facility case-mix information from random, stratified samples of homes and residents. Data were obtained for six years (1979-1985) covering the three-year period before and after implementation of the prospective payment system. STUDY DESIGN. This study used a pre-post, longitudinal analytical design in which interrupted, time-series regression models were estimated to test the effects of prospective payment and other factors, e.g., facility characteristics, nursing home market factors, facility case mix, and quality of care, on nursing home costs. PRINCIPAL FINDINGS. Prospective payment contributed to an estimated $3.03 decrease in total variable costs in the third year from what would have been expected under the previous retrospective cost-based payment system. Responsiveness to payment system efficiency incentives declined over the study period, however, indicating a growing problem in achieving further cost reductions. Some evidence suggested that cost reductions might have reduced access for public patients. CONCLUSIONS. Study findings are consistent with the results of other studies that have demonstrated the effectiveness of prospective payment systems in restraining nursing home costs. Potential policy trade-offs among cost containment, access, and quality assurance deserve further consideration, particularly by researchers and policymakers designing the new generation of case mix-based and other nursing home payment systems. PMID:8463109

Effect of prospective reimbursement on nursing home costs.

PubMed

Coburn, A F; Fortinsky, R; McGuire, C; McDonald, T P

1993-04-01

This study evaluates the effect of Maine's Medicaid nursing home prospective payment system on nursing home costs and access to care for public patients. The implementation of a facility-specific prospective payment system for nursing homes provided the opportunity for longitudinal study of the effect of that system. Data sources included audited Medicaid nursing home cost reports, quality-of-care data from state facility survey and licensure files, and facility case-mix information from random, stratified samples of homes and residents. Data were obtained for six years (1979-1985) covering the three-year period before and after implementation of the prospective payment system. This study used a pre-post, longitudinal analytical design in which interrupted, time-series regression models were estimated to test the effects of prospective payment and other factors, e.g., facility characteristics, nursing home market factors, facility case mix, and quality of care, on nursing home costs. Prospective payment contributed to an estimated $3.03 decrease in total variable costs in the third year from what would have been expected under the previous retrospective cost-based payment system. Responsiveness to payment system efficiency incentives declined over the study period, however, indicating a growing problem in achieving further cost reductions. Some evidence suggested that cost reductions might have reduced access for public patients. Study findings are consistent with the results of other studies that have demonstrated the effectiveness of prospective payment systems in restraining nursing home costs. Potential policy trade-offs among cost containment, access, and quality assurance deserve further consideration, particularly by researchers and policymakers designing the new generation of case mix-based and other nursing home payment systems.

Modeling indoor particulate exposures in inner city school classrooms

PubMed Central

Gaffin, Jonathan M.; Petty, Carter R.; Hauptman, Marissa; Kang, Choong-Min; Wolfson, Jack M.; Awad, Yara Abu; Di, Qian; Lai, Peggy S.; Sheehan, William J.; Baxi, Sachin; Coull, Brent A.; Schwartz, Joel D.; Gold, Diane R.; Koutrakis, Petros; Phipatanakul, Wanda

2016-01-01

Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed-effects linear models were used to determine the relationships between indoor PM2.5 and BC and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared to those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: 1) there are important PM2.5 sources in classrooms; 2) the penetration of outdoor PM2.5 particles varies by school, and 3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (Out of sample correlations: PM2.5: r2 = 0.68, BC; r2 = 0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available. PMID:27599884

Determination of boiling point of petrochemicals by gas chromatography-mass spectrometry and multivariate regression analysis of structural activity relationship.

PubMed

Fakayode, Sayo O; Mitchell, Breanna S; Pollard, David A

2014-08-01

Accurate understanding of analyte boiling points (BP) is of critical importance in gas chromatographic (GC) separation and crude oil refinery operation in petrochemical industries. This study reported the first combined use of GC separation and partial-least-square (PLS1) multivariate regression analysis of petrochemical structural activity relationship (SAR) for accurate BP determination of two commercially available (D3710 and MA VHP) calibration gas mix samples. The results of the BP determination using PLS1 multivariate regression were further compared with the results of traditional simulated distillation method of BP determination. The developed PLS1 regression was able to correctly predict analytes BP in D3710 and MA VHP calibration gas mix samples, with a root-mean-square-%-relative-error (RMS%RE) of 6.4%, and 10.8% respectively. In contrast, the overall RMS%RE of 32.9% and 40.4%, respectively obtained for BP determination in D3710 and MA VHP using a traditional simulated distillation method were approximately four times larger than the corresponding RMS%RE of BP prediction using MRA, demonstrating the better predictive ability of MRA. The reported method is rapid, robust, and promising, and can be potentially used routinely for fast analysis, pattern recognition, and analyte BP determination in petrochemical industries. Copyright © 2014 Elsevier B.V. All rights reserved.

Nursing home cost and ownership type: evidence of interaction effects.

PubMed

Arling, G; Nordquist, R H; Capitman, J A

1987-06-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed.

Nursing home cost and ownership type: evidence of interaction effects.

PubMed Central

Arling, G; Nordquist, R H; Capitman, J A

1987-01-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed. PMID:3301746

The effectiveness of nutrition education and labeling in Dutch supermarkets.

PubMed

Steenhuis, Ingrid; van Assema, Patricia; van Breukelen, Gerard; Glanz, Karen

2004-01-01

Nutrition education and labeling may help consumers to eat less fat. The purpose of this study is to assess the effect of nutrition education with and without shelf labeling on reduced fat intake in Dutch supermarkets. The design consisted of a randomized, pretest-posttest, experimental control group design. In total, 2203 clients of 13 supermarkets were included in the sample. Total fat intake of clients and behavioral determinants of eating less fat were measured by a questionnaire. A mixed-effect regression model was used for the analysis. No significant effects were found for the educational intervention, alone or with the labeling, on total fat intake and the psychosocial determinants of eating less fat. Nutrition education and labeling of low-fat food products in supermarkets did not prove to be effective strategies. The fact that the supermarket is a highly competitive environment may have accounted for this lack of effect.

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

Kinship and nonrelative foster care: the effect of placement type on child well-being.

PubMed

Font, Sarah A

2014-01-01

This study uses a national sample of 1,215 children, ages 6-17, who spent some time in formal kinship or nonrelative foster care to identify the effect of placement type on academic achievement, behavior, and health. Several identification strategies are used to reduce selection bias, including ordinary least squares, change score models, propensity score weighting, and instrumental variables regression. The results consistently estimate a negative effect of kin placements on reading scores, but kin placements appear to have no effect on child health, and findings on children's math and cognitive skills test scores and behavioral problems are mixed. Estimated declines in both academic achievement and behavioral problems are concentrated among children who are lower functioning at baseline. © 2014 The Author. Child Development © 2014 Society for Research in Child Development, Inc.

Inverse sampling regression for pooled data.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Eskridge, Kent; Crossa, José

2017-06-01

Because pools are tested instead of individuals in group testing, this technique is helpful for estimating prevalence in a population or for classifying a large number of individuals into two groups at a low cost. For this reason, group testing is a well-known means of saving costs and producing precise estimates. In this paper, we developed a mixed-effect group testing regression that is useful when the data-collecting process is performed using inverse sampling. This model allows including covariate information at the individual level to incorporate heterogeneity among individuals and identify which covariates are associated with positive individuals. We present an approach to fit this model using maximum likelihood and we performed a simulation study to evaluate the quality of the estimates. Based on the simulation study, we found that the proposed regression method for inverse sampling with group testing produces parameter estimates with low bias when the pre-specified number of positive pools (r) to stop the sampling process is at least 10 and the number of clusters in the sample is also at least 10. We performed an application with real data and we provide an NLMIXED code that researchers can use to implement this method.

Comparison of Total Solar Irradiance with NASA/NSO Spectromagnetograph Data in Solar Cycles 22 and 23

NASA Technical Reports Server (NTRS)

Jones, Harrison P.; Branston, Detrick D.; Jones, Patricia B.; Popescu, Miruna D.

2002-01-01

An earlier study compared NASA/NSO Spectromagnetograph (SPM) data with spacecraft measurements of total solar irradiance (TSI) variations over a 1.5 year period in the declining phase of solar cycle 22. This paper extends the analysis to an eight-year period which also spans the rising and early maximum phases of cycle 23. The conclusions of the earlier work appear to be robust: three factors (sunspots, strong unipolar regions, and strong mixed polarity regions) describe most of the variation in the SPM record, but only the first two are associated with TSI. Additionally, the residuals of a linear multiple regression of TSI against SPM observations over the entire eight-year period show an unexplained, increasing, linear time variation with a rate of about 0.05 W m(exp -2) per year. Separate regressions for the periods before and after 1996 January 01 show no unexplained trends but differ substantially in regression parameters. This behavior may reflect a solar source of TSI variations beyond sunspots and faculae but more plausibly results from uncompensated non-solar effects in one or both of the TSI and SPM data sets.

Effect of Landscape Pattern on Insect Species Density within Urban Green Spaces in Beijing, China

PubMed Central

Su, Zhimin; Li, Xiaoma; Zhou, Weiqi; Ouyang, Zhiyun

2015-01-01

Urban green space is an important refuge of biodiversity in urban areas. Therefore, it is crucial to understand the relationship between the landscape pattern of green spaces and biodiversity to mitigate the negative effects of urbanization. In this study, we collected insects from 45 green patches in Beijing during July 2012 using suction sampling. The green patches were dominated by managed lawns, mixed with scattered trees and shrubs. We examined the effects of landscape pattern on insect species density using hierarchical partitioning analysis and partial least squares regression. The results of the hierarchical partitioning analysis indicated that five explanatory variables, i.e., patch area (with 19.9% independent effects), connectivity (13.9%), distance to nearest patch (13.8%), diversity for patch types (11.0%), and patch shape (8.3%), significantly contributed to insect species density. With the partial least squares regression model, we found species density was negatively related to patch area, shape, connectivity, diversity for patch types and proportion of impervious surface at the significance level of p < 0.05 and positively related to proportion of vegetated land. Regression tree analysis further showed that the highest species density was found in green patches with an area <500 m2. Our results indicated that improvement in habitat quality, such as patch area and connectivity that are typically thought to be important for conservation, did not actually increase species density. However, increasing compactness (low-edge) of patch shape and landscape composition did have the expected effect. Therefore, it is recommended that the composition of the surrounding landscape should be considered simultaneously with planned improvements in local habitat quality. PMID:25793897

Effect of landscape pattern on insect species density within urban green spaces in Beijing, China.

PubMed

Su, Zhimin; Li, Xiaoma; Zhou, Weiqi; Ouyang, Zhiyun

2015-01-01

Urban green space is an important refuge of biodiversity in urban areas. Therefore, it is crucial to understand the relationship between the landscape pattern of green spaces and biodiversity to mitigate the negative effects of urbanization. In this study, we collected insects from 45 green patches in Beijing during July 2012 using suction sampling. The green patches were dominated by managed lawns, mixed with scattered trees and shrubs. We examined the effects of landscape pattern on insect species density using hierarchical partitioning analysis and partial least squares regression. The results of the hierarchical partitioning analysis indicated that five explanatory variables, i.e., patch area (with 19.9% independent effects), connectivity (13.9%), distance to nearest patch (13.8%), diversity for patch types (11.0%), and patch shape (8.3%), significantly contributed to insect species density. With the partial least squares regression model, we found species density was negatively related to patch area, shape, connectivity, diversity for patch types and proportion of impervious surface at the significance level of p < 0.05 and positively related to proportion of vegetated land. Regression tree analysis further showed that the highest species density was found in green patches with an area <500 m2. Our results indicated that improvement in habitat quality, such as patch area and connectivity that are typically thought to be important for conservation, did not actually increase species density. However, increasing compactness (low-edge) of patch shape and landscape composition did have the expected effect. Therefore, it is recommended that the composition of the surrounding landscape should be considered simultaneously with planned improvements in local habitat quality.

The consumption of alcohol mixed with energy drinks: prevalence and key correlates among Canadian high school students.

PubMed

Azagba, Sunday; Langille, Don; Asbridge, Mark

2013-01-01

An emerging body of research has reported high consumption of alcohol mixed with energy drinks among young adults, particularly college students. However, little is known about adolescents' consumption of these drinks. The purpose of this study was to determine the prevalence of consumption of alcohol mixed with energy drinks and to examine its correlates among Canadian high school students. We used a nationally representative sample of 36 155 Canadian students in grades 7 to 12 who participated in the 2010/2011 Youth Smoking Survey. About 20% of Canadian high school students reported consuming alcohol mixed with energy drinks in the last year, with considerable variation across provinces. Multivariate logistic regression analyses showed that the odds of consumption of these drinks were higher among students in lower grades (grades 7 and 8) and among students who identified their ethnicity as black or "other." Consumption of alcohol mixed with energy drinks was positively associated with substance use (current smoking [adjusted odds ratio (OR) 1.52, 95% confidence interval (CI) 1.19-1.95], past-year heavy drinking [adjusted OR 3.41, 95% CI 2.84-4.09] and marijuana use [adjusted OR 2.29, 95% CI 1.90-2.76]), absence from school, participation in school team sports and having more weekly spending money. Students who felt more connected to school and had an academic average of 70% or higher were less likely to consume alcohol mixed with energy drinks. The consumption of alcohol mixed with energy drinks is an emerging public health concern. Consumption of these drinks is substantial among Canadian high school students and can lead to many potential harms, both acute (e.g., injury) and long term (e.g., increased alcohol dependence). Our findings highlight the need for further research into the long-term effects of consumption of alcohol mixed with energy drinks among young people, as well as the development of interventions aimed at reducing consumption of these drinks.

Regression Analysis of Mixed Panel Count Data with Dependent Terminal Events

PubMed Central

Yu, Guanglei; Zhu, Liang; Li, Yang; Sun, Jianguo; Robison, Leslie L.

2017-01-01

Event history studies are commonly conducted in many fields and a great deal of literature has been established for the analysis of the two types of data commonly arising from these studies: recurrent event data and panel count data. The former arises if all study subjects are followed continuously, while the latter means that each study subject is observed only at discrete time points. In reality, a third type of data, a mixture of the two types of the data above, may occur and furthermore, as with the first two types of the data, there may exist a dependent terminal event, which may preclude the occurrences of recurrent events of interest. This paper discusses regression analysis of mixed recurrent event and panel count data in the presence of a terminal event and an estimating equation-based approach is proposed for estimation of regression parameters of interest. In addition, the asymptotic properties of the proposed estimator are established and a simulation study conducted to assess the finite-sample performance of the proposed method suggests that it works well in practical situations. Finally the methodology is applied to a childhood cancer study that motivated this study. PMID:28098397

Cleaning products and short-term respiratory effects among female cleaners with asthma.

PubMed

Vizcaya, David; Mirabelli, Maria C; Gimeno, David; Antó, Josep-Maria; Delclos, George L; Rivera, Marcela; Orriols, Ramon; Arjona, Lourdes; Burgos, Felip; Zock, Jan-Paul

2015-11-01

We evaluated the short-term effects of exposure to cleaning products on lung function and respiratory symptoms among professional cleaning women. Twenty-one women with current asthma and employed as professional cleaners participated in a 15-day panel study. During 312 person-days of data collection, participants self-reported their use of cleaning products and respiratory symptoms in daily diaries and recorded their forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) three times per day using a handheld spirometer. We evaluated associations of cleaning product use with upper and lower respiratory tract symptoms using Poisson mixed regression models and with changes in FEV1 and PEF using linear mixed regression analyses. Participants reported using an average of 2.4 cleaning products per day, with exposure to at least one strong irritant (eg, ammonia, bleach, hydrochloric acid) on 56% of person-days. Among participants without atopy, lower respiratory tract symptoms were associated with the use of hydrochloric acid and detergents. Measurements of FEV1 and PEF taken in the evening were 174 mL (95% CI 34 to 314) and 37 L/min (CI 4 to 70), respectively, lower on days when three or more sprays were used. Evening and next morning FEV1 were both lower following the use of hydrochloric acid (-616 and -526 mL, respectively) and solvents (-751 and -1059 mL, respectively). Diurnal variation in FEV1 and PEF increased on days when ammonia and lime-scale removers were used. The use of specific cleaning products at work, mainly irritants and sprays, may exacerbate asthma. 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.

Dialectical Behavior Therapy Compared With Enhanced Usual Care for Adolescents With Repeated Suicidal and Self-Harming Behavior: Outcomes Over a One-Year Follow-Up.

PubMed

Mehlum, Lars; Ramberg, Maria; Tørmoen, Anita J; Haga, Egil; Diep, Lien M; Stanley, Barbara H; Miller, Alec L; Sund, Anne M; Grøholt, Berit

2016-04-01

We conducted a 1-year prospective follow-up study of posttreatment clinical outcomes in adolescents with recent and repetitive self-harm who had been randomly allocated to receive 19 weeks of either dialectical behavior therapy adapted for adolescents (DBT-A) or enhanced usual care (EUC) at community child and adolescent psychiatric outpatient clinics. Assessments of self-harm, suicidal ideation, depression, hopelessness, borderline symptoms, and global level of functioning were made at the end of the 19-week treatment period and at follow-up 1 year later. Altogether 75 of the 77 (97%) adolescents participated at both time points. Frequencies of hospitalizations, emergency department visits and other use of mental health care during the 1-year follow-up period were recorded. Change analyses were performed using mixed effects linear spline regression and mixed effect Poisson regression with robust variance. Over the 52-week follow-up period, DBT-A remained superior to EUC in reducing the frequency of self-harm. For other outcomes such as suicidal ideation, hopelessness, and depressive or borderline symptoms and for the global level of functioning, inter-group differences apparent at the 19-week assessment were no longer observed, mainly due to participants in the EUC group having significantly improved on these dimensions over the follow-up year, whereas DBT-A participants remained unchanged. A stronger long-term reduction in self-harm and a more rapid recovery in suicidal ideation, depression, and borderline symptoms suggest that DBT-A may be a favorable treatment alternative for adolescents with repetitive self-harming behavior. Treatment for Adolescents With Deliberate Self Harm; http://clinicaltrials.gov/; NCT00675129. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Longitudinal data analysis in support of functional stability concepts for leachate management at closed municipal landfills

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gibbons, Robert D., E-mail: rdg@uchicago.edu; Morris, Jeremy W.F., E-mail: jmorris@geosyntec.com; Prucha, Christopher P., E-mail: cprucha@wm.com

2014-09-15

Highlights: • Longitudinal data analysis using a mixed-effects regression model. • Dataset consisted of a total of 1402 samples from 101 closed municipal landfills. • Target analytes and classes generally showed predictable degradation trends. • Validates historical studies focused on macro organic indicators such as BOD. • BOD can serve as “gateway” indicator for planning leachate management. - Abstract: Landfill functional stability provides a target that supports no environmental threat at the relevant point of exposure in the absence of active control systems. With respect to leachate management, this study investigates “gateway” indicators for functional stability in terms of themore » predictability of leachate characteristics, and thus potential threat to water quality posed by leachate emissions. Historical studies conducted on changes in municipal solid waste (MSW) leachate concentrations over time (longitudinal analysis) have concentrated on indicator compounds, primarily chemical oxygen demand (COD) and biochemical oxygen demand (BOD). However, validation of these studies using an expanded database and larger constituent sets has not been performed. This study evaluated leachate data using a mixed-effects regression model to determine the extent to which leachate constituent degradation can be predicted based on waste age or operational practices. The final dataset analyzed consisted of a total of 1402 samples from 101 MSW landfills. Results from the study indicated that all leachate constituents exhibit a decreasing trend with time in the post-closure period, with 16 of the 25 target analytes and aggregate classes exhibiting a statistically significant trend consistent with well-studied indicators such as BOD. Decreasing trends in BOD concentration after landfill closure can thus be considered representative of trends for many leachate constituents of concern.« less

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Anthropometry and blood pressure changes in a Caribbean adolescent population of African ancestry: an evaluation of longitudinal data using a multilevel mixed regression approach.

PubMed

Nichols, S; Cadogan, F

2012-10-01

The aim of this study was to determine the effect of growth pattern on blood pressure changes in an adolescent population of African ancestry based on longitudinal data and to compare this with estimates derived from cross-sectional data. Participants had measurements of weight, height, blood pressure and percentage body fat taken annually using standardized procedures. Annual blood pressure and anthropometry velocities as well as one- and three-year interval gender specific tracking coefficients were computed. We investigated whether changes in blood pressure could be explained by measures of growth using a multilevel mixed regression approach. The results showed that systolic blood pressure (SBP) increased by 1.27 and 3.09 mmHg per year among females and males, respectively. Similarly, diastolic blood pressure (DBP) increased by 1.16 and 1.92 mmHg per year among females and males, respectively. Multilevel analyses suggested that weight, body mass index, percentage body fat and height were the strongest anthropometric determinants of blood pressure change in this population. The results also suggest that there are gender differences in the relative importance of these anthropometric measures with height playing a minor role in predicting blood pressure changes among adolescent females. With the exception of DBP at 18 years among females, there were no significant differences between mean blood pressure generated from cross-sectional and longitudinal data by age in both males and females. Anthropometric measures are important covariates of age-related blood pressure changes and cross-sectional data may provide a more cost-effective and useful proxy for generating age-related blood pressure estimates in this population.

Population mixing for leukaemia, lymphoma and CNS tumours in teenagers and young adults in England, 1996-2005.

PubMed

van Laar, Marlous; Stark, Daniel P; McKinney, Patricia; Parslow, Roger C; Kinsey, Sally E; Picton, Susan V; Feltbower, Richard G

2014-09-23

Little aetiological epidemiological research has been undertaken for major cancers occurring in teenagers and young adults (TYA). Population mixing, as a possible proxy for infectious exposure, has been well researched for childhood malignancies. We aimed to investigate effects of population mixing in this older age group using an English national cancer dataset. Cases of leukaemia, lymphoma and central nervous system (CNS) tumours amongst 15-24 year olds in England (diagnosed 1996-2005) were included in the study. Data were obtained by ward of diagnosis and linked to 1991 census variables including population mixing (Shannon index); data on person-weighted population density and deprivation (Townsend score) were also used and considered as explanatory variables. Associations between TYA cancer incidence and census variables were investigated using negative binomial regression, and results presented as incidence rate ratios (IRR) with 95% confidence intervals (CI). A total of 6251 cases of leukaemia (21%), lymphoma (49%) and CNS tumours (30%) were analysed. Higher levels of population mixing were associated with a significant decrease in the incidence of CNS tumours (IRR=0.83, 95% CI=0.75-0.91), accounted for by astrocytomas and 'other CNS tumours'; however, there was no association with leukaemia or lymphoma. Incidence of CNS tumours and lymphoma was 3% lower in more deprived areas (IRR=0.97, 95% CI=0.96-0.99 and IRR=0.97, 95% CI=.96-0.98 respectively). Population density was not associated with the incidence of leukaemia, lymphoma or CNS tumours. Our results suggest a possible role for environmental risk factors with population correlates in the aetiology of CNS tumours amongst TYAs. Unlike studies of childhood cancer, associations between population mixing and the incidence of leukaemia and lymphoma were not observed.

Changes in contraceptive use and method mix in Pakistan: 1990-91 to 2006-07.

PubMed

Carton, Thomas W; Agha, Sohail

2012-03-01

To determine (a) whether the influence of the determinants of family planning use in Pakistan changed between 1990-91 and 2006-07, and (b) if these changes were associated with changes in the method mix. Data from the Pakistan Demographic and Health Surveys (PDHS) of 1990-91 and 2006-07 were used in the analyses. Data on 5184 married, non-pregnant, fecund women in 1990-91 and 8041 married, non-pregnant, fecund women in 2006-07 were used. Logistic regression analysis was used to identify factors associated with the use of any contraceptive method and whether the influence of these factors changed between the survey years. Changes in the method mix were examined. The effects of urban/rural residence, wealth and education on contraceptive use changed between 1990-91 and 2006-07. Differentials in contraceptive use by residence, wealth and education declined and were accompanied by changes in the method mix. In rural areas and among less-educated women, the contribution of traditional methods to the method mix increased. Among the poorest women, the method mix shifted towards traditional methods and condoms. Less-educated, rural, Pakistani women increased the use of family planning at a faster rate than more-educated, urban, women by adopting the use of traditional family planning methods. Poor women also increased family planning use more quickly than non-poor women, by adopting condoms and traditional methods. The more rapid increase in the demand for family planning among poorer, less-educated, rural women is a positive trend. In order to convert this demand into the use of longer-term modern methods, however, access to high quality services must be improved in rural and low-income urban areas.

Gender differences in the causal direction between workplace harassment and drinking.

PubMed

Freels, Sally A; Richman, Judith A; Rospenda, Kathleen M

2005-08-01

Data from a longitudinal study of university employees across four waves is used to determine the extent to which workplace harassment predicts drinking or conversely the extent to which drinking predicts workplace harassment, and to address gender differences in these relationships. Mixed effects regression models are used to test the effects of 1) harassment at the previous wave on drinking at the current wave, adjusting for drinking at the previous wave, and 2) drinking at the previous wave on harassment at the current wave, adjusting for harassment at the previous wave. For males, drinking at the previous wave predicts sexual harassment at the current wave, whereas for females, sexual harassment at the previous wave predicts drinking at the current wave.

Traditional Masculinity as a Risk Factor for Suicidal Ideation: Cross-Sectional and Prospective Evidence from a Study of Young Adults.

PubMed

Coleman, Daniel

2015-01-01

Traditional masculinity is hypothesized to be associated with suicidal ideation, and traditional masculinity is predicted to interact with stressors, intensifying suicidal ideation. Cross-sectional and prospective data from a study of 2,431 young adults was analyzed using hierarchical regression main effects and interaction models. Traditional masculinity was associated with suicidal ideation, second only in strength to depression, including when controlling for other risk factors. Prospective effects were substantially weaker. There was mixed evidence for traditional masculinity by stress interactions. The results provide preliminary support for the role of traditional masculinity in suicidal ideation, but the relationship should be tested in studies of suicide attempts and mortality. Implications for prevention and intervention are explored.

Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey

PubMed Central

Chalkley, Martin

2017-01-01

Objective To analyse how training doctors’ demographic and socioeconomic characteristics vary according to the specialty that they are training for. Design Descriptive statistics and mixed logistic regression analysis of cross-sectional survey data to quantify evidence of systematic relationships between doctors’ characteristics and their specialty. Setting Doctors in training in the United Kingdom in 2013. Participants 27 530 doctors in training but not in their foundation year who responded to the National Training Survey 2013. Main outcome measures Mixed logit regression estimates and the corresponding odds ratios (calculated separately for all doctors in training and a subsample comprising those educated in the UK), relating gender, age, ethnicity, place of studies, socioeconomic background and parental education to the probability of training for a particular specialty. Results Being female and being white British increase the chances of being in general practice with respect to any other specialty, while coming from a better-off socioeconomic background and having parents with tertiary education have the opposite effect. Mixed results are found for age and place of studies. For example, the difference between men and women is greatest for surgical specialties for which a man is 12.121 times more likely to be training to a surgical specialty (relative to general practice) than a woman (p-value<0.01). Doctors who attended an independent school which is proxy for doctor’s socioeconomic background are 1.789 and 1.413 times more likely to be training for surgical or medical specialties (relative to general practice) than those who attended a state school (p-value<0.01). Conclusions There are systematic and substantial differences between specialties in respect of training doctors’ gender, ethnicity, age and socioeconomic background. The persistent underrepresentation in some specialties of women, minority ethnic groups and of those coming from disadvantaged backgrounds will impact on the representativeness of the profession into the future. Further research is needed to understand how the processes of selection and the self-selection of applicants into specialties gives rise to these observed differences. PMID:28801397

Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.

PubMed

Tan, Li Kuo; Liew, Yih Miin; Lim, Einly; McLaughlin, Robert A

2017-07-01

Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints. We have benchmarked our approach primarily against the publicly-available left ventricle segmentation challenge (LVSC) dataset, which consists of 100 training and 100 validation cardiac MRI cases representing a heterogeneous mix of cardiac pathologies and imaging parameters across multiple centers. Our approach attained a .77 Jaccard index, which is the highest published overall result in comparison to other automated algorithms. To test general applicability, we also evaluated against the Kaggle Second Annual Data Science Bowl, where the evaluation metric was the indirect clinical measures of LV volume rather than direct myocardial contours. Our approach attained a Continuous Ranked Probability Score (CRPS) of .0124, which would have ranked tenth in the original challenge. With this we demonstrate the effectiveness of convolutional neural network regression paired with domain-specific features in clinical segmentation. Copyright © 2017 Elsevier B.V. All rights reserved.

Acute Effects of Nitrogen Dioxide on Cardiovascular Mortality in Beijing: An Exploration of Spatial Heterogeneity and the District-specific Predictors

NASA Astrophysics Data System (ADS)

Luo, Kai; Li, Runkui; Li, Wenjing; Wang, Zongshuang; Ma, Xinming; Zhang, Ruiming; Fang, Xin; Wu, Zhenglai; Cao, Yang; Xu, Qun

2016-12-01

The exploration of spatial variation and predictors of the effects of nitrogen dioxide (NO2) on fatal health outcomes is still sparse. In a multilevel case-crossover study in Beijing, China, we used mixed Cox proportional hazard model to examine the citywide effects and conditional logistic regression to evaluate the district-specific effects of NO2 on cardiovascular mortality. District-specific predictors that could be related to the spatial pattern of NO2 effects were examined by robust regression models. We found that a 10 μg/m3 increase in daily mean NO2 concentration was associated with a 1.89% [95% confidence interval (CI): 1.33-2.45%], 2.07% (95% CI: 1.23-2.91%) and 1.95% (95% CI: 1.16-2.72%) increase in daily total cardiovascular (lag03), cerebrovascular (lag03) and ischemic heart disease (lag02) mortality, respectively. For spatial variation of NO2 effects across 16 districts, significant effects were only observed in 5, 4 and 2 districts for the above three outcomes, respectively. Generally, NO2 was likely having greater adverse effects on districts with larger population, higher consumption of coal and more civilian vehicles. Our results suggested independent and spatially varied effects of NO2 on total and subcategory cardiovascular mortalities. The identification of districts with higher risk can provide important insights for reducing NO2 related health hazards.

Stand and landscape level effects of a major outbreak of spruce beetles on forest vegetation in the Copper River Basin, Alaska

USGS Publications Warehouse

Allen, J.L.; Wesser, S.; Markon, C.J.; Winterberger, K.C.

2006-01-01

From 1989 to 2003, a widespread outbreak of spruce beetles (Dendroctonus rufipennis) in the Copper River Basin, Alaska, infested over 275,000 ha of forests in the region. During 1997 and 1998, we measured forest vegetation structure and composition on one hundred and thirty-six 20-m ?? 20-m plots to assess both the immediate stand and landscape level effects of the spruce beetle infestation. A photo-interpreted vegetation and infestation map was produced using color-infrared aerial photography at a scale of 1:40,000. We used linear regression to quantify the effects of the outbreak on forest structure and composition. White spruce (Picea glauca) canopy cover and basal area of medium-to-large trees [???15 cm diameter-at-breast height (1.3 m, dbh)] were reduced linearly as the number of trees attacked by spruce beetles increased. Black spruce (Picea mariana) and small diameter white spruce (<15 cm dbh) were infrequently attacked and killed by spruce beetles. This selective attack of mature white spruce reduced structural complexity of stands to earlier stages of succession and caused mixed tree species stands to lose their white spruce and become more homogeneous in overstory composition. Using the resulting regressions, we developed a transition matrix to describe changes in vegetation types under varying levels of spruce beetle infestations, and applied the model to the vegetation map. Prior to the outbreak, our study area was composed primarily of stands of mixed white and black spruce (29% of area) and pure white spruce (25%). However, the selective attack on white spruce caused many of these stands to transition to black spruce dominated stands (73% increase in area) or shrublands (26% increase in area). The post-infestation landscape was thereby composed of more even distributions of shrubland and white, black, and mixed spruce communities (17-22% of study area). Changes in the cover and composition of understory vegetation were less evident in this study. However, stands with the highest mortality due to spruce beetles had the lowest densities of white spruce seedlings suggesting a longer forest regeneration time without an increase in seedling germination, growth, or survival. ?? 2006 Elsevier B.V. All rights reserved.

Suicidality in pediatric bipolar disorder: predictor or outcome of family processes and mixed mood presentation?

PubMed Central

Algorta, Guillermo Pérez; Youngstrom, Eric A; Frazier, Thomas W; Freeman, Andrew J; Youngstrom, Jennifer Kogos; Findling, Robert L

2011-01-01

Objective Pediatric bipolar disorder (PBD) involves a potent combination of mood dysregulation and interpersonal processes, placing these youth at significantly greater risk of suicide. We examined the relationship between suicidal behavior, mood symptom presentation, family functioning, and quality of life (QoL) in youth with PBD. Methods Participants were 138 youths aged 5–18 years presenting to outpatient clinics with DSM-IV diagnoses of bipolar I disorder (n = 27), bipolar II disorder (n = 18), cyclothymic disorder (n = 48), and bipolar disorder not otherwise specified (n = 45). Results Twenty PBD patients had lifetime suicide attempts, 63 had past or current suicide ideation, and 55 were free of suicide ideation and attempts. Attempters were older than nonattempters. Suicide ideation and attempts were linked to higher depressive symptoms, and rates were even higher in youths meeting criteria for the mixed specifier proposed for DSM-5. Both suicide ideation and attempts were associated with lower youth QoL and poorer family functioning. Parent effects (with suicidality treated as outcome) and child effects (where suicide was the predictor of poor family functioning) showed equally strong evidence in regression models, even after adjusting for demographics. Conclusions These findings underscore the strong association between mixed features and suicidality in PBD, as well as the association between QoL, family functioning, and suicidality. It is possible that youths are not just a passive recipient of family processes, and their illness may play an active role in disrupting family functioning. Replication with longitudinal data and qualitative methods should investigate both child and parent effect models. PMID:21320255

Suicidality in pediatric bipolar disorder: predictor or outcome of family processes and mixed mood presentation?

PubMed

Algorta, Guillermo Pérez; Youngstrom, Eric A; Frazier, Thomas W; Freeman, Andrew J; Youngstrom, Jennifer Kogos; Findling, Robert L

2011-02-01

Pediatric bipolar disorder (PBD) involves a potent combination of mood dysregulation and interpersonal processes, placing these youth at significantly greater risk of suicide. We examined the relationship between suicidal behavior, mood symptom presentation, family functioning, and quality of life (QoL) in youth with PBD. Participants were 138 youths aged 5-18 years presenting to outpatient clinics with DSM-IV diagnoses of bipolar I disorder (n=27), bipolar II disorder (n=18), cyclothymic disorder (n=48), and bipolar disorder not otherwise specified (n=45). Twenty PBD patients had lifetime suicide attempts, 63 had past or current suicide ideation, and 55 were free of suicide ideation and attempts. Attempters were older than nonattempters. Suicide ideation and attempts were linked to higher depressive symptoms, and rates were even higher in youths meeting criteria for the mixed specifier proposed for DSM-5. Both suicide ideation and attempts were associated with lower youth QoL and poorer family functioning. Parent effects (with suicidality treated as outcome) and child effects (where suicide was the predictor of poor family functioning) showed equally strong evidence in regression models, even after adjusting for demographics. These findings underscore the strong association between mixed features and suicidality in PBD, as well as the association between QoL, family functioning, and suicidality. It is possible that youths are not just a passive recipient of family processes, and their illness may play an active role in disrupting family functioning. Replication with longitudinal data and qualitative methods should investigate both child and parent effect models. © 2011 John Wiley and Sons A/S.

Adjusted adaptive Lasso for covariate model-building in nonlinear mixed-effect pharmacokinetic models.

PubMed

Haem, Elham; Harling, Kajsa; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Karlsson, Mats O

2017-02-01

One important aim in population pharmacokinetics (PK) and pharmacodynamics is identification and quantification of the relationships between the parameters and covariates. Lasso has been suggested as a technique for simultaneous estimation and covariate selection. In linear regression, it has been shown that Lasso possesses no oracle properties, which means it asymptotically performs as though the true underlying model was given in advance. Adaptive Lasso (ALasso) with appropriate initial weights is claimed to possess oracle properties; however, it can lead to poor predictive performance when there is multicollinearity between covariates. This simulation study implemented a new version of ALasso, called adjusted ALasso (AALasso), to take into account the ratio of the standard error of the maximum likelihood (ML) estimator to the ML coefficient as the initial weight in ALasso to deal with multicollinearity in non-linear mixed-effect models. The performance of AALasso was compared with that of ALasso and Lasso. PK data was simulated in four set-ups from a one-compartment bolus input model. Covariates were created by sampling from a multivariate standard normal distribution with no, low (0.2), moderate (0.5) or high (0.7) correlation. The true covariates influenced only clearance at different magnitudes. AALasso, ALasso and Lasso were compared in terms of mean absolute prediction error and error of the estimated covariate coefficient. The results show that AALasso performed better in small data sets, even in those in which a high correlation existed between covariates. This makes AALasso a promising method for covariate selection in nonlinear mixed-effect models.

Log-normal frailty models fitted as Poisson generalized linear mixed models.

PubMed

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Hospital support services and the impacts of outsourcing on occupational health and safety.

PubMed

Siganporia, Pearl; Astrakianakis, George; Alamgir, Hasanat; Ostry, Aleck; Nicol, Anne-Marie; Koehoorn, Mieke

2016-10-01

Outsourcing labor is linked to negative impacts on occupational health and safety (OHS). In British Columbia, Canada, provincial health care service providers outsource support services such as cleaners and food service workers (CFSWs) to external contractors. This study investigates the impact of outsourcing on the occupational health safety of hospital CFSWs through a mixed methods approach. Worker's compensation data for hospital CFSWs were analyzed by negative binomial and multiple linear regressions supplemented by iterative thematic analysis of telephone interviews of the same job groups. Non-significant decreases in injury rates and days lost per injury were observed in outsourced CFSWs post outsourcing. Significant decreases (P < 0.05) were observed in average costs per injury for cleaners post outsourcing. Outsourced workers interviewed implied instances of underreporting workplace injuries. This mixed methods study describes the impact of outsourcing on OHS of healthcare workers in British Columbia. Results will be helpful for policy-makers and workplace regulators to assess program effectiveness for outsourced workers.

Redefining Racial Residential Segregation and its Association With Physical Activity Among African Americans 50 years and Older: A Mixed Methods Approach

PubMed Central

Armstrong-Brown, Janelle; Eng, Eugenia; Hammond, Wizdom Powell; Zimmer, Catherine; Bowling, J. Michael

2016-01-01

Physical inactivity is one of the factors contributing to disproportionate disease rates among older African Americans. Previous literature indicates that older African Americans are more likely to live in racially segregated neighborhoods and that racial residential segregation is associated with limited opportunities for physical activity. A cross-sectional mixed methods study was conducted guided by the concept of therapeutic landscapes. Multilevel regression analyses demonstrated that racial residential segregation was associated with more minutes of physical activity and greater odds of meeting physical activity recommendations. Qualitative interviews revealed the following physical activity related themes: aging of the neighborhood, knowing your neighbors, feeling of safety, and neighborhood racial identity. Perceptions of social cohesion enhanced participants’ physical activity, offering a plausible explanation to the higher rates of physical activity found in this population. Understanding how social cohesion operates within racially segregated neighborhoods can help to inform the design of effective interventions for this population. PMID:24812201

Hospital support services and the impacts of outsourcing on occupational health and safety

PubMed Central

Alamgir, Hasanat; Ostry, Aleck; Nicol, Anne-Marie; Koehoorn, Mieke

2016-01-01

Background Outsourcing labor is linked to negative impacts on occupational health and safety (OHS). In British Columbia, Canada, provincial health care service providers outsource support services such as cleaners and food service workers (CFSWs) to external contractors. Objectives This study investigates the impact of outsourcing on the occupational health safety of hospital CFSWs through a mixed methods approach. Methods Worker’s compensation data for hospital CFSWs were analyzed by negative binomial and multiple linear regressions supplemented by iterative thematic analysis of telephone interviews of the same job groups. Results Non-significant decreases in injury rates and days lost per injury were observed in outsourced CFSWs post outsourcing. Significant decreases (P < 0.05) were observed in average costs per injury for cleaners post outsourcing. Outsourced workers interviewed implied instances of underreporting workplace injuries. Conclusions This mixed methods study describes the impact of outsourcing on OHS of healthcare workers in British Columbia. Results will be helpful for policy-makers and workplace regulators to assess program effectiveness for outsourced workers. PMID:27696988

The Balanced Budget Act (1997) and the supplyof nursing home subacute care.

PubMed

Qaseem, Amir; Weech-Maldonado, Robert; Mkanta, William

2007-01-01

This article examines the impact of the Medicare prospective payment system (PPS) on the supply of subacute care services by nursing homes. A quasi-experimental interrupted time-series design using Heckman's two-stage regression model is employed to test for changes before and after the implementation of Medicare PPS. Our findings suggest that the change in Medicare reimbursement from cost-based to PPS under the Balanced Budget Act of 1997 resulted in a decrease of 1.7 percent in the supply of subacute care beds by nursing homes. However, this was a one-time, short-term negative effect. The supply of nursing home subacute care remained stable in the long-term. Other environmental factors, such as Medicare hospital discharges, hospital-based subacute care, Medicare managed care penetration, availability of home health, and per capita income were associated with nursing home subacute care supply. Organizational-level factors, such as occupancy rate, RN staff mix, and Medicare payer mix were also predictors of nursing home subacute care supply.

Choice and Constraint in the Negotiation of the Grandparent Role: A Mixed-Methods Study.

PubMed

McGarrigle, Christine A; Timonen, Virpi; Layte, Richard

2018-01-01

Few studies have examined how the allocation and consequences of grandchild care vary across different socioeconomic groups. We analyze qualitative data alongside data from The Irish Longitudinal Study on Ageing (TILDA), in a convergent mixed-methods approach. Regression models examined characteristics associated with grandchild care, and the relationship between grandchild care and depressive symptoms and well-being. Qualitative data shed light on processes and choices that explain patterns of grandchild care provision. Tertiary-educated grandparents provided less intensive grandchild care compared with primary educated. Qualitative data indicated that this pattern stems from early boundary-drawing among higher educated grandparents while lower socioeconomic groups were constrained and less able to say no. Intensive grandchild care was associated with more depressive symptoms and lower well-being and was moderated by participation in social activities and level of education attainment. The effect of grandchild care on well-being of grandparents depends on whether it is provided by choice or obligation.

Choice and Constraint in the Negotiation of the Grandparent Role: A Mixed-Methods Study

PubMed Central

McGarrigle, Christine A.; Timonen, Virpi; Layte, Richard

2018-01-01

Few studies have examined how the allocation and consequences of grandchild care vary across different socioeconomic groups. We analyze qualitative data alongside data from The Irish Longitudinal Study on Ageing (TILDA), in a convergent mixed-methods approach. Regression models examined characteristics associated with grandchild care, and the relationship between grandchild care and depressive symptoms and well-being. Qualitative data shed light on processes and choices that explain patterns of grandchild care provision. Tertiary-educated grandparents provided less intensive grandchild care compared with primary educated. Qualitative data indicated that this pattern stems from early boundary-drawing among higher educated grandparents while lower socioeconomic groups were constrained and less able to say no. Intensive grandchild care was associated with more depressive symptoms and lower well-being and was moderated by participation in social activities and level of education attainment. The effect of grandchild care on well-being of grandparents depends on whether it is provided by choice or obligation. PMID:29372176

Small financial incentives increase smoking cessation in homeless smokers: a pilot study.

PubMed

Businelle, Michael S; Kendzor, Darla E; Kesh, Anshula; Cuate, Erica L; Poonawalla, Insiya B; Reitzel, Lorraine R; Okuyemi, Kolawole S; Wetter, David W

2014-03-01

Although over 70% of homeless individuals smoke, few studies have examined the effectiveness of smoking cessation interventions in this vulnerable population. The purpose of this pilot study was to compare the effectiveness of shelter-based smoking cessation clinic usual care (UC) to an adjunctive contingency management (CM) treatment that offered UC plus small financial incentives for smoking abstinence. Sixty-eight homeless individuals in Dallas, Texas (recruited in 2012) were assigned to UC (n=58) or UC plus financial incentives (CM; n=10) groups and were followed for 5 consecutive weeks (1 week pre-quit through 4 weeks post-quit). A generalized linear mixed model regression analysis was conducted to compare biochemically-verified abstinence rates between groups. An additional model examined the interaction between time and treatment group. The participants were primarily male (61.8%) and African American (58.8%), and were 49 years of age on average. There was a significant effect of treatment group on abstinence overall, and effects varied over time. Follow-up logistic regression analyses indicated that CM participants were significantly more likely than UC participants to be abstinent on the quit date (50% vs. 19% abstinent) and at 4 weeks post-quit (30% vs. 1.7% abstinent). Offering small financial incentives for smoking abstinence may be an effective way to facilitate smoking cessation in homeless individuals. Copyright © 2013 Elsevier Ltd. All rights reserved.

Proton-pump inhibitor use does not affect semen quality in subfertile men.

PubMed

Keihani, Sorena; Craig, James R; Zhang, Chong; Presson, Angela P; Myers, Jeremy B; Brant, William O; Aston, Kenneth I; Emery, Benjamin R; Jenkins, Timothy G; Carrell, Douglas T; Hotaling, James M

2018-01-01

Proton-pump inhibitors (PPIs) are among the most widely used drugs worldwide. PPI use has recently been linked to adverse changes in semen quality in healthy men; however, the effects of PPI use on semen parameters remain largely unknown specifically in cases with male factor infertility. We examined whether PPI use was associated with detrimental effects on semen parameters in a large population of subfertile men. We retrospectively reviewed data from 12 257 subfertile men who had visited our fertility clinic from 2003 to 2013. Patients who reported using any PPIs for >3 months before semen sample collection were included; 7698 subfertile men taking no medication served as controls. Data were gathered on patient age, medication use, and conventional semen parameters; patients taking any known spermatotoxic medication were excluded. Linear mixed-effect regression models were used to test the effect of PPI use on semen parameters adjusting for age. A total of 248 patients (258 samples) used PPIs for at least 3 months before semen collection. In regression models, PPI use (either as the only medication or when used in combination with other nonspermatotoxic medications) was not associated with statistically significant changes in semen parameters. To our knowledge, this is the largest study to compare PPI use with semen parameters in subfertile men. Using PPIs was not associated with detrimental effects on semen quality in this retrospective study.

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

Race-based job discrimination, disparities in job control, and their joint effects on health.

PubMed

Meyer, John D

2014-05-01

To examine disparities between job control scores in Black and White subjects and attempt to discern whether self-rated low job control in Blacks may arise from structural segregation into different jobs, or represents individual responses to race-based discrimination in hiring or promotion. Data from the National Survey of Midlife in the United States (MIDUS) were analyzed by mixed-effects linear regression and variance regression to determine the effects of grouping by occupation, and racial discrimination in hiring or promotion, on control scores from the Job Content Questionnaire in Black and White subjects. Path analyses were constructed to determine the mediating effect of discrimination on pathways from education and job control to self-rated health. Black subjects exhibited lower mean job control scores compared to Whites (mean score difference 2.26, P < 0.001) adjusted for age, sex, education, and income. This difference narrowed to 1.86 when adjusted for clustering by occupation, and was greatly reduced by conditioning on race-based discrimination (score difference 1.03, P = 0.12). Path analyses showed greater reported discrimination in Blacks with increasing education, and a stronger effect of job control on health in Black subjects. Individual racially-based discrimination appears a stronger determinant than structural segregation in reduced job control in Black workers, and may contribute to health disparities consequent on work. © 2013 Wiley Periodicals, Inc.

Combined effects of exposure to occupational noise and mixed organic solvents on blood pressure in car manufacturing company workers.

PubMed

Attarchi, Mirsaeed; Golabadi, Majid; Labbafinejad, Yasser; Mohammadi, Saber

2013-02-01

Recent studies suggest that occupational exposures such as noise and organic solvents may affect blood pressure. The aim of this study was to investigate interaction of noise and mixed organic solvents on blood pressure. Four hundred seventy-one workers of a car manufacturing plant were divided into four groups: group one or G1 workers exposed to noise and mixed organic solvents in the permitted limit or control group, G3 exposed to noise only, G2 exposed to solvents only, and G4 workers exposed to noise and mixed organic solvents at higher than the permitted limit or co-exposure group. Biological interaction of two variables on hypertension was calculated using the synergistic index. The workers of co-exposure group (G4), noise only group (G3), and solvents only group (G2) had significantly higher mean values of SBP and DBP than workers of control group (G1) or office workers (P < 0.05). Also logistic regression analysis showed a significant association between hypertension and exposure to noise and mixture of organic solvents. Odds ratio for hypertension in the co-exposure group and the noise only and solvents only exposed groups was 14.22, 9.43, and 4.38, respectively, compared to control group. In this study, the estimated synergism index was 1.11. Our results indicate that exposure to noise or a mixture of organic solvents may be associated with the prevalence of hypertension in car manufacturing company workers and co-exposure to noise and a mixture of solvents has an additive effect in this regard. Therefore appropriate preventive programs in these workers recommended. Copyright © 2012 Wiley Periodicals, Inc.

Cervical cancer cells (HeLa) response to photodynamic therapy using a zinc phthalocyanine photosensitizer.

PubMed

Hodgkinson, Natasha; Kruger, Cherie Ann; Mokwena, Mpho; Abrahamse, Heidi

2017-12-01

Cervical cancer is the most common gynecological malignancy worldwide, and the leading cause of cancer related deaths among females. Conventional treatment for early cervical cancer is radical hysterectomy. In locally advanced cancer the treatment of choice is concurrent chemo radiation. Although such treatment methods show promise, they do have adverse side effects. To minimize these effects, as well as prevent cancer re-occurrence, new treatment methods are being investigated. Photodynamic therapy (PDT) involves the selective uptake of a photosensitizer (PS) by cancer cells, illumination with light of an appropriate wavelength that triggers a photochemical reaction leading to the generation of reactive oxygen and subsequent tumor regression. The effect of PDT on a cervical cancer cell line (HeLa) was assessed by exposing cultured cells to a sulphonated zinc phthalocyanine PS (ZnPcS mix ) and irradiating the cells using a 673nm diode laser. The effects were measured using the Trypan blue viability assay, adenosine triphosphate assay (ATP) luminescence assay for proliferation, Lactate Dehydrogenase (LDH) membrane integrity cytotoxicity assay, and fluorescent microscopy to assess PS cellular localization and nuclear damage. Fluorescent microscopy revealed localization of the PS in the cytoplasm and perinuclear region of HeLa cells. PDT treated cellular responses showed dose dependent structural changes, with decreased cell viability and proliferation, as well as considerable membrane damage. Hoechst stained cells also revealed DNA damage in PDT treated cells. The final findings from this study suggest that ZnPcS mix is a promising PS for the PDT treatment of cervical cancer in vitro, where a significant 85% cellular cytotoxicity with only 25% cellular viability was noted in cells which received 1μM ZnPcS mix when an 8J/cm 2 fluence was applied. Copyright © 2017 Elsevier B.V. All rights reserved.

The effect of Medicaid nursing home reimbursement policy on Medicare hospice use in nursing homes.

PubMed

Miller, Susan C; Gozalo, Pedro; Lima, Julie C; Mor, Vincent

2011-09-01

To understand how changes in Medicaid nursing home (NH) reimbursement policy and rates affect a NH's approach to end-of-life care (ie, its use of hospice). This longitudinal study merged US NH decedents' (1999 to 2004) resident assessment data (MDS) with Part A claims data to determine the proportion of a NH's decedents using hospice. Freestanding NHs across the 48 contiguous US states were included. A NH-level analytic file was merged with NH survey (ie, OSCAR) and area resource file data, and with annual data on state Medicaid NH rates, case-mix reimbursement policies, and hospice certificate of need (CON). NH fixed-effect (within) regression analysis examined the effect of changing state policies, controlling for differing time trends in CON and case-mix states and for facility-level and county-level attributes. Models were stratified by urban/rural status. A $10 increase in the Medicaid rate resulted in a 0.41% [95% confidence interval (CI): 0.275, 0.553] increase in hospice use in urban NHs and a 0.37% decrease (95% CI: -0.676, -0.063) in rural NHs not adjacent to urban areas. There was a nonstatistically significant increase in rural NHs adjacent to urban areas. Introduction of case-mix reimbursement resulted in a 2.14% (95% CI: 1.388, 2.896) increase in hospice use in urban NHs, with comparable increases in rural NHs. This study supports and extends previous research by showing changes in Medicaid NH reimbursement policies affect a NH's approach to end-of-life care. It also shows how policy changes can have differing effects depending on a NH's urban/rural status.

Evaluating effects of developmental education for college students using a regression discontinuity design.

PubMed

Moss, Brian G; Yeaton, William H

2013-10-01

Annually, American colleges and universities provide developmental education (DE) to millions of underprepared students; however, evaluation estimates of DE benefits have been mixed. Using a prototypic exemplar of DE, our primary objective was to investigate the utility of a replicative evaluative framework for assessing program effectiveness. Within the context of the regression discontinuity (RD) design, this research examined the effectiveness of a DE program for five, sequential cohorts of first-time college students. Discontinuity estimates were generated for individual terms and cumulatively, across terms. Participants were 3,589 first-time community college students. DE program effects were measured by contrasting both college-level English grades and a dichotomous measure of pass/fail, for DE and non-DE students. Parametric and nonparametric estimates of overall effect were positive for continuous and dichotomous measures of achievement (grade and pass/fail). The variability of program effects over time was determined by tracking results within individual terms and cumulatively, across terms. Applying this replication strategy, DE's overall impact was modest (an effect size of approximately .20) but quite consistent, based on parametric and nonparametric estimation approaches. A meta-analysis of five RD results yielded virtually the same estimate as the overall, parametric findings. Subset analysis, though tentative, suggested that males benefited more than females, while academic gains were comparable for different ethnicities. The cumulative, within-study comparison, replication approach offers considerable potential for the evaluation of new and existing policies, particularly when effects are relatively small, as is often the case in applied settings.

A prospective survey of chiropractic student experiences with pediatric care and variability of case mix while on clinical placement in Rarotonga.

PubMed

Todd, Angela J; Carroll, Matthew T; Russell, David G; Mitchell, Eleanor K L

2017-03-01

To compare chiropractic students' perceptions of preparedness for practice before and after a clinical placement in Rarotonga and to report demographics from these experiences. The students completed deidentified pre- and postplacement surveys assessing pediatric practice preparedness. Students tallied the patient numbers, age, and chiropractic techniques used per visit for each day of clinic placement. On completion of the program, participating students (27/34, or 79% of the student cohort) did a postplacement survey on their perception of practice preparedness. Data were analyzed with the Spearman rho correlation, the Mann-Whitney U test, and regression analysis. There was an increase in perceived preparedness for pediatric practice, ranging from 24.1% of the student cohort at the start of the study to 82.1% following clinical placement in Rarotonga. The change in student preparedness to practice with children was positively correlated with the total number of children managed (r s = .05, p = .01) and the number of children managed who were under 10 years of age (r s = .60, p = .001). Multiple regression analysis demonstrated a medium positive effect for postprogram preparedness (F [4, 20] = 3.567, p = .024). Clinical outreach to Rarotonga provided a broad case mix of patients and a change in student perceptions of preparedness to practice with children, which was positively affected by the total number of children managed and the number of children managed who were under 10 years of age.

Commensurate Priors for Incorporating Historical Information in Clinical Trials Using General and Generalized Linear Models

PubMed Central

Hobbs, Brian P.; Sargent, Daniel J.; Carlin, Bradley P.

2014-01-01

Assessing between-study variability in the context of conventional random-effects meta-analysis is notoriously difficult when incorporating data from only a small number of historical studies. In order to borrow strength, historical and current data are often assumed to be fully homogeneous, but this can have drastic consequences for power and Type I error if the historical information is biased. In this paper, we propose empirical and fully Bayesian modifications of the commensurate prior model (Hobbs et al., 2011) extending Pocock (1976), and evaluate their frequentist and Bayesian properties for incorporating patient-level historical data using general and generalized linear mixed regression models. Our proposed commensurate prior models lead to preposterior admissible estimators that facilitate alternative bias-variance trade-offs than those offered by pre-existing methodologies for incorporating historical data from a small number of historical studies. We also provide a sample analysis of a colon cancer trial comparing time-to-disease progression using a Weibull regression model. PMID:24795786

Lithologic mapping of silicate rocks using TIMS

NASA Technical Reports Server (NTRS)

Gillespie, A. R.

1986-01-01

Common rock-forming minerals have thermal infrared spectral features that are measured in the laboratory to infer composition. An airborne Daedalus scanner (TIMS) that collects six channels of thermal infrared radiance data (8 to 12 microns), may be used to measure these same features for rock identification. Previously, false-color composite pictures made from channels 1, 3, and 5 and emittance spectra for small areas on these images were used to make lithologic maps. Central wavelength, standard deviation, and amplitude of normal curves regressed on the emittance spectra are related to compositional information for crystalline igneous silicate rocks. As expected, the central wavelength varies systematically with silica content and with modal quartz content. Standard deviation is less sensitive to compositional changes, but large values may result from mixed admixture of vegetation. Compression of the six TIMS channels to three image channels made from the regressed parameters may be effective in improving geologic mapping from TIMS data, and these synthetic images may form a basis for the remote assessment of rock composition.

Inferential Processing among Adequate and Struggling Adolescent Comprehenders and Relations to Reading Comprehension

PubMed Central

Barth, Amy E.; Barnes, Marcia; Francis, David J.; Vaughn, Sharon; York, Mary

2015-01-01

Separate mixed model analyses of variance (ANOVA) were conducted to examine the effect of textual distance on the accuracy and speed of text consistency judgments among adequate and struggling comprehenders across grades 6–12 (n = 1203). Multiple regressions examined whether accuracy in text consistency judgments uniquely accounted for variance in comprehension. Results suggest that there is considerable growth across the middle and high school years, particularly for adequate comprehenders in those text integration processes that maintain local coherence. Accuracy in text consistency judgments accounted for significant unique variance for passage-level, but not sentence-level comprehension, particularly for adequate comprehenders. PMID:26166946

Association Between Cardiovascular and Intraocular Pressure Changes in a 14-day 6 deg Head Down Tilt (HDT) Bed Rest Study: Possible Implications in Retinal Anatomy

NASA Technical Reports Server (NTRS)

Cromwell, R. L.; Zanello, S. B.; Yarbough, P. O.; Ploutz-Snyder, R.; Taibbi, G.; Brewer, J. L.; Vizzeri, G.

2013-01-01

Mean IOP significantly increased while at 6deg HDT and returned towards pre-bed rest values upon leaving bed rest. While mean IOP increased during bed rest, it remained within the normal limits for subject safety. A diuretic shift and cardiovascular deconditioning occurs during in-bed rest, as expected. There was no demonstrable correlation between the largest change in IOP (pre/post) and cardiovascular measure changes (pre/post). Additional mixed effects linear regression modeling may reveal some subclinical physiological changes that might assist in describing the VIIP syndrome pathophysiology.

Gas detection by correlation spectroscopy employing a multimode diode laser.

PubMed

Lou, Xiutao; Somesfalean, Gabriel; Zhang, Zhiguo

2008-05-01

A gas sensor based on the gas-correlation technique has been developed using a multimode diode laser (MDL) in a dual-beam detection scheme. Measurement of CO(2) mixed with CO as an interfering gas is successfully demonstrated using a 1570 nm tunable MDL. Despite overlapping absorption spectra and occasional mode hops, the interfering signals can be effectively excluded by a statistical procedure including correlation analysis and outlier identification. The gas concentration is retrieved from several pair-correlated signals by a linear-regression scheme, yielding a reliable and accurate measurement. This demonstrates the utility of the unsophisticated MDLs as novel light sources for gas detection applications.

Constrained inference in mixed-effects models for longitudinal data with application to hearing loss.

PubMed

Davidov, Ori; Rosen, Sophia

2011-04-01

In medical studies, endpoints are often measured for each patient longitudinally. The mixed-effects model has been a useful tool for the analysis of such data. There are situations in which the parameters of the model are subject to some restrictions or constraints. For example, in hearing loss studies, we expect hearing to deteriorate with time. This means that hearing thresholds which reflect hearing acuity will, on average, increase over time. Therefore, the regression coefficients associated with the mean effect of time on hearing ability will be constrained. Such constraints should be accounted for in the analysis. We propose maximum likelihood estimation procedures, based on the expectation-conditional maximization either algorithm, to estimate the parameters of the model while accounting for the constraints on them. The proposed methods improve, in terms of mean square error, on the unconstrained estimators. In some settings, the improvement may be substantial. Hypotheses testing procedures that incorporate the constraints are developed. Specifically, likelihood ratio, Wald, and score tests are proposed and investigated. Their empirical significance levels and power are studied using simulations. It is shown that incorporating the constraints improves the mean squared error of the estimates and the power of the tests. These improvements may be substantial. The methodology is used to analyze a hearing loss study.

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

Regression calibration for models with two predictor variables measured with error and their interaction, using instrumental variables and longitudinal data.

PubMed

Strand, Matthew; Sillau, Stefan; Grunwald, Gary K; Rabinovitch, Nathan

2014-02-10

Regression calibration provides a way to obtain unbiased estimators of fixed effects in regression models when one or more predictors are measured with error. Recent development of measurement error methods has focused on models that include interaction terms between measured-with-error predictors, and separately, methods for estimation in models that account for correlated data. In this work, we derive explicit and novel forms of regression calibration estimators and associated asymptotic variances for longitudinal models that include interaction terms, when data from instrumental and unbiased surrogate variables are available but not the actual predictors of interest. The longitudinal data are fit using linear mixed models that contain random intercepts and account for serial correlation and unequally spaced observations. The motivating application involves a longitudinal study of exposure to two pollutants (predictors) - outdoor fine particulate matter and cigarette smoke - and their association in interactive form with levels of a biomarker of inflammation, leukotriene E4 (LTE 4 , outcome) in asthmatic children. Because the exposure concentrations could not be directly observed, we used measurements from a fixed outdoor monitor and urinary cotinine concentrations as instrumental variables, and we used concentrations of fine ambient particulate matter and cigarette smoke measured with error by personal monitors as unbiased surrogate variables. We applied the derived regression calibration methods to estimate coefficients of the unobserved predictors and their interaction, allowing for direct comparison of toxicity of the different pollutants. We used simulations to verify accuracy of inferential methods based on asymptotic theory. Copyright © 2013 John Wiley & Sons, Ltd.

Study of non-Hodgkin's lymphoma mortality associated with industrial pollution in Spain, using Poisson models

PubMed Central

Ramis, Rebeca; Vidal, Enrique; García-Pérez, Javier; Lope, Virginia; Aragonés, Nuria; Pérez-Gómez, Beatriz; Pollán, Marina; López-Abente, Gonzalo

2009-01-01

Background Non-Hodgkin's lymphomas (NHLs) have been linked to proximity to industrial areas, but evidence regarding the health risk posed by residence near pollutant industries is very limited. The European Pollutant Emission Register (EPER) is a public register that furnishes valuable information on industries that release pollutants to air and water, along with their geographical location. This study sought to explore the relationship between NHL mortality in small areas in Spain and environmental exposure to pollutant emissions from EPER-registered industries, using three Poisson-regression-based mathematical models. Methods Observed cases were drawn from mortality registries in Spain for the period 1994–2003. Industries were grouped into the following sectors: energy; metal; mineral; organic chemicals; waste; paper; food; and use of solvents. Populations having an industry within a radius of 1, 1.5, or 2 kilometres from the municipal centroid were deemed to be exposed. Municipalities outside those radii were considered as reference populations. The relative risks (RRs) associated with proximity to pollutant industries were estimated using the following methods: Poisson Regression; mixed Poisson model with random provincial effect; and spatial autoregressive modelling (BYM model). Results Only proximity of paper industries to population centres (>2 km) could be associated with a greater risk of NHL mortality (mixed model: RR:1.24, 95% CI:1.09–1.42; BYM model: RR:1.21, 95% CI:1.01–1.45; Poisson model: RR:1.16, 95% CI:1.06–1.27). Spatial models yielded higher estimates. Conclusion The reported association between exposure to air pollution from the paper, pulp and board industry and NHL mortality is independent of the model used. Inclusion of spatial random effects terms in the risk estimate improves the study of associations between environmental exposures and mortality. The EPER could be of great utility when studying the effects of industrial pollution on the health of the population. PMID:19159450

Exposure to lithium through drinking water and calcium homeostasis during pregnancy: A longitudinal study.

PubMed

Harari, Florencia; Åkesson, Agneta; Casimiro, Esperanza; Lu, Ying; Vahter, Marie

2016-05-01

There is increasing evidence of adverse health effects due to elevated lithium exposure through drinking water but the impact on calcium homeostasis is unknown. This study aimed at elucidating if lithium exposure through drinking water during pregnancy may impair the maternal calcium homeostasis. In a population-based mother-child cohort in the Argentinean Andes (n=178), with elevated lithium concentrations in the drinking water (5-1660μg/L), blood lithium concentrations (correlating significantly with lithium in water, urine and plasma) were measured repeatedly during pregnancy by inductively coupled plasma mass spectrometry and used as exposure biomarker. Markers of calcium homeostasis included: plasma 25-hydroxyvitamin D3, serum parathyroid hormone (PTH), and calcium, phosphorus and magnesium concentrations in serum and urine. The median maternal blood lithium concentration was 25μg/L (range 1.9-145). In multivariable-adjusted mixed-effects linear regression models, blood lithium was inversely associated with 25-hydroxyvitamin D3 (-6.1nmol/L [95%CI -9.5; -2.6] for a 25μg/L increment in blood lithium). The estimate increased markedly with increasing percentiles of 25-hydroxyvitamin D3. In multivariable-adjusted mixed-effects logistic regression models, the odds ratio of having 25-hydroxyvitamin D3<30nmol/L (19% of the women) was 4.6 (95%CI 1.1; 19.3) for a 25μg/L increment in blood lithium. Blood lithium was also positively associated with serum magnesium, but not with serum calcium and PTH, and inversely associated with urinary calcium and magnesium. In conclusion, our study suggests that lithium exposure through drinking water during pregnancy may impair the calcium homeostasis, particularly vitamin D. The results reinforce the need for better control of lithium in drinking water, including bottled water. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models

NASA Astrophysics Data System (ADS)

Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo

2016-11-01

The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.

Freedom Solo Versus Trifecta Bioprotheses: Clinical and Hemodynamic Evaluation after Propensity Score Matching.

PubMed

J Cerqueira, Rui; Melo, Renata; Moreira, Soraia; A Saraiva, Francisca; Andrade, Marta; Salgueiro, Elson; Almeida, Jorge; J Amorim, Mário; Pinho, Paulo; Lourenço, André; F Leite-Moreira, Adelino

2017-01-01

To compare stentless Freedom Solo and stented Trifecta aortic bioprostheses regarding hemodynamic profile, left ventricular mass regression, early and late postoperative outcomes and survival. Longitudinal cohort study of consecutive patients undergoing aortic valve replacement (from 2009 to 2016) with either Freedom Solo or Trifecta at one centre. Local databases and national records were queried. Postoperative echocardiography (3-6 months) was obtained for hemodynamic profile (mean transprosthetic gradient and effective orifice area) and left ventricle mass determination. After propensity score matching (21 covariates), Kaplan-Meier analysis and cumulative incidence analysis were performed for survival and combined outcome of structural valve deterioration and endocarditis, respectively. Hemodynamics and left ventricle mass regression were assessed by a mixed- -effects model including propensity score as a covariate. From a total sample of 397 Freedom Solo and 525 Trifecta patients with a median follow-up time of 4.0 (2.2- 6.0) and 2.4 (1.4-3.7) years, respectively, a matched sample of 329 pairs was obtained. Well-balanced matched groups showed no difference in survival (hazard ratio=1.04, 95% confidence interval=0.69-1.56) or cumulative hazards of combined outcome (subhazard ratio=0.54, 95% confidence interval=0.21-1.39). Although Trifecta showed improved hemodynamic profile compared to Freedom Solo, no differences were found in left ventricle mass regression. Trifecta has a slightly improved hemodynamic profile compared to Freedom Solo but this does not translate into differences in the extent of mass regression, postoperative outcomes or survival, which were good and comparable for both bioprostheses. Long-term follow-up is needed for comparisons with older models of bioprostheses.

Peer victimization predicts psychological symptoms beyond the effects of child maltreatment.

PubMed

Sansen, Lisa Margareta; Iffland, Benjamin; Neuner, Frank

2014-12-30

Experiences of peer victimization have been repeatedly associated with psychological symptoms and disorders. However, as peer victimization is correlated with child maltreatment occurring within the family, it remains unclear whether the pathological effect of peer victimization is an artifact that can be attributed to previous aversive events. To separate the effects of peer victimization from child maltreatment, we studied both event types as well as psychological symptoms in a mixed clinical sample of ambulant and psychiatric patients (N=168), a self-selected community sample recruited through the internet (N=995), and a student sample (N=272). Hierarchical regression analyses showed that, after controlling for child maltreatment, peer victimization accounted for an incremental proportion of the variance of different symptom dimensions in each sample. These results indicate that peer victimization is an independent predictor of psychopathology.

Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power.

PubMed

Fu, Qiang; George, Linda K

2015-07-01

Previous studies have widely reported that the association between socioeconomic status (SES) and childhood overweight and obesity in China is significant and positive, which lends little support to the fundamental-cause perspective. Using multiple waves (1997, 2000, 2004 and 2006) of the China Health and Nutrition Survey (CHNS) (N = 2,556, 2,063, 1,431 and 1,242, respectively) and continuous BMI cut-points obtained from a polynomial method, (mixed-effect) logistic regression analyses show that parental state-sector employment, an important, yet overlooked, indicator of political power during the market transformation has changed from a risk factor for childhood overweight/obesity in 1997 to a protective factor for childhood overweight/obesity in 2006. Results from quantile regression analyses generate the same conclusions and demonstrate that the protective effect of parental state sector employment at high percentiles of BMI is robust under different estimation strategies. By bridging the fundamental causes perspective and theories of market transformation, this research not only documents the effect of political power on childhood overweight/obesity but also calls for the use of multifaceted, culturally-relevant stratification measures in testing the fundamental cause perspective across time and space. © 2015 Foundation for the Sociology of Health & Illness.

Do social relations buffer the effect of neighborhood deprivation on health-related quality of life? Results from the LifeLines Cohort Study.

PubMed

Klijs, Bart; Mendes de Leon, Carlos F; Kibele, Eva U B; Smidt, Nynke

2017-03-01

We investigated whether social relations buffer the effect of neighborhood deprivation on mental and physical health-related quality of life. Baseline data from the LifeLines Cohort Study (N=68,111) and a neighborhood deprivation index were used to perform mixed effect linear regression analyses. Results showed that fewer personal contacts (b, 95%CI: -0.88(-1.08;-0.67)) and lower social need fulfillment (-4.52(-4.67;-4.36)) are associated with lower mental health-related quality of life. Higher neighborhood deprivation was also associated with lower mental health related quality of life (-0.18(-0.24;-0.11)), but only for those with few personal contacts or low social need fulfillment. Our results suggest that social relations buffer the effect of neighborhood deprivation on mental health-related quality of life. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Longitudinal Effects of Adolescent Volunteering on Secondary School Completion and Adult Volunteering

PubMed Central

Moorfoot, Nicholas; Leung, Rachel K.; Toumbourou, John W.; Catalano, Richard F.

2016-01-01

This study explores the longitudinal effect of adolescent volunteering behaviour on young adult volunteering and the completion of secondary school. Utilising data from the Australian sample of the International Youth Development Study, frequency of volunteering in Grade 9 (mean age = 15 years) and in young adulthood (mean age = 21 years), and completion of secondary school were measured. Mixed effect logistic regression analyses revealed that adolescent volunteering was associated with an increased likelihood of volunteering in young adulthood (Odds Ratio [OR] 1.29; 95% Confidence Interval [CI] 1.20 – 1.39; N = 2,648) and of Grade 12 completion (OR 1.14; CI 1.03 – 1.28; N = 2,648), after controlling for family socioeconomic status and adolescent school adjustment. These findings suggest that adolescent volunteering may lead to further involvement in young adult volunteering and have a positive effect on school completion. PMID:27458548

The Longitudinal Effects of Adolescent Volunteering on Secondary School Completion and Adult Volunteering.

PubMed

Moorfoot, Nicholas; Leung, Rachel K; Toumbourou, John W; Catalano, Richard F

This study explores the longitudinal effect of adolescent volunteering behaviour on young adult volunteering and the completion of secondary school. Utilising data from the Australian sample of the International Youth Development Study, frequency of volunteering in Grade 9 (mean age = 15 years) and in young adulthood (mean age = 21 years), and completion of secondary school were measured. Mixed effect logistic regression analyses revealed that adolescent volunteering was associated with an increased likelihood of volunteering in young adulthood (Odds Ratio [OR] 1.29; 95% Confidence Interval [CI] 1.20 - 1.39; N = 2,648) and of Grade 12 completion (OR 1.14; CI 1.03 - 1.28; N = 2,648), after controlling for family socioeconomic status and adolescent school adjustment. These findings suggest that adolescent volunteering may lead to further involvement in young adult volunteering and have a positive effect on school completion.

Analysing the effect of multiple sclerosis on vitamin D related biochemical markers of bone remodelling.

PubMed

McKenna, Malachi J; Murray, Barbara; Lonergan, Roisin; Segurado, Ricardo; Tubridy, Niall; Kilbane, Mark T

2018-03-01

The Irish population is at risk of vitamin D deficiency during the winter months, but the secular trend over the past 40 years is for marked improvement. Multiple sclerosis (MS) is common in Ireland with a latitudinal pattern favouring highest incidence in northern regions; MS is linked strongly with vitamin D status as a causal factor. We sought firstly to study the relationship between vitamin D status and vitamin D-related bone biochemistry, and secondly to evaluate if MS had an independent effect on vitamin D related markers of bone remodelling. Using a case-control design of 165 pairs (MS patient and matched control) residing in three different geographic regions during winter months, we measured serum 25-hydroxyvitamin D (25OHD), parathyroid hormone (PTH), C-terminal telopeptide of type I collagen (CTX) and total procollagen type I amino-terminal propeptide (PINP). Given the paired case-control design, associations were explored using mixed-effects linear regression analysis with the patient-control pair as a random effect and after log transformation of 25OHD. A two-way interaction effect was tested for vitamin D status (25OHD <30nmol/L) and the presence of MS on PTH, CTX, and PINP. In the total group, just over one-third (34.5%) had 25OHD <30nmol/L. PTH was elevated in 7.6%. CTX was not elevated in any case, and PINP was elevated in 4.5%. On mixed-effects linear regression analysis after adjusting for confounders (age, sex, renal function, and serum albumin), we demonstrated the principal determinant of 25OHD was geographical location (p<0.001), of PTH was 25OHD (p<0.001), of CTX was PTH (p<0.001), and of PINP was PTH (p<0.001). MS did not have an independent effect on PTH (p=0.921), CTX (p=0.912), or PINP (p=0.495). As regards an interaction effect, the presence of MS and 25OHD <30nmol/L was not significant but tended towards having lower PTH (p=0.207). In conclusion, in Ireland in winter only a minority had any abnormality in the secondary indices of vitamin D deficiency, and MS had no independent effect on parathyroid status or bone remodelling activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Little Schmidy Pediatric Hospital Fall Risk Assessment Index: A diagnostic accuracy study.

PubMed

Franck, Linda S; Gay, Caryl L; Cooper, Bruce; Ezrre, Suzanne; Murphy, Barbette; Chan, June Shu-Ling; Buick, Maureen; Meer, Carrie R

2017-03-01

Falls are among the most common potentially preventable adverse events. Current pediatric falls risk assessment methods have poor precision and accuracy. To evaluate an inpatient pediatric fall risk assessment index, known as the Little Schmidy, and describe characteristics of pediatric falls. Retrospective case control and descriptive study. The dataset included 114 reported falls and 151,678 Little Schmidy scores documented in medical records during the 5-year study period (2007-2011). Pediatric medical and surgical inpatient units of an academic medical center in the western United States. Pediatric hospital inpatients <25 years of age. Nurses used the 5-item, 7-point Little Schmidy to assess fall risk each day and night shift throughout the patient's hospitalization. Conditional fixed-effects logistic regressions were used to examine predictive relationships between Little Schmidy scores (at admission, highest prior to fall, and just prior to fall) and the patient's fall status (fell or not). The sensitivity and specificity of different cut-off scores were explored. Associations between Little Schmidy scores and patient and hospitalization factors were examined using multilevel mixed-effects logistic regression and multilevel mixed-effects ordinal logistic regression. Little Schmidy scores were significantly associated with pediatric falls (p<0.005). Maximal performance was achieved with a 4-item, 4-point, Little Schmidy index (LS4) using a cut-off score of 1 to indicate fall risk with sensitivity of 79% and specificity of 49%. Patients with an LS4 score ≥1 were 4 times more likely to fall before the next assessment than patients with a score of 0. LS4 scores indicative of fall risk were associated with age ≥5 years, neurological diagnosis, multiple hospitalizations, and night shift, but not with sex, length of hospital stay, or hospital unit. Of the 114 reported falls, 64% involved a male patient, nearly one third (32%) involved adolescents (13-17 years), most resulted in no (59%) or mild (36%) injury, and most (54%) were related to diagnosis or clinical characteristics. For 60% of the falls, fall precautions had been implemented prior to the fall. The revised 4-item Little Schmidy, the LS4, predicts pediatric falls when administered every day and night shift, but identifies most patients (65%) as being at risk for fall. Strategies for improving the accuracy and efficiency of the assessments are proposed. Further research is needed to develop more effective pediatric fall prevention strategies tailored to patient's age, diagnosis, and time of day. Copyright © 2017 Elsevier Ltd. All rights reserved.

Preventing youth access to alcohol: outcomes from a multi-community time-series trial*.

PubMed

Wagenaar, Alexander C; Toomey, Traci L; Erickson, Darin J

2005-03-01

AIMS/INTERVENTION: The Complying with the Minimum Drinking Age project (CMDA) is a community trial designed to test effects of two interventions designed to reduce alcohol sales to minors: (1) training for management of retail alcohol establishments and (2) enforcement checks of alcohol establishments. CMDA is a multi-community time-series quasi-experimental trial with a nested cohort design. CMDA was implemented in 20 cities in four geographic areas in the US Midwest. The core outcome, propensity for alcohol sales to minors, was directly tested with research staff who attempted to purchase alcohol without showing age identification using a standardized protocol in 602 on-premise and 340 off-premise alcohol establishments. Data were collected every other week in all communities over 4 years. Mixed-model regression and Box-Jenkins time-series analyses were used to assess short- and long-term establishment-specific and general community-level effects of the two interventions. Effects of the training intervention were mixed. Specific deterrent effects were observed for enforcement checks, with an immediate 17% reduction in likelihood of sales to minors. These effects decayed entirely within 3 months in off-premise establishments and to an 8.2% reduction in on-premise establishments. Enforcement checks prevent alcohol sales to minors. At the intensity levels tested, enforcement primarily affected specific establishments checked, with limited diffusion to the whole community. Finally, most of the enforcement effect decayed within 3 months, suggesting that a regular schedule of enforcement is necessary to maintain deterrence.

Determinants of plasma triglyceride levels in a multiethnic working class Caribbean population: effect of ethnicity, diet and obesity.

PubMed

Ramdath, Dinesh Dan; Singh, Shamjeet; Hilaire, Debbie G; Nayak, B Shivananda

2013-01-01

Objective of the study is to identify the predictors of plasma triglycerides. A stratified random sample of university staff categories underwent measurements of anthropometry, blood pressure, and fasting blood glucose, insulin, lipids, CRP and homocysteine. Dietary intakes were assessed using duplicate 24h recalls. HOMA-IR was calculated. Stepwise, multivariate regression analysis was performed with TAG as the dependent variable. The sample (n=251) was 55% females with a mean age of 44.9±9.7 years. African ancestry comprised 43%, followed South Asian 30% and mixed ethnicity 27%. Prevalence of obesity was 19.4%, insulin resistance 22.7% and metabolic syndrome 21.6%. Males had significantly higher (p<0.01) triglycerides and VLDL and lower HDL than females. Africans had significantly lower triglycerides and cholesterol than South Asians and Mix. Triglycerides were significantly (p<0.01) correlated with glucose, cholesterol, insulin, CRP, systolic, diastolic blood pressure, WC, BMI, age and components of MS. Glucose, cholesterol, insulin and total energy intake predicted TAG, to varying extents, in all participants (R(2)=45.1%), males (R(2)=40.3%), females (R(2)=56.0%), Africans (R(2)=35.0%), TSA (R(2)=31.5%) and mix (R(2)=51.0%). Africans have lower triglycerides and cholesterol than South Asians and mix. Major predictors of triglycerides were fasting glucose and cholesterol independent of gender and ethnicity. Copyright © 2013 Diabetes India. All rights reserved.

Effects of Nursing Home Residency on Diabetes Care in Individuals with Dementia: An Explorative Analysis Based on German Claims Data

PubMed Central

Schwarzkopf, Larissa; Holle, Rolf; Schunk, Michaela

2017-01-01

Aims This claims data-based study compares the intensity of diabetes care in community dwellers and nursing home residents with dementia. Methods Delivery of diabetes-related medical examinations (DRMEs) was compared via logistic regression in 1,604 community dwellers and 1,010 nursing home residents with dementia. The intra-individual effect of nursing home transfer was evaluated within mixed models. Results Delivery of DRMEs decreases with increasing care dependency, with more community-living individuals receiving DRMEs. Moreover, DRME provision decreases after nursing home transfer. Conclusion Dementia patients receive fewer DRMEs than recommended, especially in cases of higher care dependency and particularly in nursing homes. This suggests lacking awareness regarding the specific challenges of combined diabetes and dementia care. PMID:28413415

Flow of nanofluid past a Riga plate

NASA Astrophysics Data System (ADS)

Ahmad, Adeel; Asghar, Saleem; Afzal, Sumaira

2016-03-01

This paper studies the mixed convection boundary layer flow of a nanofluid past a vertical Riga plate in the presence of strong suction. The mathematical model incorporates the Brownian motion and thermophoresis effects due to nanofluid and the Grinberg-term for the wall parallel Lorentz force due to Riga plate. The analytical solution of the problem is presented using the perturbation method for small Brownian and thermophoresis diffusion parameters. The numerical solution is also presented to ensure the reliability of the asymptotic method. The comparison of the two solutions shows an excellent agreement. The correlation expressions for skin friction, Nusselt number and Sherwood number are developed by performing linear regression on the obtained numerical data. The effects of nanofluid and the Lorentz force due to Riga plate, on the skin friction are discussed.

The Energy Content and Composition of Meals Consumed after an Overnight Fast and Their Effects on Diet Induced Thermogenesis: A Systematic Review, Meta-Analyses and Meta-Regressions

PubMed Central

Quatela, Angelica; Callister, Robin; Patterson, Amanda; MacDonald-Wicks, Lesley

2016-01-01

This systematic review investigated the effects of differing energy intakes, macronutrient compositions, and eating patterns of meals consumed after an overnight fast on Diet Induced Thermogenesis (DIT). The initial search identified 2482 records; 26 papers remained once duplicates were removed and inclusion criteria were applied. Studies (n = 27) in the analyses were randomized crossover designs comparing the effects of two or more eating events on DIT. Higher energy intake increased DIT; in a mixed model meta-regression, for every 100 kJ increase in energy intake, DIT increased by 1.1 kJ/h (p < 0.001). Meals with a high protein or carbohydrate content had a higher DIT than high fat, although this effect was not always significant. Meals with medium chain triglycerides had a significantly higher DIT than long chain triglycerides (meta-analysis, p = 0.002). Consuming the same meal as a single bolus eating event compared to multiple small meals or snacks was associated with a significantly higher DIT (meta-analysis, p = 0.02). Unclear or inconsistent findings were found by comparing the consumption of meals quickly or slowly, and palatability was not significantly associated with DIT. These findings indicate that the magnitude of the increase in DIT is influenced by the energy intake, macronutrient composition, and eating pattern of the meal. PMID:27792142

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Regression analysis of mixed panel count data with dependent terminal events.

PubMed

Yu, Guanglei; Zhu, Liang; Li, Yang; Sun, Jianguo; Robison, Leslie L

2017-05-10

Event history studies are commonly conducted in many fields, and a great deal of literature has been established for the analysis of the two types of data commonly arising from these studies: recurrent event data and panel count data. The former arises if all study subjects are followed continuously, while the latter means that each study subject is observed only at discrete time points. In reality, a third type of data, a mixture of the two types of the data earlier, may occur and furthermore, as with the first two types of the data, there may exist a dependent terminal event, which may preclude the occurrences of recurrent events of interest. This paper discusses regression analysis of mixed recurrent event and panel count data in the presence of a terminal event and an estimating equation-based approach is proposed for estimation of regression parameters of interest. In addition, the asymptotic properties of the proposed estimator are established, and a simulation study conducted to assess the finite-sample performance of the proposed method suggests that it works well in practical situations. Finally, the methodology is applied to a childhood cancer study that motivated this study. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Application of seemingly unrelated regression in medical data with intermittently observed time-dependent covariates.

PubMed

Keshavarzi, Sareh; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Pakfetrat, Maryam

2012-01-01

BACKGROUND. In many studies with longitudinal data, time-dependent covariates can only be measured intermittently (not at all observation times), and this presents difficulties for standard statistical analyses. This situation is common in medical studies, and methods that deal with this challenge would be useful. METHODS. In this study, we performed the seemingly unrelated regression (SUR) based models, with respect to each observation time in longitudinal data with intermittently observed time-dependent covariates and further compared these models with mixed-effect regression models (MRMs) under three classic imputation procedures. Simulation studies were performed to compare the sample size properties of the estimated coefficients for different modeling choices. RESULTS. In general, the proposed models in the presence of intermittently observed time-dependent covariates showed a good performance. However, when we considered only the observed values of the covariate without any imputations, the resulted biases were greater. The performances of the proposed SUR-based models in comparison with MRM using classic imputation methods were nearly similar with approximately equal amounts of bias and MSE. CONCLUSION. The simulation study suggests that the SUR-based models work as efficiently as MRM in the case of intermittently observed time-dependent covariates. Thus, it can be used as an alternative to MRM.

Alternative High School Students: Prevalence and Correlates of Overweight

ERIC Educational Resources Information Center

Kubik, Martha Y.; Davey, Cynthia; Fulkerson, Jayne A.; Sirard, John; Story, Mary; Arcan, Chrisa

2009-01-01

Objective: To determine prevalence and correlates of overweight among adolescents attending alternative high schools (AHS). Methods: AHS students (n=145) from 6 schools completed surveys and anthropometric measures. Cross-sectional associations were assessed using mixed model multivariate logistic regression. Results: Among students, 42% were…

Safety analysis of urban signalized intersections under mixed traffic.

PubMed

S, Anjana; M V L R, Anjaneyulu

2015-02-01

This study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models. Hierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections. The study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study. As a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis and generation of groundwater concentration time series

NASA Astrophysics Data System (ADS)

Crăciun, Maria; Vamoş, Călin; Suciu, Nicolae

2018-01-01

Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in probability density function approaches. The well-known interaction by exchange with the mean mixing model is a special case consisting of a linear regression with constant coefficients.

Does the presence and mix of destinations influence walking and physical activity?

PubMed

King, Tania Louise; Bentley, Rebecca Jodie; Thornton, Lukar Ezra; Kavanagh, Anne Marie

2015-09-17

Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how specific destinations are related to activity. This study examined associations between types and mix of destinations and both walking frequency and physical activity. The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Using geographic information systems, seven types of destinations were examined within three network buffers (400 meters (m), 800 m and 1200 m) of respondents' homes. Multilevel logistic regression was used to estimate effects of each destination type separately, as well as destination mix (variety) on: 1) likelihood of walking for at least 10 min ≥ 4/week; 2) likelihood of being sufficiently physically active. All models were adjusted for potential confounders. All destination types were positively associated with walking frequency, and physical activity sufficiency at 1200 m. For the 800 m buffer: all destinations except transport stops and sports facilities were significantly associated with physical activity, while all except sports facilities were associated with walking frequency; at 400 m, café/takeaway food stores and transport stops were associated with walking frequency and physical activity sufficiency, and sports facilities were also associated with walking frequency. Strongest associations for both outcomes were observed for community resources and small food stores at both 800 m and 1200 m. For all buffer distances: greater mix was associated with greater walking frequency. Inclusion of walking in physical activity models led to attenuation of associations. The results of this analysis indicate that there is an association between destinations and both walking frequency and physical activity sufficiency, and that this relationship varies by destination type. It is also clear that greater mix of destinations positively predicts walking frequency and physical activity sufficiency.

Impact of Case Mix Severity on Quality Improvement in a Patient-centered Medical Home (PCMH) in the Maryland Multi-Payor Program.

PubMed

Khanna, Niharika; Shaya, Fadia T; Chirikov, Viktor V; Sharp, David; Steffen, Ben

2016-01-01

We present data on quality of care (QC) improvement in 35 of 45 National Quality Forum metrics reported annually by 52 primary care practices recognized as patient-centered medical homes (PCMHs) that participated in the Maryland Multi-Payor Program from 2011 to 2013. We assigned QC metrics to (1) chronic, (2) preventive, and (3) mental health care domains. The study used a panel data design with no control group. Using longitudinal fixed-effects regressions, we modeled QC and case mix severity in a PCMH. Overall, 35 of 45 quality metrics reported by 52 PCMHs demonstrated improvement over 3 years, and case mix severity did not affect the achievement of quality improvement. From 2011 to 2012, QC increased by 0.14 (P < .01) for chronic, 0.15 (P < .01) for preventive, and 0.34 (P < .01) for mental health care domains; from 2012 to 2013 these domains increased by 0.03 (P = .06), 0.04 (P = .05), and 0.07 (P = .12), respectively. In univariate analyses, lower National Commission on Quality Assurance PCMH level was associated with higher QC for the mental health care domain, whereas case mix severity did not correlate with QC. In multivariate analyses, higher QC correlated with larger practices, greater proportion of older patients, and readmission visits. Rural practices had higher proportions of Medicaid patients, lower QC, and higher QC improvement in interaction analyses with time. The gains in QC in the chronic disease domain, the preventive care domain, and, most significantly, the mental health care domain were observed over time regardless of patient case mix severity. QC improvement was generally not modified by practice characteristics, except for rurality. © Copyright 2016 by the American Board of Family Medicine.

Water mass mixing: The dominant control on the zinc distribution in the North Atlantic Ocean

NASA Astrophysics Data System (ADS)

Roshan, Saeed; Wu, Jingfeng

2015-07-01

Dissolved zinc (dZn) concentration was determined in the North Atlantic during the U.S. GEOTRACES 2010 and 2011 cruise (GOETRACES GA03). A relatively poor linear correlation (R2 = 0.756) was observed between dZn and silicic acid (Si), the slope of which was 0.0577 nM/µmol/kg. We attribute the relatively poor dZn-Si correlation to the following processes: (a) differential regeneration of zinc relative to silicic acid, (b) mixing of multiple water masses that have different Zn/Si, and (c) zinc sources such as sedimentary or hydrothermal. To quantitatively distinguish these possibilities, we use the results of Optimum Multi-Parameter Water Mass Analysis by Jenkins et al. (2015) to model the zinc distribution below 500 m. We hypothesized two scenarios: conservative mixing and regenerative mixing. The first scenario (conservative) could be modeled to results in a correlation with observations with a R2 = 0.846. In the second scenario, we took a Si-related regeneration into account, which could model the observations with a R2 = 0.867. Through this regenerative mixing scenario, we estimated a Zn/Si = 0.0548 nM/µmol/kg that may be more realistic than linear regression slope due to accounting for process b. However, this did not improve the model substantially (R2 = 0.867 versus0.846), which may indicate the insignificant effect of remineralization on the zinc distribution in this region. The relative weakness in the model-observation correlation (R2~0.85 for both scenarios) implies that processes (a) and (c) may be plausible. Furthermore, dZn in the upper 500 m exhibited a very poor correlation with apparent oxygen utilization, suggesting a minimal role for the organic matter-associated remineralization process.

Spatial Characteristics of Small Green Spaces' Mitigating Effects on Microscopic Urban Heat Islands

NASA Astrophysics Data System (ADS)

Park, J.; Lee, D. K.; Jeong, W.; Kim, J. H.; Huh, K. Y.

2015-12-01

The purpose of the study is to find small greens' disposition, types and sizes to reduce air temperature effectively in urban blocks. The research sites were six high developed blocks in Seoul, Korea. Air temperature was measured with mobile loggers in clear daytime during summer, from August to September, at screen level. Also the measurement repeated over three times a day during three days by walking and circulating around the experimental blocks and the control blocks at the same time. By analyzing spatial characteristics, the averaged air temperatures were classified with three spaces, sunny spaces, building-shaded spaces and small green spaces by using Kruskal-Wallis Test; and small green spaces in 6 blocks were classified into their outward forms, polygonal or linear and single or mixed. The polygonal and mixed types of small green spaces mitigated averaged air temperature of each block which they belonged with a simple linear regression model with adjusted R2 = 0.90**. As the area and volume of these types increased, the effect of air temperature reduction (ΔT; Air temperature difference between sunny space and green space in a block) also increased in a linear relationship. The experimental range of this research is 100m2 ~ 2,000m2 of area, and 1,000m3 ~ 10,000m3 of volume of small green space. As a result, more than 300m2 and 2,300m3 of polygonal green spaces with mixed vegetation is required to lower 1°C; 650m2 and 5,000m3 of them to lower 2°C; about 2,000m2 and about 10,000m3 of them to lower 4°C air temperature reduction in an urban block.

Cognitive Effects of Adenotonsillectomy for Obstructive Sleep Apnea.

PubMed

Taylor, H Gerry; Bowen, Susan R; Beebe, Dean W; Hodges, Elise; Amin, Raouf; Arens, Raanan; Chervin, Ronald D; Garetz, Susan L; Katz, Eliot S; Moore, Reneé H; Morales, Knashawn H; Muzumdar, Hiren; Paruthi, Shalini; Rosen, Carol L; Sadhwani, Anjali; Thomas, Nina Hattiangadi; Ware, Janice; Marcus, Carole L; Ellenberg, Susan S; Redline, Susan; Giordani, Bruno

2016-08-01

Research reveals mixed evidence for the effects of adenotonsillectomy (AT) on cognitive tests in children with obstructive sleep apnea syndrome (OSAS). The primary aim of the study was to investigate effects of AT on cognitive test scores in the randomized Childhood Adenotonsillectomy Trial. Children ages 5 to 9 years with OSAS without prolonged oxyhemoglobin desaturation were randomly assigned to watchful waiting with supportive care (n = 227) or early AT (eAT, n = 226). Neuropsychological tests were administered before the intervention and 7 months after the intervention. Mixed model analysis compared the groups on changes in test scores across follow-up, and regression analysis examined associations of these changes in the eAT group with changes in sleep measures. Mean test scores were within the average range for both groups. Scores improved significantly (P < .05) more across follow-up for the eAT group than for the watchful waiting group. These differences were found only on measures of nonverbal reasoning, fine motor skills, and selective attention and had small effects sizes (Cohen's d, 0.20-0.24). As additional evidence for AT-related effects on scores, gains in test scores for the eAT group were associated with improvements in sleep measures. Small and selective effects of AT were observed on cognitive tests in children with OSAS without prolonged desaturation. Relative to evidence from Childhood Adenotonsillectomy Trial for larger effects of surgery on sleep, behavior, and quality of life, AT may have limited benefits in reversing any cognitive effects of OSAS, or these benefits may require more extended follow-up to become manifest. Copyright © 2016 by the American Academy of Pediatrics.

Cognitive Effects of Adenotonsillectomy for Obstructive Sleep Apnea

PubMed Central

Bowen, Susan R.; Beebe, Dean W.; Hodges, Elise; Amin, Raouf; Arens, Raanan; Chervin, Ronald D.; Garetz, Susan L.; Katz, Eliot S.; Moore, Reneé H.; Morales, Knashawn H.; Muzumdar, Hiren; Paruthi, Shalini; Rosen, Carol L.; Sadhwani, Anjali; Thomas, Nina Hattiangadi; Ware, Janice; Marcus, Carole L.; Ellenberg, Susan S.; Redline, Susan; Giordani, Bruno

2016-01-01

OBJECTIVE: Research reveals mixed evidence for the effects of adenotonsillectomy (AT) on cognitive tests in children with obstructive sleep apnea syndrome (OSAS). The primary aim of the study was to investigate effects of AT on cognitive test scores in the randomized Childhood Adenotonsillectomy Trial. METHODS: Children ages 5 to 9 years with OSAS without prolonged oxyhemoglobin desaturation were randomly assigned to watchful waiting with supportive care (n = 227) or early AT (eAT, n = 226). Neuropsychological tests were administered before the intervention and 7 months after the intervention. Mixed model analysis compared the groups on changes in test scores across follow-up, and regression analysis examined associations of these changes in the eAT group with changes in sleep measures. RESULTS: Mean test scores were within the average range for both groups. Scores improved significantly (P < .05) more across follow-up for the eAT group than for the watchful waiting group. These differences were found only on measures of nonverbal reasoning, fine motor skills, and selective attention and had small effects sizes (Cohen’s d, 0.20–0.24). As additional evidence for AT-related effects on scores, gains in test scores for the eAT group were associated with improvements in sleep measures. CONCLUSIONS: Small and selective effects of AT were observed on cognitive tests in children with OSAS without prolonged desaturation. Relative to evidence from Childhood Adenotonsillectomy Trial for larger effects of surgery on sleep, behavior, and quality of life, AT may have limited benefits in reversing any cognitive effects of OSAS, or these benefits may require more extended follow-up to become manifest. PMID:27464674

The consumption of alcohol mixed with energy drinks: prevalence and key correlates among Canadian high school students

PubMed Central

Azagba, Sunday; Langille, Don

2013-01-01

Background An emerging body of research has reported high consumption of alcohol mixed with energy drinks among young adults, particularly college students. However, little is known about adolescents’ consumption of these drinks. The purpose of this study was to determine the prevalence of consumption of alcohol mixed with energy drinks and to examine its correlates among Canadian high school students. Methods We used a nationally representative sample of 36 155 Canadian students in grades 7 to 12 who participated in the 2010/2011 Youth Smoking Survey. Results About 20% of Canadian high school students reported consuming alcohol mixed with energy drinks in the last year, with considerable variation across provinces. Multivariate logistic regression analyses showed that the odds of consumption of these drinks were higher among students in lower grades (grades 7 and 8) and among students who identified their ethnicity as black or “other.” Consumption of alcohol mixed with energy drinks was positively associated with substance use (current smoking [adjusted odds ratio (OR) 1.52, 95% confidence interval (CI) 1.19–1.95], past-year heavy drinking [adjusted OR 3.41, 95% CI 2.84–4.09] and marijuana use [adjusted OR 2.29, 95% CI 1.90–2.76]), absence from school, participation in school team sports and having more weekly spending money. Students who felt more connected to school and had an academic average of 70% or higher were less likely to consume alcohol mixed with energy drinks. Interpretation The consumption of alcohol mixed with energy drinks is an emerging public health concern. Consumption of these drinks is substantial among Canadian high school students and can lead to many potential harms, both acute (e.g., injury) and long term (e.g., increased alcohol dependence). Our findings highlight the need for further research into the long-term effects of consumption of alcohol mixed with energy drinks among young people, as well as the development of interventions aimed at reducing consumption of these drinks. PMID:25077098

Prevention nearby: the influence of the presence of a potential guardian on the severity of child sexual abuse.

PubMed

Leclerc, Benoit; Smallbone, Stephen; Wortley, Richard

2015-04-01

The main aim of this study was to examine the effect of a potential guardian on the severity of child sexual abuse. Using data obtained on crime events from adult child sexual offenders incarcerated in Queensland (Australia), mixed-effects logistic regression analyses were conducted to examine the effect of potential guardianship on the severity of abuse. Controlling for victim and situational characteristics, the analyses showed that the presence of a potential guardian reduced the duration of sexual contact and the occurrence of penetration. Presence of a potential guardian decreased the risk of sexual penetration by 86%. The study highlights the importance of the presence of a potential guardian for reducing the severity of child sexual abuse, and suggests more broadly that guardianship may be an important protective factor in sexual offending. © The Author(s) 2013.

Attitudes toward victims of rape: effects of gender, race, religion, and social class.

PubMed

Nagel, Barbara; Matsuo, Hisako; McIntyre, Kevin P; Morrison, Nancy

2005-06-01

Although previous literature focusing on perceptions of victims of rape has examined how gender, race, and culture influence the attitudes one holds toward victims, these studies have yielded mixed results. This study compared perceptions of victims of rape across a wide range of ages, educational backgrounds, religions, and income levels, while focusing on gender and racial differences. Results indicate (N = 220) that victims of rape are generally viewed more sympathetically by females than by males and by Whites than by African Americans. However, the effect of race disappears when socioeconomic variables are controlled, suggesting a more complex relationship. Also, a hierarchical regression indicates that age, sex, education, and income are significant predictors of attitudes toward victims. This study builds on existing research that examines such attitudes from a cultural perspective and extends this literature by examining the interactive effects of several demographic variables within a community sample.

Effects of relational coordination among colleagues and span of control on work engagement among home-visiting nurses.

PubMed

Naruse, Takashi; Sakai, Mahiro; Nagata, Satoko

2016-04-01

Home-visiting nursing agencies are required to foster staff nurse's work engagement; thus, the factors related to work engagement require identification. This study examined relational coordination among colleagues and agency span of control on the work engagement of home-visiting nurses. Cross-sectional data from 93 staff nurses in 31 home-visiting nursing agencies were collected via a survey and analyzed using mixed linear regression. There was no significant main effect of relational coordination among nurse colleagues on work engagement. In large agencies with a large span of control, relational coordination among nursing colleagues predicted work engagement. Nursing managers' relational coordination was found to be positively associated with staff nurse work engagement. Agency span of control is a moderating factor on the positive effect of relational coordination with nursing colleagues on staff nurse work engagement. © 2016 Japan Academy of Nursing Science.

The effects of ownership and ownership change on nursing home industry costs.

PubMed

Holmes, J S

1996-08-01

This study examines the effects of ownership type and ownership change on nursing home cost structures, differentiating patient care costs from plant costs. Administrative data from the Michigan Department of Social Services, Medical Services Administration (Medicaid), and the Michigan Department of Public Health are used. Cost data are based on audited cost reports for 393 nursing care facilities in Michigan in 1989. Other facility characteristics are based on data from the 1989 annual licensing and certification survey conducted by the Michigan Department of Public Health. A series of ordinary least squares regressions is estimated, in which the dependent variable is either per diem patient costs or per diem plant costs. Ownership types are defined as chain, proprietary non-chain, freestanding non-profit, government-owned, and hospital-based facilities. Pooled estimation techniques, as well as separate regressions by ownership type, are presented to test for interaction effects. Key variables include whether a facility changed ownership in the preceding five years and whether chain facilities are in-state- or out-of-state-owned, in addition to size, payer mix, and case mix. Behavioral differences among nursing home ownership types in respect to patient care costs tended to distinguish government-owned and hospital-based facilities from the freestanding homes rather than the usual distinction between for-profit and not-for-profit classes. Variables traditionally included in nursing home cost studies, such as size, occupancy, payer mix and case mix, were found to have similar effects on per diem patient care costs for freestanding non-profit homes as well as for chain proprietary facilities. With regard to the effects of ownership change on per diem plant and per diem patient costs, however, there are few differences among ownership types. Chain and non-chain for-profit facilities, non-profit homes, and hospital long-term care units that had changed ownership reported significantly higher per diem plant costs than facilities without a change of ownership, but did not spend more on patient-related costs. Michigan Medicaid plant reimbursement system policy changes instituted in 1985 to promote continued ownership of facilities were not entirely successful. Non-profit homes look increasingly like their for-profit counterparts with respect to spending on patient care costs. Increased competition for the more lucrative private-pay patients, coupled with declining state Medicaid reimbursement to nursing homes, may have blurred the historical distinctions between the non-profit and for-profit sectors in the nursing home industry. An exception to increasing homogeneity within the nursing home industry is the tendency of proprietary homes to experience more frequent changes of ownership, which results in higher capital costs passed on to state Medicaid programs. Findings from this study indicate that while facility sales increase per diem plant costs, they do not result in increased spending for direct patient care, suggesting that state Medicaid programs may be indirectly subsidizing facility sales with no accompanying increase in expenditures for patient care. To discourage frequent facility sales, state Medicaid programs may need to consider alternative methods of reimbursing nursing home owners for capital costs.

Pharmacodynamics and effectiveness of topical nitroglycerin at lowering blood pressure during autonomic dysreflexia.

PubMed

Solinsky, R; Bunnell, A E; Linsenmeyer, T A; Svircev, J N; Engle, A; Burns, S P

2017-10-01

Secondary analysis of prospectively collected observational data assessing the safety of an autonomic dysreflexia (AD) management protocol. To estimate the time to onset of action, time to full clinical effect (sustained systolic blood pressure (SBP) <160 mm Hg) and effectiveness of nitroglycerin ointment at lowering blood pressure for patients with spinal cord injuries experiencing AD. US Veterans Affairs inpatient spinal cord injury (SCI) unit. Episodes of AD recalcitrant to nonpharmacologic interventions that were given one to two inches of 2% topical nitroglycerin ointment were recorded. Pharmacodynamics as above and predictive characteristics (through a mixed multivariate logistic regression model) were calculated. A total of 260 episodes of pharmacologically managed AD were recorded in 56 individuals. Time to onset of action for nitroglycerin ointment was 9-11 min. Time to full clinical effect was 14-20 min. Topical nitroglycerin controlled SBP <160 mm Hg in 77.3% of pharmacologically treated AD episodes with the remainder requiring additional antihypertensive medications. A multivariate logistic regression model was unable to identify statistically significant factors to predict which patients would respond to nitroglycerin ointment (odds ratios 95% confidence intervals 0.29-4.93). The adverse event rate, entirely attributed to hypotension, was 3.6% with seven of the eight events resolving with close observation alone and one episode requiring normal saline. Nitroglycerin ointment has a rapid onset of action and time to full clinical effect with high efficacy and relatively low adverse event rate for patients with SCI experiencing AD.

Understanding discharge communication behaviours in a pediatric emergency care context: a mixed methods observation study protocol.

PubMed

Curran, Janet A; Bishop, Andrea; Plint, Amy; MacPhee, Shannon; Zemek, Roger; Chorney, Jill; Jabbour, Mona; Porter, Stephen; Sawyer, Scott

2017-04-17

One of the most important transitions in the continuum of care for children is discharge to home. Optimal discharge communication between healthcare providers and caregivers (e.g., parents or other guardians) who present to the emergency department (ED) with their children is not well understood. The lack of policies and considerable variation in practice regarding discharge communication in pediatric EDs pose a quality and safety risk for children and their parents. The aim of this mixed methods study is to better understand the process and structure of discharge communication in a pediatric ED context to contribute to the design and development of discharge communication interventions. We will use surveys, administrative data and real-time video observation to characterize discharge communication for six common illness presentations in a pediatric ED: (1) asthma, (2) bronchiolitis, (3) abdominal pain, (4) fever, (5) diarrhea and vomiting, and (6) minor head injury. Participants will be recruited from one of two urban pediatric EDs in Canada. Video recordings will be analyzed using Observer XT. We will use logistic regression to identify potential demographic and visit characteristic cofounders and multivariate logistic regression to examine association between verbal and non-verbal behaviours and parent recall and comprehension. Video recording of discharge communication will provide an opportunity to capture important data such as temporality, sequence and non-verbal behaviours that might influence the communication process. Given the importance of better characterizing discharge communication to identify potential barriers and enablers, we anticipate that the findings from this study will contribute to the development of more effective discharge communication policies and interventions.

Performance of the score systems Acute Physiology and Chronic Health Evaluation II and III at an interdisciplinary intensive care unit, after customization

PubMed Central

Markgraf, Rainer; Deutschinoff, Gerd; Pientka, Ludger; Scholten, Theo; Lorenz, Cristoph

2001-01-01

Background: Mortality predictions calculated using scoring scales are often not accurate in populations other than those in which the scales were developed because of differences in case-mix. The present study investigates the effect of first-level customization, using a logistic regression technique, on discrimination and calibration of the Acute Physiology and Chronic Health Evaluation (APACHE) II and III scales. Method: Probabilities of hospital death for patients were estimated by applying APACHE II and III and comparing these with observed outcomes. Using the split sample technique, a customized model to predict outcome was developed by logistic regression. The overall goodness-of-fit of the original and the customized models was assessed. Results: Of 3383 consecutive intensive care unit (ICU) admissions over 3 years, 2795 patients could be analyzed, and were split randomly into development and validation samples. The discriminative powers of APACHE II and III were unchanged by customization (areas under the receiver operating characteristic [ROC] curve 0.82 and 0.85, respectively). Hosmer-Lemeshow goodness-of-fit tests showed good calibration for APACHE II, but insufficient calibration for APACHE III. Customization improved calibration for both models, with a good fit for APACHE III as well. However, fit was different for various subgroups. Conclusions: The overall goodness-of-fit of APACHE III mortality prediction was improved significantly by customization, but uniformity of fit in different subgroups was not achieved. Therefore, application of the customized model provides no advantage, because differences in case-mix still limit comparisons of quality of care. PMID:11178223

12-step participation and outcomes over 7 years among adolescent substance use patients with and without psychiatric comorbidity.

PubMed

Chi, Felicia W; Sterling, Stacy; Campbell, Cynthia I; Weisner, Constance

2013-01-01

This study examines the associations between 12-step participation and outcomes over 7 years among 419 adolescent substance use patients with and without psychiatric comorbidities. Although level of participation decreased over time for both groups, comorbid adolescents participated in 12-step groups at comparable or higher levels across time points. Results from mixed-effects logistic regression models indicated that for both groups, 12-step participation was associated with both alcohol and drug abstinence at follow-ups, increasing the likelihood of either by at least 3 times. Findings highlight the potential benefits of 12-step participation in maintaining long-term recovery for adolescents with and without psychiatric disorders.

A mixed methods evaluation of the maternal-newborn dashboard in Ontario: dashboard attributes, contextual factors, and facilitators and barriers to use: a study protocol.

PubMed

Dunn, Sandra; Sprague, Ann E; Grimshaw, Jeremy M; Graham, Ian D; Taljaard, Monica; Fell, Deshayne; Peterson, Wendy E; Darling, Elizabeth; Harrold, JoAnn; Smith, Graeme N; Reszel, Jessica; Lanes, Andrea; Truskoski, Carolyn; Wilding, Jodi; Weiss, Deborah; Walker, Mark

2016-05-04

There are wide variations in maternal-newborn care practices and outcomes across Ontario. To help institutions and care providers learn about their own performance, the Better Outcomes Registry & Network (BORN) Ontario has implemented an audit and feedback system, the Maternal-Newborn Dashboard (MND), for all hospitals providing maternal-newborn care. The dashboard provides (1) near real-time feedback, with site-specific and peer comparison data about six key performance indicators; (2) a visual display of evidence-practice gaps related to the indicators; and (3) benchmarks to provide direction for practice change. This study aims to evaluate the effects of the dashboard, dashboard attributes, contextual factors, and facilitation/support needs that influence the use of this audit and feedback system to improve performance. The objectives of this study are to (1) evaluate the effect of implementing the dashboard across Ontario; (2) explore factors that potentially explain differences in the use of the MND among hospitals; (3) measure factors potentially associated with differential effectiveness of the MND; and (4) identify factors that predict differences in hospital performance. A mixed methods design includes (1) an interrupted time series analysis to evaluate the effect of the intervention on six indicators, (2) key informant interviews with a purposeful sample of directors/managers from up to 20 maternal-newborn care hospitals to explore factors that influence the use of the dashboard, (3) a provincial survey of obstetrical directors/managers from all maternal-newborn hospitals in the province to measure factors that influence the use of the dashboard, and (4) a multivariable generalized linear mixed effects regression analysis of the indicators at each hospital to quantitatively evaluate the change in practice following implementation of the dashboard and to identify factors most predictive of use. Study results will provide essential data to develop knowledge translation strategies for facilitating practice change, which can be further evaluated through a future cluster randomized trial.

Breaking from binaries - using a sequential mixed methods design.

PubMed

Larkin, Patricia Mary; Begley, Cecily Marion; Devane, Declan

2014-03-01

To outline the traditional worldviews of healthcare research and discuss the benefits and challenges of using mixed methods approaches in contributing to the development of nursing and midwifery knowledge. There has been much debate about the contribution of mixed methods research to nursing and midwifery knowledge in recent years. A sequential exploratory design is used as an exemplar of a mixed methods approach. The study discussed used a combination of focus-group interviews and a quantitative instrument to obtain a fuller understanding of women's experiences of childbirth. In the mixed methods study example, qualitative data were analysed using thematic analysis and quantitative data using regression analysis. Polarised debates about the veracity, philosophical integrity and motivation for conducting mixed methods research have largely abated. A mixed methods approach can contribute to a deeper, more contextual understanding of a variety of subjects and experiences; as a result, it furthers knowledge that can be used in clinical practice. The purpose of the research study should be the main instigator when choosing from an array of mixed methods research designs. Mixed methods research offers a variety of models that can augment investigative capabilities and provide richer data than can a discrete method alone. This paper offers an example of an exploratory, sequential approach to investigating women's childbirth experiences. A clear framework for the conduct and integration of the different phases of the mixed methods research process is provided. This approach can be used by practitioners and policy makers to improve practice.

Getting the right balance? A mixed logit analysis of the relationship between UK training doctors' characteristics and their specialties using the 2013 National Training Survey.

PubMed

Rodriguez Santana, Idaira; Chalkley, Martin

2017-08-11

To analyse how training doctors' demographic and socioeconomic characteristics vary according to the specialty that they are training for. Descriptive statistics and mixed logistic regression analysis of cross-sectional survey data to quantify evidence of systematic relationships between doctors' characteristics and their specialty. Doctors in training in the United Kingdom in 2013. 27 530 doctors in training but not in their foundation year who responded to the National Training Survey 2013. Mixed logit regression estimates and the corresponding odds ratios (calculated separately for all doctors in training and a subsample comprising those educated in the UK), relating gender, age, ethnicity, place of studies, socioeconomic background and parental education to the probability of training for a particular specialty. Being female and being white British increase the chances of being in general practice with respect to any other specialty, while coming from a better-off socioeconomic background and having parents with tertiary education have the opposite effect. Mixed results are found for age and place of studies. For example, the difference between men and women is greatest for surgical specialties for which a man is 12.121 times more likely to be training to a surgical specialty (relative to general practice) than a woman (p-value<0.01). Doctors who attended an independent school which is proxy for doctor's socioeconomic background are 1.789 and 1.413 times more likely to be training for surgical or medical specialties (relative to general practice) than those who attended a state school (p-value<0.01). There are systematic and substantial differences between specialties in respect of training doctors' gender, ethnicity, age and socioeconomic background. The persistent underrepresentation in some specialties of women, minority ethnic groups and of those coming from disadvantaged backgrounds will impact on the representativeness of the profession into the future. Further research is needed to understand how the processes of selection and the self-selection of applicants into specialties gives rise to these observed differences. © 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.

Bio hydrogen production from cassava starch by anaerobic mixed cultures: Multivariate statistical modeling

NASA Astrophysics Data System (ADS)

Tien, Hai Minh; Le, Kien Anh; Le, Phung Thi Kim

2017-09-01

Bio hydrogen is a sustainable energy resource due to its potentially higher efficiency of conversion to usable power, high energy efficiency and non-polluting nature resource. In this work, the experiments have been carried out to indicate the possibility of generating bio hydrogen as well as identifying effective factors and the optimum conditions from cassava starch. Experimental design was used to investigate the effect of operating temperature (37-43 °C), pH (6-7), and inoculums ratio (6-10 %) to the yield hydrogen production, the COD reduction and the ratio of volume of hydrogen production to COD reduction. The statistical analysis of the experiment indicated that the significant effects for the fermentation yield were the main effect of temperature, pH and inoculums ratio. The interaction effects between them seem not significant. The central composite design showed that the polynomial regression models were in good agreement with the experimental results. This result will be applied to enhance the process of cassava starch processing wastewater treatment.

Public reporting influences antibiotic and injection prescription in primary care: a segmented regression analysis.

PubMed

Liu, Chenxi; Zhang, Xinping; Wan, Jie

2015-08-01

Inappropriate use and overuse of antibiotics and injections are serious threats to the global population, particularly in developing countries. In recent decades, public reporting of health care performance (PRHCP) has been an instrument to improve the quality of care. However, existing evidence shows a mixed effect of PRHCP. This study evaluated the effect of PRHCP on physicians' prescribing practices in a sample of primary care institutions in China. Segmented regression analysis was used to produce convincing evidence for health policy and reform. The PRHCP intervention was implemented in Qian City that started on 1 October 2013. Performance data on prescription statistics were disclosed to patients and health workers monthly in 10 primary care institutions. A total of 326 655 valid outpatient prescriptions were collected. Monthly effective prescriptions were calculated as analytical units in the research (1st to 31st every month). This study involved multiple assessments of outcomes 13 months before and 11 months after PRHCP intervention (a total of 24 data points). Segmented regression models showed downward trends from baseline on antibiotics (coefficient = -0.64, P = 0.004), combined use of antibiotics (coefficient = -0.41, P < 0.001) and injections (coefficient = -0.5957, P = 0.001) after PRHCP intervention. The average expenditure of patients slightly increased monthly before the intervention (coefficient = 0.8643, P < 0.001); PRHCP intervention also led to a temporary increase in average expenditure of patients (coefficient = 2.20, P = 0.307) but slowed down the ascending trend (coefficient = -0.45, P = 0.033). The prescription rate of antibiotics and injections after intervention (about 50%) remained high. PRHCP showed positive effects on physicians' prescribing behaviour, considering the downward trends on the use of antibiotics and injections and average expenditure through the intervention. However, the effect was not immediately observed; a lag time existed before public reporting intervention worked. © 2015 John Wiley & Sons, Ltd.

Combining data visualization and statistical approaches for interpreting measurements and meta-data: Integrating heatmaps, variable clustering, and mixed regression models

EPA Science Inventory

The advent of new higher throughput analytical instrumentation has put a strain on interpreting and explaining the results from complex studies. Contemporary human, environmental, and biomonitoring data sets are comprised of tens or hundreds of analytes, multiple repeat measures...

Predicting Student Engagement in Online High Schools

ERIC Educational Resources Information Center

Vieira, Christopher James

2013-01-01

The purpose of this study was to analyze student engagement in online high schools based on demographic information of high school students using a mixed methods research design. Key findings through a multiple regression analysis and Pearson correlation coefficient suggest that although the majority of participants in the study are highly engaged…

Visualizing Mixed Variable-Type Multidimensional Data Using Tree Distances

DTIC Science & Technology

2015-09-01

24 1. The Regression Method .................................................. 25 2. Maximum Deviance Ratio Method... Deviance Change as a Factor of the Amount of Correlation? ................................................... 50 B. A PROPOSED SOLUTION...Splice mapping using d1 ...................... 36 Figure 18. Reduction in 2R analog ( deviance ratio-DevRat) per variable for the Splice data

A longitudinal analysis of the influence of the neighborhood built environment on walking for transportation: the RESIDE study.

PubMed

Knuiman, Matthew W; Christian, Hayley E; Divitini, Mark L; Foster, Sarah A; Bull, Fiona C; Badland, Hannah M; Giles-Corti, Billie

2014-09-01

The purpose of the present analysis was to use longitudinal data collected over 7 years (from 4 surveys) in the Residential Environments (RESIDE) Study (Perth, Australia, 2003-2012) to more carefully examine the relationship of neighborhood walkability and destination accessibility with walking for transportation that has been seen in many cross-sectional studies. We compared effect estimates from 3 types of logistic regression models: 2 that utilize all available data (a population marginal model and a subject-level mixed model) and a third subject-level conditional model that exclusively uses within-person longitudinal evidence. The results support the evidence that neighborhood walkability (especially land-use mix and street connectivity), local access to public transit stops, and variety in the types of local destinations are important determinants of walking for transportation. The similarity of subject-level effect estimates from logistic mixed models and those from conditional logistic models indicates that there is little or no bias from uncontrolled time-constant residential preference (self-selection) factors; however, confounding by uncontrolled time-varying factors, such as health status, remains a possibility. These findings provide policy makers and urban planners with further evidence that certain features of the built environment may be important in the design of neighborhoods to increase walking for transportation and meet the health needs of residents. © The Author 2014. 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.

Effect of breast-feeding on weight retention at 3 and 6 months postpartum: data from the North Carolina WIC Programme.

PubMed

Krause, Katrina M; Lovelady, Cheryl A; Peterson, Bercedis L; Chowdhury, Najmul; Østbye, Truls

2010-12-01

Pregnancy-related weight retention can contribute to obesity, and breast-feeding may facilitate postpartum weight loss. We investigated the effect of breast-feeding on postpartum weight retention. A retrospective follow-up study of weight retention, compared in women who were fully breast-feeding, combining breast-feeding with formula-feeding (mixed feeding), or formula-feeding at 3 months (n 14 330) or 6 months (n 4922) postpartum, controlling for demographic and weight-related covariates using multiple linear regression. The North Carolina Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Participants in the North Carolina WIC Programme who delivered a baby between 1996 and 2004. In covariate-adjusted analyses, there was no association between breast-feeding and weight retention at 3 months postpartum. At 6 months postpartum, as compared to formula-feeders, mean weight retention was 0·84 kg lower in mixed feeders (95 % CI 0·39, 1·29; P = 0·0002) and 1·38 kg lower in full breast-feeders (95 % CI 0·89, 1·87; P ≤ 0·0001). Breast-feeding was inversely associated with weight retention at 6 months postpartum in this large, racially diverse sample of low-income women. Further, full breast-feeding had a larger protective effect than did breast-feeding combined with formula-feeding.

Investigating organic molecules responsible of auxin-like activity of humic acid fraction extracted from vermicompost.

PubMed

Scaglia, Barbara; Nunes, Ramom Rachide; Rezende, Maria Olímpia Oliveira; Tambone, Fulvia; Adani, Fabrizio

2016-08-15

This work studied the auxin-like activity of humic acids (HA) obtained from vermicomposts produced using leather wastes plus cattle dung at different maturation stages (fresh, stable and mature). Bioassays were performed by testing HA concentrations in the range of 100-6000mgcarbonL(-1). (13)C CPMAS-NMR and GC-MS instrumental methods were used to assess the effect of biological processes and starting organic mixtures on HA composition. Not all HAs showed IAA-like activity and in general, IAA-like activity increased with the length of the vermicomposting process. The presence of leather wastes was not necessary to produce the auxin-like activity of HA, since HA extracted from a mix of cattle manure and sawdust, where no leather waste was added, showed IAA-like activity as well. CPMAS (13)CNMR revealed that HAs were similar independently of the mix used and that the humification process involved the increasing concentration of pre-existing alkali soluble fractions in the biomass. GC/MS allowed the identification of the molecules involved in IAA-like effects: carboxylic acids and amino acids. The concentration of active molecules, rather than their simple presence in HA, determined the bio-stimulating effect, and a good linear regression between auxin-like activity and active stimulating molecules concentration was found (R(2)=-0.85; p<0.01, n=6). Copyright © 2016 Elsevier B.V. All rights reserved.

Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liou, Kuo-Nan

2016-02-09

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracingmore » computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.« less

Did Rev-1 small ruminants vaccination helped improve cattle brucellosis prevalence status in Algeria?

PubMed

Kardjadj, Moustafa

2017-12-01

In 2006, the Algerian authorities started the Rev-1 vaccination of sheep and goats; consequently, there was a significant improvement of small ruminant brucellosis sanitary status. In this paper, we attempt to study the effect of Rev-1 small ruminants' vaccination on cattle brucellosis prevalence in Algeria. Our results showed an overall cattle herd seroprevalence of 12% (9 positive herds of 75). The risk factor analysis using a logistic regression model indicated that the presence of small ruminants along with cattle in the herd (mixed herds) decreased the odds for brucellosis seropositivity by 1.69 [95% CI 0.54-2.84; P = 0.042] compared to the cattle herds only. Likewise, the present study showed that the presence of Rev-1 vaccinated small ruminants in the herd decreased also the odds for brucellosis seropositivity by 4.10 [95% CI 3.20-5.00; P = 0.003] compared to other herds. This result lead to the assumption that the small ruminants Rev-1 vaccination diminish Brucella microbisme pressure in the mixed herds and help decrease the cattle brucellosis prevalence in these herds.

Growth in stature in fragile X families: A mixed longitudinal study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loesch, D.Z.; Huggins, R.M.; Hoang, N.H.

1995-09-11

The effect of fragile X on growth in stature was estimated in individuals aged 5-20 years from 50 fragile X families. The multivariate normal model for pedigree analysis was applied to the mixed longitudinal data, which varied with regard to intervals between the measurements and their number in individual subjects, totalling 349 measurement data points from fragile X families, and 292 data points from unrelated normal subjects. The results of genetic and regression analysis showed that, in fragile X boys and girls, total pubertal height gain is impaired, whereas the rate of growth during the preadolescent period is increased, comparedmore » with the growth rate of nonfragile X subjects. Moreover, the growth parameters in fragile X males were found to be correlated with the size of CGG trinucleotide expansion. The hypothesis of premature activation of the hypothalamo-pituitary gonadal axis is postulated as the cause of growth impairment in fragile X boys and girls, which should be verified by data on the timing of pubertal stages, hormone levels, and bone maturation. 33 refs., 2 figs., 3 tabs.« less

Road death trend in the United States: implied effects of prevention.

PubMed

Robertson, Leon

2018-05-01

This study estimates road deaths prevented by U.S. vehicle safety regulations, state laws, and other efforts based on comparison of actual deaths to those predicted from temperature and precipitation effects on exposure, migration to warmer areas, population growth, median age of the population, and vehicle mix. Logistic regression of risk factors predictive of road deaths in 1961, prior to the adoption of federal vehicle safety regulations, state behavioral change laws, and other preventive efforts were used to predict deaths in subsequent years given the changing prevalence of the risk factors from 1962 to 2015. The included risk factors are strong predictors of road death risk. Without the preventive efforts, an additional 5.8 million road deaths would likely have occurred in the U.S. from the initiation of federal safety standards for new vehicles in 1968 through 2015.

A Video-Based Intervention on and Evaluation of Nursing Aides' Therapeutic Communication and Residents' Agitation During Mealtime in a Dementia Care Unit.

PubMed

Levy-Storms, Lené; Harris, Lesley M; Chen, Xiao

2016-01-01

The researchers conducted a communication training intervention for certified nursing assistants (CNAs). The intervention aimed at improving CNAs' therapeutic techniques for relating to agitated residents during care. This study focused on an in-depth evaluation of mealtime interactions using videos. Sixteen CNAs and 16 residents living with dementia from one long-term care facility were videotaped during mealtime interactions before and after a therapeutic communication training program. Mixed-effect Poisson regression revealed no effect of the intervention as a whole on residents' refusals, but the intervention did improve CNAs' communication. Additional analyses using specific CNAs' therapeutic communication behaviors indicated a significant negative association with refusals at post-test but not pretest. The findings suggest some communication mechanisms for how the intervention positively influenced residents' refusals.

The effects of guided inquiry instruction on student achievement in high school biology

NASA Astrophysics Data System (ADS)

Vass, Laszlo

The purpose of this quantitative, quasi-experimental study was to measure the effect of a student-centered instructional method called guided inquiry on the achievement of students in a unit of study in high school biology. The study used a non-random sample of 109 students, the control group of 55 students enrolled in high school one, received teacher centered instruction while the experimental group of 54 students enrolled at high school two received student-centered, guided inquiry instruction. The pretest-posttest design of the study analyzed scores using an independent t-test, a dependent t-test (p = <.001), an ANCOVA (p = .007), mixed method ANOVA (p = .024) and hierarchical linear regression (p = <.001). The experimental group that received guided inquiry instruction had statistically significantly higher achievement than the control group.

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

PubMed

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Evaluating large-scale propensity score performance through real-world and synthetic data experiments.

PubMed

Tian, Yuxi; Schuemie, Martijn J; Suchard, Marc A

2018-06-22

Propensity score adjustment is a popular approach for confounding control in observational studies. Reliable frameworks are needed to determine relative propensity score performance in large-scale studies, and to establish optimal propensity score model selection methods. We detail a propensity score evaluation framework that includes synthetic and real-world data experiments. Our synthetic experimental design extends the 'plasmode' framework and simulates survival data under known effect sizes, and our real-world experiments use a set of negative control outcomes with presumed null effect sizes. In reproductions of two published cohort studies, we compare two propensity score estimation methods that contrast in their model selection approach: L1-regularized regression that conducts a penalized likelihood regression, and the 'high-dimensional propensity score' (hdPS) that employs a univariate covariate screen. We evaluate methods on a range of outcome-dependent and outcome-independent metrics. L1-regularization propensity score methods achieve superior model fit, covariate balance and negative control bias reduction compared with the hdPS. Simulation results are mixed and fluctuate with simulation parameters, revealing a limitation of simulation under the proportional hazards framework. Including regularization with the hdPS reduces commonly reported non-convergence issues but has little effect on propensity score performance. L1-regularization incorporates all covariates simultaneously into the propensity score model and offers propensity score performance superior to the hdPS marginal screen.

A comparison of regression methods for model selection in individual-based landscape genetic analysis.

PubMed

Shirk, Andrew J; Landguth, Erin L; Cushman, Samuel A

2018-01-01

Anthropogenic migration barriers fragment many populations and limit the ability of species to respond to climate-induced biome shifts. Conservation actions designed to conserve habitat connectivity and mitigate barriers are needed to unite fragmented populations into larger, more viable metapopulations, and to allow species to track their climate envelope over time. Landscape genetic analysis provides an empirical means to infer landscape factors influencing gene flow and thereby inform such conservation actions. However, there are currently many methods available for model selection in landscape genetics, and considerable uncertainty as to which provide the greatest accuracy in identifying the true landscape model influencing gene flow among competing alternative hypotheses. In this study, we used population genetic simulations to evaluate the performance of seven regression-based model selection methods on a broad array of landscapes that varied by the number and type of variables contributing to resistance, the magnitude and cohesion of resistance, as well as the functional relationship between variables and resistance. We also assessed the effect of transformations designed to linearize the relationship between genetic and landscape distances. We found that linear mixed effects models had the highest accuracy in every way we evaluated model performance; however, other methods also performed well in many circumstances, particularly when landscape resistance was high and the correlation among competing hypotheses was limited. Our results provide guidance for which regression-based model selection methods provide the most accurate inferences in landscape genetic analysis and thereby best inform connectivity conservation actions. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Estimating ground-level PM(10) in a Chinese city by combining satellite data, meteorological information and a land use regression model.

PubMed

Meng, Xia; Fu, Qingyan; Ma, Zongwei; Chen, Li; Zou, Bin; Zhang, Yan; Xue, Wenbo; Wang, Jinnan; Wang, Dongfang; Kan, Haidong; Liu, Yang

2016-01-01

Development of exposure assessment model is the key component for epidemiological studies concerning air pollution, but the evidence from China is limited. Therefore, a linear mixed effects (LME) model was established in this study in a Chinese metropolis by incorporating aerosol optical depth (AOD), meteorological information and the land use regression (LUR) model to predict ground PM10 levels on high spatiotemporal resolution. The cross validation (CV) R(2) and the RMSE of the LME model were 0.87 and 19.2 μg/m(3), respectively. The relative prediction error (RPE) of daily and annual mean predicted PM10 concentrations were 19.1% and 7.5%, respectively. This study was the first attempt in China to estimate both short-term and long-term variation of PM10 levels with high spatial resolution in a Chinese metropolis with the LME model. The results suggested that the LME model could provide exposure assessment for short-term and long-term epidemiological studies in China. Copyright © 2015 Elsevier Ltd. All rights reserved.

Allergy and desensitization to latex. Clinical study on 50 dentistry subjects.

PubMed

Vozza, I; Ranghi, G; Quaranta, A

2005-04-01

Nowadays latex allergy represents a relevant social and occupational problem because this substance constitutes the first material to realise many dental and non dental products; then, there is a cross-reactivity between latex allergens and proteins present in many vegetal foods. The aim of our research was to find latex allergy cases experimenting a percutaneous desensitization protocol. Among 50 examined subjects, those patients resulting positive to thiuram-mix by patch test have been submitted to desensitization after removal of all latex products and substances giving cross-allergy (kiwi, celery, chestnuts, tomato, banana etc.). Desensitization has been carried out by using latex glove from 10 s progressively to 1 h after 1-year treatment. In 7 patients out of 11 (63.6%) regression of symptoms has been verified; 2 patients (18.2%) have declined treatment and 2 patients (18.2%) have showed no regression. Apart immunotherapy and DNA-vaccines, nowadays percutaneous desensitization is the most efficacious, safe and easy treatment for latex allergic patients; it has no collateral effects during its execution and no symptoms coming back to work, but it needs further verifications.

Online EEG artifact removal for BCI applications by adaptive spatial filtering.

PubMed

Guarnieri, Roberto; Marino, Marco; Barban, Federico; Ganzetti, Marco; Mantini, Dante

2018-06-28

The performance of brain computer interfaces (BCIs) based on electroencephalography (EEG) data strongly depends on the effective attenuation of artifacts that are mixed in the recordings. To address this problem, we have developed a novel online EEG artifact removal method for BCI applications, which combines blind source separation (BSS) and regression (REG) analysis. The BSS-REG method relies on the availability of a calibration dataset of limited duration for the initialization of a spatial filter using BSS. Online artifact removal is implemented by dynamically adjusting the spatial filter in the actual experiment, based on a linear regression technique. Our results showed that the BSS-REG method is capable of attenuating different kinds of artifacts, including ocular and muscular, while preserving true neural activity. Thanks to its low computational requirements, BSS-REG can be applied to low-density as well as high-density EEG data. We argue that BSS-REG may enable the development of novel BCI applications requiring high-density recordings, such as source-based neurofeedback and closed-loop neuromodulation. © 2018 IOP Publishing Ltd.

Dough performance, quality and shelf life of flat bread supplemented with fractions of germinated date seed.

PubMed

Hejri-Zarifi, Sudiyeh; Ahmadian-Kouchaksaraei, Zahra; Pourfarzad, Amir; Khodaparast, Mohammad Hossein Haddad

2014-12-01

Germinated palm date seeds were milled into two fractions: germ and residue. Dough rheological characteristics, baking (specific volume and sensory evaluation), and textural properties (at first day and during storage for 5 days) were determined in Barbari flat bread. Germ and residue fractions were incorporated at various levels ranged in 0.5-3 g/100 g of wheat flour. Water absorption, arrival time and gelatination temperature were decreased by germ fraction but accompanied by an increasing effect on the mixing tolerance index and degree of softening in most levels. Although improvement in dough stability was monitored but specific volume of bread was not affected by both fractions. Texture analysis of bread samples during 5 days of storage indicated that both fractions of germinated date seeds were able to diminish bread staling. Avrami non-linear regression equation was chosen as useful mathematical model to properly study bread hardening kinetics. In addition, principal component analysis (PCA) allowed discriminating among dough and bread specialties. Partial least squares regression (PLSR) models were applied to determine the relationships between sensory and instrumental data.

A SYSTEMATIC REVIEW AND META-ANALYSIS OF DROPOUT RATES IN YOUTH SOCCER.

PubMed

Møllerløkken, Nina Elise; Lorås, Håvard; Pedersen, Arve Vorland

2015-12-01

Despite the many benefits of involvement in youth sports, participation in them declines throughout childhood and adolescence. The present study performed a systematic review and meta-analysis of 12 studies reporting dropout rates in youth soccer, involving a total of 724,036 youths ages 10-18 years from five countries. The mixed effects meta-regression analyses took into account age and sex as statistical moderators of dropout rate. Potential articles were identified through computerized searches of the databases PubMed, MedLine, Embase, and SportDiscus up until August 2014, without any further time limit. Based on results reported in the 10 included articles, the annual weighted mean dropout rate is 23.9% across the included cohorts. Meta-regression indicated that annual dropout rates are stable from the ages of 10-19 years, with higher rates for girls (26.8%) compared to boys (21.4%). The present study suggests that youth soccer players are prone to dropout rates in which close to one-fourth of players leave the sport annually, which appears to be a consistent finding across ages 10-18 years.

Changes in case-mix and outcomes of critically ill patients in an Australian tertiary intensive care unit.

PubMed

Williams, T A; Ho, K M; Dobb, G J; Finn, J C; Knuiman, M W; Webb, S A R

2010-07-01

Critical care service is expensive and the demand for such service is increasing in many developed countries. This study aimed to assess the changes in characteristics of critically ill patients and their effect on long-term outcome. This cohort study utilised linked data between the intensive care unit database and state-wide morbidity and mortality databases. Logistic and Cox regression was used to examine hospital survival and five-year survival of 22,298 intensive care unit patients, respectively. There was a significant increase in age, severity of illness and Charlson Comorbidity Index of the patients over a 16-year study period. Although hospital mortality and median length of intensive care unit and hospital stay remained unchanged, one- and five-year survival had significantly improved with time, after adjusting for age, gender; severity of illness, organ failure, comorbidity, 'new' cancer and diagnostic group. Stratified analyses showed that the improvement in five-year survival was particularly strong among patients admitted after cardiac surgery (P = 0.001). In conclusion, although critical care service is increasingly being provided to patients with a higher severity of acute and chronic illnesses, long-term survival outcome has improved with time suggesting that critical care service may still be cost-effectiveness despite the changes in case-mix.

Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

PubMed Central

Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation. PMID:24688400

Prediction of frequency for simulation of asphalt mix fatigue tests using MARS and ANN.

PubMed

Ghanizadeh, Ali Reza; Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation.

The effects of green areas on air surface temperature of the Kuala Lumpur city using WRF-ARW modelling and Remote Sensing technique

NASA Astrophysics Data System (ADS)

Isa, N. A.; Mohd, W. M. N. Wan; Salleh, S. A.; Ooi, M. C. G.

2018-02-01

Matured trees contain high concentration of chlorophyll that encourages the process of photosynthesis. This process produces oxygen as a by-product and releases it into the atmosphere and helps in lowering the ambient temperature. This study attempts to analyse the effect of green area on air surface temperature of the Kuala Lumpur city. The air surface temperatures of two different dates which are, in March 2006 and March 2016 were simulated using the Weather Research and Forecasting (WRF) model. The green area in the city was extracted using the Normalized Difference Vegetation Index (NDVI) from two Landsat satellite images. The relationship between the air surface temperature and the green area were analysed using linear regression models. From the study, it was found that, the green area was significantly affecting the distribution of air temperature within the city. A strong negative correlation was identified through this study which indicated that higher NDVI values tend to have lower air surface temperature distribution within the focus study area. It was also found that, different urban setting in mixed built-up and vegetated areas resulted in different distributions of air surface temperature. Future studies should focus on analysing the air surface temperature within the area of mixed built-up and vegetated area.

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

PubMed

Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza

2017-09-27

Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.

Effects of a Web-Based Computer-Tailored Game to Reduce Binge Drinking Among Dutch Adolescents: A Cluster Randomized Controlled Trial

PubMed Central

Crutzen, Rik; Mercken, Liesbeth; Candel, Math; de Vries, Hein

2016-01-01

Background Binge drinking among Dutch adolescents is among the highest in Europe. Few interventions so far have focused on adolescents aged 15 to 19 years. Because binge drinking increases significantly during those years, it is important to develop binge drinking prevention programs for this group. Web-based computer-tailored interventions can be an effective tool for reducing this behavior in adolescents. Embedding the computer-tailored intervention in a serious game may make it more attractive to adolescents. Objective The aim was to assess whether a Web-based computer-tailored intervention is effective in reducing binge drinking in Dutch adolescents aged 15 to 19 years. Secondary outcomes were reduction in excessive drinking and overall consumption during the previous week. Personal characteristics associated with program adherence were also investigated. Methods A cluster randomized controlled trial was conducted among 34 Dutch schools. Each school was randomized into either an experimental (n=1622) or a control (n=1027) condition. Baseline assessment took place in January and February 2014. At baseline, demographic variables and alcohol use were assessed. Follow-up assessment of alcohol use took place 4 months later (May and June 2014). After the baseline assessment, participants in the experimental condition started with the intervention consisting of a game about alcohol in which computer-tailored feedback regarding motivational characteristics was embedded. Participants in the control condition only received the baseline questionnaire. Both groups received the 4-month follow-up questionnaire. Effects of the intervention were assessed using logistic regression mixed models analyses for binge and excessive drinking and linear regression mixed models analyses for weekly consumption. Factors associated with intervention adherence in the experimental condition were explored by means of a linear regression model. Results In total, 2649 adolescents participated in the baseline assessment. At follow-up, 824 (31.11%) adolescents returned. The intervention was effective in reducing binge drinking among adolescents aged 15 years (P=.03) and those aged 16 years when they participated in at least 2 intervention sessions (P=.04). Interaction effects between excessive drinking and educational level (P=.08) and between weekly consumption and age (P=.09) were found; however, in-depth analyses revealed no significant subgroup effects for both interaction effects. Additional analyses revealed that prolonged use of the intervention was associated with stronger effects for binge drinking. Yet, overall adherence to the intervention was low. Analyses revealed that being Protestant, female, younger, a nonbinge drinker, and having a higher educational background were associated with adherence. Conclusions The intervention was effective for adolescents aged 15 and 16 years concerning binge drinking. Prevention messages may be more effective for those at the start of their drinking career, whereas other methods may be needed for those with a longer history of alcohol consumption. Despite using game elements, intervention completion was low. Trial Registration Dutch Trial Register: NTR4048; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4048 (Archived by WebCite® at http://www.webcitation.org/6eSJD3FiY) PMID:26842694

Effects of a Web-Based Computer-Tailored Game to Reduce Binge Drinking Among Dutch Adolescents: A Cluster Randomized Controlled Trial.

PubMed

Jander, Astrid; Crutzen, Rik; Mercken, Liesbeth; Candel, Math; de Vries, Hein

2016-02-03

Binge drinking among Dutch adolescents is among the highest in Europe. Few interventions so far have focused on adolescents aged 15 to 19 years. Because binge drinking increases significantly during those years, it is important to develop binge drinking prevention programs for this group. Web-based computer-tailored interventions can be an effective tool for reducing this behavior in adolescents. Embedding the computer-tailored intervention in a serious game may make it more attractive to adolescents. The aim was to assess whether a Web-based computer-tailored intervention is effective in reducing binge drinking in Dutch adolescents aged 15 to 19 years. Secondary outcomes were reduction in excessive drinking and overall consumption during the previous week. Personal characteristics associated with program adherence were also investigated. A cluster randomized controlled trial was conducted among 34 Dutch schools. Each school was randomized into either an experimental (n=1622) or a control (n=1027) condition. Baseline assessment took place in January and February 2014. At baseline, demographic variables and alcohol use were assessed. Follow-up assessment of alcohol use took place 4 months later (May and June 2014). After the baseline assessment, participants in the experimental condition started with the intervention consisting of a game about alcohol in which computer-tailored feedback regarding motivational characteristics was embedded. Participants in the control condition only received the baseline questionnaire. Both groups received the 4-month follow-up questionnaire. Effects of the intervention were assessed using logistic regression mixed models analyses for binge and excessive drinking and linear regression mixed models analyses for weekly consumption. Factors associated with intervention adherence in the experimental condition were explored by means of a linear regression model. In total, 2649 adolescents participated in the baseline assessment. At follow-up, 824 (31.11%) adolescents returned. The intervention was effective in reducing binge drinking among adolescents aged 15 years (P=.03) and those aged 16 years when they participated in at least 2 intervention sessions (P=.04). Interaction effects between excessive drinking and educational level (P=.08) and between weekly consumption and age (P=.09) were found; however, in-depth analyses revealed no significant subgroup effects for both interaction effects. Additional analyses revealed that prolonged use of the intervention was associated with stronger effects for binge drinking. Yet, overall adherence to the intervention was low. Analyses revealed that being Protestant, female, younger, a nonbinge drinker, and having a higher educational background were associated with adherence. The intervention was effective for adolescents aged 15 and 16 years concerning binge drinking. Prevention messages may be more effective for those at the start of their drinking career, whereas other methods may be needed for those with a longer history of alcohol consumption. Despite using game elements, intervention completion was low. Dutch Trial Register: NTR4048; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4048 (Archived by WebCite® at http://www.webcitation.org/6eSJD3FiY).

Solid precipitation measurement intercomparison in Bismarck, North Dakota, from 1988 through 1997

USGS Publications Warehouse

Ryberg, Karen R.; Emerson, Douglas G.; Macek-Rowland, Kathleen M.

2009-01-01

A solid precipitation measurement intercomparison was recommended by the World Meteorological Organization (WMO) and was initiated after approval by the ninth session of the Commission for Instruments and Methods of Observation. The goal of the intercomparison was to assess national methods of measuring solid precipitation against methods whose accuracy and reliability were known. A field study was started in Bismarck, N. Dak., during the 1988-89 winter as part of the intercomparison. The last official field season of the WMO intercomparison was 1992-93; however, the Bismarck site continued to operate through the winter of 1996-97. Precipitation events at Bismarck were categorized as snow, mixed, or rain on the basis of descriptive notes recorded as part of the solid precipitation intercomparison. The rain events were not further analyzed in this study. Catch ratios (CRs) - the ratio of the precipitation catch at each gage to the true precipitation measurement (the corrected double fence intercomparison reference) - were calculated. Then, regression analysis was used to develop equations that model the snow and mixed precipitation CRs at each gage as functions of wind speed and temperature. Wind speed at the gages, functions of temperature, and upper air conditions (wind speed and air temperature at 700 millibars pressure) were used as possible explanatory variables in the multiple regression analysis done for this study. The CRs were modeled by using multiple regression analysis for the Tretyakov gage, national shielded gage, national unshielded gage, AeroChem gage, national gage with double fence, and national gage with Wyoming windshield. As in earlier studies by the WMO, wind speed and air temperature were found to influence the CR of the Tretyakov gage. However, in this study, the temperature variable represented the average upper air temperature over the duration of the event. The WMO did not use upper air conditions in its analysis. The national shielded and unshielded gages where found to be influenced by functions of wind speed only, as in other studies, but the upper air wind speed was used as an explanatory variable in this study. The AeroChem gage was not used in the WMO intercomparison study for 1987-93. The AeroChem gage had a highly varied CR at Bismarck, and a number of variables related to wind speed and temperature were used in the model for the CR. Despite extensive efforts to find a model for the national gage with double fence, no statistically significant regression model was found at the 0.05 level of statistical significance. The national gage with Wyoming windshield had a CR modeled by temperature and wind speed variables, and the regression relation had the highest coefficient of determination (R2 = 0.572) and adjusted coefficient of multiple determination (R2a = 0.476) of all of the models identified for any gage. Three of the gage CRs evaluated could be compared with those in the WMO intercomparison study for 1987-93. The WMO intercomparison had the advantage of a much larger dataset than this study. However, the data in this study represented a longer time period. Snow precipitation catch is highly varied depending on the equipment used and the weather conditions. Much of the variation is not accounted for in the WMO equations or in the equations developed in this study, particularly for unshielded gages. Extensive attempts at regression analysis were made with the mixed precipitation data, but it was concluded that the sample sizes were not large enough to model the CRs. However, the data could be used to test the WMO intercomparison equations. The mixed precipitation equations for the Tretyakov and national shielded gages are similar to those for snow in that they are more likely to underestimate precipitation when observed amounts were small and overestimate precipitation when observed amounts were relatively large. Mixed precipitation is underestimated by the WMO adjustment and t

Diffusion measures indicate fight exposure-related damage to cerebral white matter in boxers and mixed martial arts fighters.

PubMed

Shin, W; Mahmoud, S Y; Sakaie, K; Banks, S J; Lowe, M J; Phillips, M; Modic, M T; Bernick, C

2014-02-01

Traumatic brain injury is common in fighting athletes such as boxers, given the frequency of blows to the head. Because DTI is sensitive to microstructural changes in white matter, this technique is often used to investigate white matter integrity in patients with traumatic brain injury. We hypothesized that previous fight exposure would predict DTI abnormalities in fighting athletes after controlling for individual variation. A total of 74 boxers and 81 mixed martial arts fighters were included in the analysis and scanned by use of DTI. Individual information and data on fight exposures, including number of fights and knockouts, were collected. A multiple hierarchical linear regression model was used in region-of-interest analysis to test the hypothesis that fight-related exposure could predict DTI values separately in boxers and mixed martial arts fighters. Age, weight, and years of education were controlled to ensure that these factors would not account for the hypothesized effects. We found that the number of knockouts among boxers predicted increased longitudinal diffusivity and transversal diffusivity in white matter and subcortical gray matter regions, including corpus callosum, isthmus cingulate, pericalcarine, precuneus, and amygdala, leading to increased mean diffusivity and decreased fractional anisotropy in the corresponding regions. The mixed martial arts fighters had increased transversal diffusivity in the posterior cingulate. The number of fights did not predict any DTI measures in either group. These findings suggest that the history of fight exposure in a fighter population can be used to predict microstructural brain damage.

Salinization of porewater in a multiple aquitard-aquifer system in Jiangsu coastal plain, China

NASA Astrophysics Data System (ADS)

Li, Jing; Liang, Xing; Zhang, Yanian; Liu, Yan; Chen, Naijia; Abubakari, Alhassan; Jin, Menggui

2017-12-01

Chemical and isotopic compositions were analyzed in porewater squeezed from a clayey aquitard in Jiangsu coastal plain, eastern China, to interpret the salinity origin, chemical evolution and water-mass mixing process. A strong geochemical fingerprint was obtained with an aligned Cl/Br ratio of 154 in the salinized aquitard porewater over a wide Cl- concentration range (396-9,720 mg/L), indicating that porewater salinity is likely derived from a mixing with old brine with a proportion of less than 20%. Very small contributions of brine exerted limited effects on water stable isotopes. The relationships between porewater δ18O and δD indicate that shallow and intermediate porewaters could be original seawater and were subsequently diluted with modern meteoric water, whereas deep porewaters with depleted stable isotopic values were probably recharged during a cooler period and modified by evaporation and seawater infiltration. The cation-Cl relationship and mineralogy of associated strata indicate that porewater has been chemically modified by silicate weathering and ion-exchange reactions. 87Sr/86Sr ratios of 0.7094-0.7112 further confirm the input source of silicate minerals. Numerical simulations were used to evaluate the long-term salinity evolution of the deep porewater. The alternations of boundary conditions (i.e., the third aquifer mixed with brine at approximately 70 ka BP, followed by recharge of glacial meltwater at 20-25 ka BP, and then mixing with Holocene seawater at 7-10 ka BP) are responsible for the shift in porewater salinity. These timeframes correspond with the results of previous studies on ancient marine transgression-regression in Jiangsu coastal plain.

Do effects of common case-mix adjusters on patient experiences vary across patient groups?

PubMed

de Boer, Dolf; van der Hoek, Lucas; Rademakers, Jany; Delnoij, Diana; van den Berg, Michael

2017-11-22

Many survey studies in health care adjust for demographic characteristics such as age, gender, educational attainment and general health when performing statistical analyses. Whether the effects of these demographic characteristics are consistent between patient groups remains to be determined. This is important as the rationale for adjustment is often that demographic sub-groups differ in their so-called 'response tendency'. This rationale may be less convincing if the effects of response tendencies vary across patient groups. The present paper examines whether the impact of these characteristics on patients' global rating of care varies across patient groups. Secondary analyses using multi-level regression models were performed on a dataset including 32 different patient groups and 145,578 observations. For each demographic variable, the 95% expected range of case-mix coefficients across patient groups is presented. In addition, we report whether the variance of coefficients for demographic variables across patient groups is significant. Overall, men, elderly, lower educated people and people in good health tend to give higher global ratings. However, these effects varied significantly across patient groups and included the possibility of no effect or an opposite effect in some patient groups. The response tendency attributed to demographic characteristics - such as older respondents being milder, or higher educated respondents being more critical - is not general or universal. As such, the mechanism linking demographic characteristics to survey results on patient experiences with quality of care is more complicated than a general response tendency. It is possible that the response tendency interacts with patient group, but it is also possible that other mechanisms are at play.

The Effectiveness of Psychosocial Interventions Delivered by Teachers in Schools: A Systematic Review and Meta-Analysis.

PubMed

Franklin, Cynthia; Kim, Johnny S; Beretvas, Tasha S; Zhang, Anao; Guz, Samantha; Park, Sunyoung; Montgomery, Katherine; Chung, Saras; Maynard, Brandy R

2017-09-01

The growing mental health needs of students within schools have resulted in teachers increasing their involvement in the delivery of school-based, psychosocial interventions. Current research reports mixed findings concerning the effectiveness of psychosocial interventions delivered by teachers for mental health outcomes. This article presents a systematic review and meta-analysis that examined the effectiveness of school-based psychosocial interventions delivered by teachers on internalizing and externalizing outcomes and the moderating factors that influence treatment effects on these outcomes. Nine electronic databases, major journals, and gray literature (e.g., websites, conference abstract) were searched and field experts were contacted to locate additional studies. Twenty-four studies that met the study inclusion criteria were coded into internalizing or externalizing outcomes and further analyzed using robust variance estimation in meta-regression. Both publication and risk of bias of studies were further assessed. The results showed statistically significant reductions in students' internalizing outcomes (d = .133, 95% CI [.002, .263]) and no statistical significant effect for externalizing outcomes (d = .15, 95% CI [-.037, .066]). Moderator analysis with meta-regression revealed that gender (%male, b = -.017, p < .05), race (% Caucasian, b = .002, p < .05), and the tier of intervention (b = .299, p = .06) affected intervention effectiveness. This study builds on existing literature that shows that teacher-delivered Tier 1 interventions are effective interventions but also adds to this literature by showing that interventions are more effective with internalizing outcomes than on the externalizing outcomes. Moderator analysis also revealed treatments were more effective with female students for internalizing outcomes and more effective with Caucasian students for externalizing outcomes.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

Developing A New Predictive Dispersion Equation Based on Tidal Average (TA) Condition in Alluvial Estuaries

NASA Astrophysics Data System (ADS)

Anak Gisen, Jacqueline Isabella; Nijzink, Remko C.; Savenije, Hubert H. G.

2014-05-01

Dispersion mathematical representation of tidal mixing between sea water and fresh water in The definition of dispersion somehow remains unclear as it is not directly measurable. The role of dispersion is only meaningful if it is related to the appropriate temporal and spatial scale of mixing, which are identified as the tidal period, tidal excursion (longitudinal), width of estuary (lateral) and mixing depth (vertical). Moreover, the mixing pattern determines the salt intrusion length in an estuary. If a physically based description of the dispersion is defined, this would allow the analytical solution of the salt intrusion problem. The objective of this study is to develop a predictive equation for estimating the dispersion coefficient at tidal average (TA) condition, which can be applied in the salt intrusion model to predict the salinity profile for any estuary during different events. Utilizing available data of 72 measurements in 27 estuaries (including 6 recently studied estuaries in Malaysia), regressions analysis has been performed with various combinations of dimensionless parameters . The predictive dispersion equations have been developed for two different locations, at the mouth D0TA and at the inflection point D1TA (where the convergence length changes). Regressions have been carried out with two separated datasets: 1) more reliable data for calibration; and 2) less reliable data for validation. The combination of dimensionless ratios that give the best performance is selected as the final outcome which indicates that the dispersion coefficient is depending on the tidal excursion, tidal range, tidal velocity amplitude, friction and the Richardson Number. A limitation of the newly developed equation is that the friction is generally unknown. In order to compensate this problem, further analysis has been performed adopting the hydraulic model of Cai et. al. (2012) to estimate the friction and depth. Keywords: dispersion, alluvial estuaries, mixing, salt intrusion, predictive equation

Socioeconomic and Cultural Correlates of Diet Quality in the Canadian Arctic: Results from the 2007-2008 Inuit Health Survey.

PubMed

Galloway, Tracey; Johnson-Down, Louise; Egeland, Grace M

2015-09-01

We examined the impact of socioeconomic and cultural factors on dietary quality in adult Inuit living in the Canadian Arctic. Interviews and a 24-h dietary recall were administered to 805 men and 1292 women from Inuit regions in the Canadian Arctic. We examined the effect of age, sex, education, income, employment, and cultural variables on respondents' energy, macronutrient intake, sodium/potassium ratio, and healthy eating index. Logistic regression was used to assess the impact of socioeconomic status (SES) on diet quality indicators. Age was positively associated with traditional food (TF) consumption and greater energy from protein but negatively associated with total energy and fibre intake. Associations between SES and diet quality differed considerably between men and women and there was considerable regional variability in diet quality measures. Age and cultural variables were significant predictors of diet quality in logistic regression. Increased age and use of the Inuit language in the home were the most significant predictors of TF consumption. Our findings are consistent with studies reporting a nutrition transition in circumpolar Inuit. We found considerable variability in diet quality and complex interaction between SES and cultural variables producing mixed effects that differ by age and gender.

How Do Clinicians Prefer Cultural Competence Training? Findings from the DSM-5 Cultural Formulation Interview Field Trial

PubMed Central

Aggarwal, Neil Krishan; Lam, Peter; Castillo, Enrico; Weiss, Mitchell G.; Diaz, Esperanza; Alarcón, Renato D.; van Dijk, Rob; Rohlof, Hans; Ndetei, David M.; Scalco, Monica; Aguilar-Gaxiola, Sergio; Bassiri, Kavoos; Deshpande, Smita; Groen, Simon; Jadhav, Sushrut; Kirmayer, Laurence J.; Paralikar, Vasudeo; Westermeyer, Joseph; Santos, Filipa; Vega-Dienstmaier, Johann; Anez, Luis; Boiler, Marit; Nicasio, Andel V.; Lewis-Fernández, Roberto

2015-01-01

Objective This study’s objective is to analyze training methods clinicians reported as most and least helpful during the DSM-5 Cultural Formulation Interview field trial, reasons why, and associations between demographic characteristics and method preferences. Method The authors used mixed methods to analyze interviews from 75 clinicians in five continents on their training preferences after a standardized training session and clinicians’ first administration of the Cultural Formulation Interview. Content analysis identified most and least helpful educational methods by reason. Bivariate and logistic regression analysis compared clinician characteristics to method preferences. Results Most frequently, clinicians named case-based behavioral simulations as “most helpful” and video as “least helpful” training methods. Bivariate and logistic regression models, first unadjusted and then clustered by country, found that each additional year of a clinician’s age was associated with a preference for behavioral simulations: OR=1.05 (95% CI: 1.01–1.10; p=0.025). Conclusions Most clinicians preferred active behavioral simulations in cultural competence training, and this effect was most pronounced among older clinicians. Effective training may be best accomplished through a combination of reviewing written guidelines, video demonstration, and behavioral simulations. Future work can examine the impact of clinician training satisfaction on patient symptoms and quality of life. PMID:26449983

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Sorek Hamer, Meytar; Lyapustin, Alexei; Wang, Yujie

2017-01-01

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

Associations between homocysteine metabolism related SNPs and carotid intima-media thickness: a Chinese sib pair study.

PubMed

Sun, Kexin; Song, Jing; Liu, Kuo; Fang, Kai; Wang, Ling; Wang, Xueyin; Li, Jing; Tang, Xun; Wu, Yiqun; Qin, Xueying; Wu, Tao; Gao, Pei; Chen, Dafang; Hu, Yonghua

2017-04-01

Carotid intima-media thickness (CIMT) is a good surrogate for atherosclerosis. Hyperhomocysteinemia is an independent risk factor for cardiovascular diseases. We aim to investigate the relationships between homocysteine (Hcy) related biochemical indexes and CIMT, the associations between Hcy related SNPs and CIMT, as well as the potential gene-gene interactions. The present study recruited full siblings (186 eligible families with 424 individuals) with no history of cardiovascular events from a rural area of Beijing. We examined CIMT, intima-media thickness for common carotid artery (CCA-IMT) and carotid bifurcation, tested plasma levels for Hcy, vitamin B6 (VB6), vitamin B12 (VB12) and folic acid (FA), and genotyped 9 SNPs on MTHFR, MTR, MTRR, BHMT, SHMT1, CBS genes. Associations between SNPs and biochemical indexes and CIMT indexes were analyzed using family-based association test analysis. We used multi-level mixed-effects regression model to verify SNP-CIMT associations and to explore the potential gene-gene interactions. VB6, VB12 and FA were negatively correlated with CIMT indexes (p < 0.05). rs2851391 T allele was associated with decreased plasma VB12 levels (p = 0.036). In FABT, CBS rs2851391 was significantly associated with CCA-IMT (p = 0.021) and CIMT (p = 0.019). In multi-level mixed-effects regression model, CBS rs2851391 was positively significantly associated with CCA-IMT (Coef = 0.032, se = 0.009, raw p < 0.001) after Bonferoni correction (corrected α = 0.0056). Gene-gene interactions were found between CBS rs2851391 and BHMT rs10037045 for CCA-IMT (p = 0.011), as well as between CBS rs2851391 and MTR rs1805087 for CCA-IMT (p = 0.007) and CIMT (p = 0.022). Significant associations are found between Hcy metabolism related genetic polymorphisms, biochemical indexes and CIMT indexes. There are complex interactions between genetic polymorphisms for CCA-IMT and CIMT.

Comparison of marginal bone loss and implant success between axial and tilted implants in maxillary All-on-4 treatment concept rehabilitations after 5 years of follow-up.

PubMed

Hopp, Milena; de Araújo Nobre, Miguel; Maló, Paulo

2017-10-01

There is need for more scientific and clinical information on longer-term outcomes of tilted implants compared to implants inserted in an axial position. Comparison of marginal bone loss and implant success after a 5-year follow-up between axial and tilted implants inserted for full-arch maxillary rehabilitation. The retrospective clinical study included 891 patients with 3564 maxillary implants rehabilitated according to the All-on-4 treatment concept. The follow-up time was 5 years. Linear mixed-effect models were performed to analyze the influence of implant orientation (axial/tilted) on marginal bone loss and binary logistic regression to assess the effect of patient characteristics on occurrence of marginal bone loss >2.8 mm. Only those patients with measurements of at least one axial and one tilted implant available were analyzed. This resulted in a data set of 2379 implants (1201 axial, 1178 tilted) in 626 patients (=reduced data set). Axial and tilted implants showed comparable mean marginal bone losses of 1.14 ± 0.71 and 1.19 ± 0.82 mm, respectively. Mixed model analysis indicated that marginal bone loss levels at 5 years follow up was not significantly affected by the orientation (axial/tilted) of the implants in the maxillary bone. Smoking and female gender were associated with marginal bone loss >2.8 mm in a logistic regression analysis. Five-year implant success rates were 96%. The occurrence of implant failure showed to be statistically independent from orientation. Within the limitations of this study and considering a follow-up time of 5 years, it can be concluded that tilted implants behave similarly with regards to marginal bone loss and implant success in comparison to axial implants in full-arch rehabilitation of the maxilla. Longer-term outcomes (10 years +) are needed to verify this result. © 2017 Wiley Periodicals, Inc.

Influence of motivation, self-efficacy and situational factors on the teaching quality of clinical educators.

PubMed

Dybowski, Christoph; Sehner, Susanne; Harendza, Sigrid

2017-05-08

Being exposed to good teachers has been shown to enhance students' knowledge and their clinical performance, but little is known about the underlying psychological mechanisms that provide the basis for being an excellent medical teacher. Self-Determination Theory (SDT) postulates that more self-regulated types of motivation are associated with higher performance. Social Cognitive Theory (SCT) focuses on self-efficacy that has been shown to be positively associated with performance. To investigate the influences of different types of teaching motivation, teaching self-efficacy, and teachers' perceptions of students' skills, competencies and motivation on teaching quality. Before the winter semester 2014, physicians involved in bedside teaching in internal medicine at the University Medical Center Hamburg-Eppendorf completed a questionnaire with sociodemographic items and instruments measuring different dimensions of teaching motivation as well as teaching self-efficacy. During the semester, physicians rated their perceptions of the participating students who rated the teaching quality after each lesson. We performed a random intercept mixed-effects linear regression with students' ratings of teaching quality as the dependent variable and students' general interest in a subject as covariate. We explored potential associations between teachers' dispositions and their perceptions of students' competencies in a mixed-effects random intercept logistic regression. 94 lessons given by 55 teachers with 500 student ratings were analyzed. Neither teaching motivation nor teaching self-efficacy were directly associated with students' rating of teaching quality. Teachers' perceptions of students' competencies and students' general interest in the lesson's subject were positively associated with students' rating of teaching quality. Physicians' perceptions of their students' competencies were significantly positively predicted by their teaching self-efficacy. Teaching quality might profit from teachers who are self-efficacious and able to detect their students' competencies. Students' general interest in a lesson's subject needs to be taken into account when they are asked to evaluate teaching quality.

Understanding the Effects of Urban Expansion on Spatio-temporal Variations of Vegetation Phenology at Global Scale from 1993 to 2014

NASA Astrophysics Data System (ADS)

Qiu, T.; Song, C.

2017-12-01

Many studies have examined the urbanization-induced vegetation phenology changes in urban environments at regional scales. However, relatively few studies have investigated the effects of urban expansion on vegetation phenology at global scale. In this study, we used times series of NASA Vegetation Index and Phenology (VIP) and ESA Climate Change Initiative Land Cover datasets to quantify how urban expansion affects growing seasons of vegetation in 14 different biomes along both latitude and urbanization gradients from 1993 to 2014. First, we calculated the percentages of impervious surface area (ISA) at 0.05˚ grid to match the spatial resolution of VIP dataset. We then applied logistic models to the ISA series to characterize the time periods of stable ISA, pre-urbanization and post-urbanization for each grid. The amplitudes of urbanization were also derived from the fitted ISA series. We then calculated the mean values of the Start of Season (SOS), End of Season (EOS) and Length of Season (LOS) from VIP datasets within each period. Linear regressions were used to quantify the correlations between ISA and SOS/EOS/LOS in 14 biomes along the latitude gradient for each period. We also calculated the differences of SOS/EOS/LOS between pre-urbanization and post-urbanization periods and applied quantile regressions to characterize the relationships between amplitudes of urbanization and those differences. We found significant correlations (p-value < 0.05) between ISA and the growing seasons of a) boreal forests at 55-60 ˚N; b) temperate broadleaf and mixed forests at 30-55 ˚N; c) temperate coniferous forests at 30-45 ˚N; d) temperate grasslands, savannas, and shrublands at 35-60 ˚N and 30-35 ˚S. We also found a significant positive correlation (p-value <0.05) between amplitudes of urbanization and LOS as well as a significant negative correlation (p-value<0.05) between amplitudes of urbanization and SOS in temperate broadleaf and mixed forest.

Estimating the energetic cost of feeding excess dietary nitrogen to dairy cows.

PubMed

Reed, K F; Bonfá, H C; Dijkstra, J; Casper, D P; Kebreab, E

2017-09-01

Feeding N in excess of requirement could require the use of additional energy to metabolize excess protein, and to synthesize and excrete urea; however, the amount and fate of this energy is unknown. Little progress has been made on this topic in recent decades, so an extension of work published in 1970 was conducted to quantify the effect of excess N on ruminant energetics. In part 1 of this study, the results of previous work were replicated using a simple linear regression to estimate the effect of excess N on energy balance. In part 2, mixed model methodology and a larger data set were used to improve upon the previously reported linear regression methods. In part 3, heat production, retained energy, and milk energy replaced the composite energy balance variable previously proposed as the dependent variable to narrow the effect of excess N. In addition, rumen degradable and undegradable protein intakes were estimated using table values and included as covariates in part 3. Excess N had opposite and approximately equal effects on heat production (+4.1 to +7.6 kcal/g of excess N) and retained energy (-4.2 to -6.6 kcal/g of excess N) but had a larger negative effect on milk gross energy (-52 to -68 kcal/g of excess N). The results suggest that feeding excess N increases heat production, but more investigation is required to determine why excess N has such a large effect on milk gross energy production. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Effects of physical activity calorie expenditure (PACE) labeling: study design and baseline sample characteristics.

PubMed

Viera, Anthony J; Tuttle, Laura; Olsson, Emily; Gras-Najjar, Julie; Gizlice, Ziya; Hales, Derek; Linnan, Laura; Lin, Feng-Chang; Noar, Seth M; Ammerman, Alice

2017-09-12

Obesity and physical inactivity are responsible for more than 365,000 deaths per year and contribute substantially to rising healthcare costs in the US, making clear the need for effective public health interventions. Calorie labeling on menus has been implemented to guide consumer ordering behaviors, but effects on calories purchased has been minimal. In this project, we tested the effect of physical activity calorie expenditure (PACE) food labels on actual point-of-decision food purchasing behavior as well as physical activity. Using a two-group interrupted time series cohort study design in three worksite cafeterias, one cafeteria was assigned to the intervention condition, and the other two served as controls. Calories from food purchased in the cafeteria were assessed by photographs of meals (accompanied by notes made on-site) using a standardized calorie database and portion size-estimation protocol. Primary outcomes will be average calories purchased and minutes of moderate to vigorous physical activity (MVPA) by individuals in the cohorts. We will compare pre-post changes in study outcomes between study groups using piecewise generalized linear mixed model regressions (segmented regressions) with a single change point in our interrupted time-series study. The results of this project will provide evidence of the effectiveness of worksite cafeteria menu labeling, which could potentially inform policy intervention approaches. Labels that convey information in a more readily understandable manner may be more effective at motivating behavior change. Strengths of this study include its cohort design and its robust data capture methods using food photographs and accelerometry.

Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis.

PubMed

Amlung, M; Petker, T; Jackson, J; Balodis, I; MacKillop, J

2016-08-01

An increasing number of studies have investigated delay discounting (DD) in relation to obesity, but with mixed findings. This meta-analysis synthesized the literature on the relationship between monetary and food DD and obesity, with three objectives: (1) to characterize the relationship between DD and obesity in both case-control comparisons and continuous designs; (2) to examine potential moderators, including case-control v. continuous design, money v. food rewards, sample sex distribution, and sample age (18 years); and (3) to evaluate publication bias. From 134 candidate articles, 39 independent investigations yielded 29 case-control and 30 continuous comparisons (total n = 10 278). Random-effects meta-analysis was conducted using Cohen's d as the effect size. Publication bias was evaluated using fail-safe N, Begg-Mazumdar and Egger tests, meta-regression of publication year and effect size, and imputation of missing studies. The primary analysis revealed a medium effect size across studies that was highly statistically significant (d = 0.43, p < 10-14). None of the moderators examined yielded statistically significant differences, although notably larger effect sizes were found for studies with case-control designs, food rewards and child/adolescent samples. Limited evidence of publication bias was present, although the Begg-Mazumdar test and meta-regression suggested a slightly diminishing effect size over time. Steep DD of food and money appears to be a robust feature of obesity that is relatively consistent across the DD assessment methodologies and study designs examined. These findings are discussed in the context of research on DD in drug addiction, the neural bases of DD in obesity, and potential clinical applications.

Reading is fundamentally similar across disparate writing systems: A systematic characterization of how words and characters influence eye movements in Chinese reading

PubMed Central

Li, Xingshan; Bicknell, Klinton; Liu, Pingping; Wei, Wei; Rayner, Keith

2013-01-01

While much previous work on reading in languages with alphabetic scripts has suggested that reading is word-based, reading in Chinese has been argued to be less reliant on words. This is primarily because in the Chinese writing system words are not spatially segmented, and characters are themselves complex visual objects. Here, we present a systematic characterization of the effects of a wide range of word and character properties on eye movements in Chinese reading, using a set of mixed-effects regression models. The results reveal a rich pattern of effects of the properties of the current, previous, and next words on a range of reading measures, which is strikingly similar to the pattern of effects of word properties reported in spaced alphabetic languages. This finding provides evidence that reading shares a word-based core and may be fundamentally similar across languages with highly dissimilar scripts. We show that these findings are robust to the inclusion of character properties in the regression models, and are equally reliable when dependent measures are defined in terms of characters rather than words, providing strong evidence that word properties have effects in Chinese reading above and beyond characters. This systematic characterization of the effects of word and character properties in Chinese advances our knowledge of the processes underlying reading and informs the future development of models of reading. More generally, however, this work suggests that differences in script may not alter the fundamental nature of reading. PMID:23834023

The mixing effects for real gases and their mixtures

NASA Astrophysics Data System (ADS)

Gong, M. Q.; Luo, E. C.; Wu, J. F.

2004-10-01

The definitions of the adiabatic and isothermal mixing effects in the mixing processes of real gases were presented in this paper. Eight substances with boiling-point temperatures from cryogenic temperature to the ambient temperature were selected from the interest of low temperature refrigeration to study their binary and multicomponent mixing effects. Detailed analyses were made on the parameters of the mixing process to know their influences on mixing effects. Those parameters include the temperatures, pressures, and mole fraction ratios of pure substances before mixing. The results show that the maximum temperature variation occurs at the saturation state of each component in the mixing process. Those components with higher boiling-point temperatures have higher isothermal mixing effects. The maximum temperature variation which is defined as the adiabatic mixing effect can even reach up to 50 K, and the isothermal mixing effect can reach about 20 kJ/mol. The possible applications of the mixing cooling effect in both open cycle and closed cycle refrigeration systems were also discussed.

Learning curve for intracranial angioplasty and stenting in single center.

PubMed

Cai, Qiankun; Li, Yongkun; Xu, Gelin; Sun, Wen; Xiong, Yunyun; Sun, Wenshan; Bao, Yuanfei; Huang, Xianjun; Zhang, Yao; Zhou, Lulu; Zhu, Wusheng; Liu, Xinfeng

2014-01-01

To identify the specific caseload to overcome learning curve effect based on data from consecutive patients treated with Intracranial Angioplasty and Stenting (IAS) in our center. The Stenting and Aggressive Medical Management for Preventing Recurrent Stroke and Intracranial Stenosis trial was prematurely terminated owing to the high rate of periprocedural complications in the endovascular arm. To date, there are no data available for determining the essential caseload sufficient to overcome the learning effect and perform IAS with an acceptable level of complications. Between March 2004 and May 2012, 188 consecutive patients with 194 lesions who underwent IAS were analyzed retrospectively. The outcome variables used to assess the learning curve were periprocedural complications (included transient ischemic attack, ischemic stroke, vessel rupture, cerebral hyperperfusion syndrome, and vessel perforation). Multivariable logistic regression analysis was employed to illustrate the existence of learning curve effect on IAS. A risk-adjusted cumulative sum chart was performed to identify the specific caseload to overcome learning curve effect. The overall rate of 30-days periprocedural complications was 12.4% (24/194). After adjusting for case-mix, multivariate logistic regression analysis showed that operator experience was an independent predictor for periprocedural complications. The learning curve of IAS to overcome complications in a risk-adjusted manner was 21 cases. Operator's level of experience significantly affected the outcome of IAS. Moreover, we observed that the amount of experience sufficient for performing IAS in our center was 21 cases. Copyright © 2013 Wiley Periodicals, Inc.

The nature of immunity to Snyder-Theilen fibrosarcoma virus induced tumors in cats.

PubMed

Johnson, L; Pedersen, N C; Theilen, G H

1985-07-01

Snyder-Theilen fibrosarcoma virus (ST-FeSV) induced tumors evoked a vigorous immune response in adolescent cats. The response was characterized histologically by a lymphoid and histiocytic cell infiltrate beginning around the 9th day post inoculation. Hyperemia edema, hemorrhage, and necrosis of the tumors occurred shortly thereafter. Gross regression of the tumors commenced around the 15th day. Viable fibrosarcoma cells could be recovered as almost pure cultures from tumors biopsied on the 9th day. Biopsies taken between days 9 and 15 contained progressively fewer tumor cells and increasing numbers of lymphoid cells, histiocytes, giant cells, and normal fibroblasts. Tumor cells in such mixed cultures did not replicate as fast as normal and died out within 7 to 14 days. Viable tumor cells were not recovered from biopsies taken after day 15. Fibrosarcoma regression was associated with the appearance of tumor cell specific cytotoxic lymphocytes and antibodies in the blood. Cell mediated immunity, as determined by a chromium release assay, consisted of both antibody dependent and independent mechanisms. Fluorescent and complement dependent cytolytic antibodies were detected in the blood at the same time as cytotoxic lymphocytes, but persisted after regression. In a preliminary experiment, serum from tumor regressor cats was injected into susceptible kittens, and the kittens were then challenged with ST-FeSV transformed fibroblasts or whole FeSV. Immune serum did not prevent the appearance of initial growth of tumors, but did slow their subsequent growth and increased the rate of regression. Immune serum had a much more dramatic inhibitory effect on the accompanying retrovirus infection.

Cancer patient experience, hospital performance and case mix: evidence from England.

PubMed

Abel, Gary A; Saunders, Catherine L; Lyratzopoulos, Georgios

2014-01-01

  This study aims to explore differences between crude and case mix-adjusted estimates of hospital performance with respect to the experience of cancer patients. This study analyzed the English 2011/2012 Cancer Patient Experience Survey covering all English National Health Service hospitals providing cancer treatment (n = 160). Logistic regression analysis was used to predict hospital performance for each of the 64 evaluative questions, adjusting for age, gender, ethnic group and cancer diagnosis. The degree of reclassification was explored across three categories (bottom 20%, middle 60% and top 20% of hospitals). There was high concordance between crude and adjusted ranks of hospitals (median Kendall's τ = 0.84; interquartile range: 0.82-0.88). Across all questions, a median of 5.0% (eight) of hospitals (interquartile range: 3.8-6.4%; six to ten hospitals) moved out of the extreme performance categories after case mix adjustment. In this context, patient case mix has only a small impact on measured hospital performance for cancer patient experience.

Ice cream structural elements that affect melting rate and hardness.

PubMed

Muse, M R; Hartel, R W

2004-01-01

Statistical models were developed to reveal which structural elements of ice cream affect melting rate and hardness. Ice creams were frozen in a batch freezer with three types of sweetener, three levels of the emulsifier polysorbate 80, and two different draw temperatures to produce ice creams with a range of microstructures. Ice cream mixes were analyzed for viscosity, and finished ice creams were analyzed for air cell and ice crystal size, overrun, and fat destabilization. The ice phase volume of each ice cream were calculated based on the freezing point of the mix. Melting rate and hardness of each hardened ice cream was measured and correlated with the structural attributes by using analysis of variance and multiple linear regression. Fat destabilization, ice crystal size, and the consistency coefficient of the mix were found to affect the melting rate of ice cream, whereas hardness was influenced by ice phase volume, ice crystal size, overrun, fat destabilization, and the rheological properties of the mix.

Turnover, staffing, skill mix, and resident outcomes in a national sample of US nursing homes.

PubMed

Trinkoff, Alison M; Han, Kihye; Storr, Carla L; Lerner, Nancy; Johantgen, Meg; Gartrell, Kyungsook

2013-12-01

The authors examined the relationship of staff turnover to selected nursing home quality outcomes, in the context of staffing and skill mix. Staff turnover is a serious concern in nursing homes as it has been found to adversely affect care. When employee turnover is minimized, better care quality is more likely in nursing homes. Data from the National Nursing Home Survey, a nationally representative sample of US nursing homes, were linked to Nursing Home Compare quality outcomes and analyzed using logistic regression. Nursing homes with high certified nursing assistant turnover had significantly higher odds of pressure ulcers, pain, and urinary tract infections even after controlling for staffing, skill mix, bed size, and ownership. Nurse turnover was associated with twice the odds of pressure ulcers, although this was attenuated when staffing was controlled. This study suggests turnover may be more important in explaining nursing home (NH) outcomes than staffing and skill mix and should therefore be given greater emphasis.

Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.

PubMed

Mikulich-Gilbertson, Susan K; Wagner, Brandie D; Grunwald, Gary K; Riggs, Paula D; Zerbe, Gary O

2018-01-01

Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes predictors from a MGLMM are always preferable to scatterplots of empirical Bayes predictors generated by separate models, unless the true association between outcomes is zero.

Bioactive compounds, antioxidant potential, and hepatoprotective activity of sea cucumber (Holothuria atra) against thioacetamide intoxication in rats.

PubMed

Esmat, Amr Y; Said, Mahmoud M; Soliman, Amel A; El-Masry, Khaled S H; Badiea, Elham Abdel

2013-01-01

The identification of the active phenolic compounds in the mixed extract of sea cucumber (Holothuria atra) body wall by high-performance liquid chromatography and an assessment of its hepatoprotective activity against thioacetamide-induced liver fibrosis in rats. Female Swiss albino rats were divided into four groups: normal controls; oral administration of a sea cucumber mixed extract (14.4 mg/kg of body weight) on days 2, 4, and 6 weekly for 8 consecutive weeks; intoxication with thioacetamide (200 mg/kg of body weight, intraperitoneally) on days 2 and 6 weekly for 8 wk; and oral administration of a sea cucumber extract and then intoxication with thioacetamide 2 h later for 8 wk. High-performance liquid chromatographic analysis of the sea cucumber mixed extract revealed the presence of some phenolic components, such as chlorogenic acid, pyrogallol, rutin, coumaric acid, catechin, and ascorbic acid. In vitro studies have shown that the extract has a high scavenging activity for the nitric oxide radical, a moderate iron-chelating activity, and a weak inhibitory effect of lipid peroxidation. The subchronic oral administration of sea cucumber extract to the rats did not show any toxic side effects but increased hepatic superoxide dismutase and glutathione peroxidase activities. The coadministration of sea cucumber extract and thioacetamide (protection modality) normalized serum direct bilirubin, alanine and aspartate aminotransferases, hepatic malondialdehyde, and hydroxyproline concentrations and antioxidant enzyme activities. In addition, the histologic examination of liver sections from the protection group that were stained with hematoxylin and eosin showed substantial attenuation of the degenerative cellular changes and regressions in liver fibrosis and necrosis induced by the thioacetamide intoxication. Sea cucumber mixed extract contains physiologically active phenolic compounds with antioxidant activity, which afforded a potential hepatoprotective activity against thioacetamide-induced liver injury in a rat model. Copyright © 2013 Elsevier Inc. All rights reserved.

[LONG-TERM SURVIVAL OF DUAL DISORDERS PATIENTS AFTER MIXED CARE IN DUAL DISORDERS AND STANDARD WARDS VERSUS CARE ONLY IN DUAL DISORDERS WARD].

PubMed

Gimelfarb, Yuri; Wolf, Aviva; Ben-Tzarfati, Mashit

2017-01-01

Dual disorders (co-occurring mental illness and substance abuse disorders in the same person) are extremely common among patients receiving mental health services. Integrated treatment has been proposed as the standard of care and it describes a flexible combination of treatments from the mental health and addiction fields that are blended together in the therapy. Scientific evidence for survival of dual disorders patients (DDPs), who had integrated dual disorders inpatient care, is lacking. To determine the long term survival rates following integrated care (Integrated Dual Diagnosis Treatment Ward [IDDTW] only) versus mixed care (IDDTW and psychiatric wards) during the life-time of DDPs. The charts of 333 subjects admitted to IDDTW during the period January 2002 - June 2006 were assessed at least 8 years after the first admission. Psychiatric diagnoses have been established and grouped according to international classification of diseases and health-related problems -10th edition (ICD-10). The Kaplan-Meier survival analysis was used to estimate the cumulative survival rates in all the subpopulations, and the predictive values of different variables were assessed by Cox proportional-hazards regression model. The total all-cause 12-year, unadjusted mortality was 21.1% in integrated care versus 24.6% in mixed care (p<.68). The Cox regression was not revealed for integrated care as a predictive factor for all-cause mortality. The findings showed that there was no consistent evidence to support integrated inpatient care over mixed care, as measured by long-term survival. More studies are required in order to address the challenges posed in the treatment of DDPs.

Family size effects on childhood obesity: Evidence on the quantity-quality trade-off using the NLSY.

PubMed

Dasgupta, Kabir; Solomon, Keisha T

2018-05-01

In this study, we use matched mother-child data from the National Longitudinal Surveys to study the effects of family size on child health. Focusing on excess body weight indicators as children's health outcome of interest, we examine the effects of exogenous variations in family size generated by twin births and parental preference for mixed sex composition of their children. We find no significant empirical support in favor of the quantity-quality trade-off theory in instrumental variable regression analysis. This result is further substantiated when we make use of the panel aspects of the data to study child health outcomes of arrival of younger siblings at later parities. Specifically, when we employ child fixed effects analysis, results suggest that birth of a younger sibling is related to a decline in the likelihood of being overweight by 4 percentage points and a drop in the probability of illness by approximately 5 percentage points. Copyright © 2018 Elsevier B.V. All rights reserved.

Surveying End-of-Life Medical Decisions in France: Evaluation of an Innovative Mixed-Mode Data Collection Strategy

PubMed Central

Pennec, Sophie; Monnier, Alain; Stephan, Amandine; Brouard, Nicolas; Bilsen, Johan; Cohen, Joachim

2016-01-01

Background Monitoring medical decisions at the end of life has become an important issue in many societies. Built on previous European experiences, the survey and project Fin de Vie en France (“End of Life in France,” or EOLF) was conducted in 2010 to provide an overview of medical end-of-life decisions in France. Objective To describe the methodology of EOLF and evaluate the effects of design innovations on data quality. Methods EOLF used a mixed-mode data collection strategy (paper and Internet) along with follow-up campaigns that employed various contact modes (paper and telephone), all of which were gathered from various institutions (research team, hospital, and medical authorities at the regional level). A telephone nonresponse survey was also used. Through descriptive statistics and multivariate logistic regressions, these innovations were assessed in terms of their effects on the response rate, quality of the sample, and differences between Web-based and paper questionnaires. Results The participation rate was 40.0% (n=5217). The respondent sample was very close to the sampling frame. The Web-based questionnaires represented only 26.8% of the questionnaires, and the Web-based secured procedure led to limitations in data management. The follow-up campaigns had a strong effect on participation, especially for paper questionnaires. With higher participation rates (63.21% and 63.74%), the telephone follow-up and nonresponse surveys showed that only a very low proportion of physicians refused to participate because of the topic or the absence of financial incentive. A multivariate analysis showed that physicians who answered on the Internet reported less medication to hasten death, and that they more often took no medical decisions in the end-of-life process. Conclusions Varying contact modes is a useful strategy. Using a mixed-mode design is interesting, but selection and measurement effects must be studied further in this sensitive field. PMID:26892632

Predictors of aggression in 3.322 patients with affective disorders and schizophrenia spectrum disorders evaluated in an emergency department setting.

PubMed

Blanco, Emily A; Duque, Laura M; Rachamallu, Vivekananda; Yuen, Eunice; Kane, John M; Gallego, Juan A

2018-05-01

The aim of this study is to determine odds of aggression and associated factors in patients with schizophrenia-spectrum disorders (SSD) and affective disorders who were evaluated in an emergency department setting. A retrospective study was conducted using de-identified data from electronic medical records from 3.322 patients who were evaluated at emergency psychiatric settings. Data extracted included demographic information, variables related to aggression towards people or property in the past 6months, and other factors that could potentially impact the risk of aggression, such as comorbid diagnoses, physical abuse and sexual abuse. Bivariate analyses and multivariate regression analyses were conducted to determine the variables significantly associated with aggression. An initial multivariate regression analysis showed that SSD had 3.1 times the odds of aggression, while bipolar disorder had 2.2 times the odds of aggression compared to unipolar depression. A second regression analysis including bipolar subtypes showed, using unipolar depression as the reference group, that bipolar disorder with a recent mixed episode had an odds ratio (OR) of 4.3, schizophrenia had an OR of 2.6 and bipolar disorder with a recent manic episode had an OR of 2.2. Generalized anxiety disorder was associated with lower odds in both regression analyses. As a whole, the SSD group had higher odds of aggression than the bipolar disorder group. However, after subdividing the groups, schizophrenia had higher odds of aggression than bipolar disorder with a recent manic episode and lower odds of aggression than bipolar disorder with a recent mixed episode. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining Factors Influencing Attrition at a Small, Private, Selective Liberal Arts College

ERIC Educational Resources Information Center

Gansemer-Topf, Ann M.; Zhang, Yi; Beatty, Cameron C.; Paja, Scott

2014-01-01

Despite a diverse body of literature on college student retention, studies focusing on small, private, selective liberal arts colleges are limited. This study utilized a mixed methodology beginning with logistic regression analyses and followed with a qualitative inquiry that included interviews with students who had not persisted. While variables…

Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution

ERIC Educational Resources Information Center

Verkuilen, Jay; Smithson, Michael

2012-01-01

Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…

Revising Our Thinking about the Relationship between Maternal Labor Supply and Preschool

ERIC Educational Resources Information Center

Fitzpatrick, Maria Donovan

2012-01-01

Many argue that childcare costs limit the labor supply of mothers, though existing evidence has been mixed. Using a child's eligibility for public kindergarten in a regression discontinuity instrumental variables framework, I estimate how use of a particular subsidy, public school, affects maternal labor supply. I find public school enrollment…

Recycling and Ambivalence: Quantitative and Qualitative Analyses of Household Recycling among Young Adults

ERIC Educational Resources Information Center

Ojala, Maria

2008-01-01

Theories about ambivalence, as well as quantitative and qualitative empirical approaches, are applied to obtain an understanding of recycling among young adults. A questionnaire was mailed to 422 Swedish young people. Regression analyses showed that a mix of negative emotions (worry) and positive emotions (hope and joy) about the environmental…

Developing design methods of concrete mix with microsilica additives for road construction

NASA Astrophysics Data System (ADS)

Dmitrienko, Vladimir; Shrivel, Igor; Kokunko, Irina; Pashkova, Olga

2017-10-01

Based on the laboratory test results, regression equations having standard cone and concrete strength, to determine the available amount of cement, water and microsilica were obtained. The joint solution of these equations allowed the researchers to develop the algorithm of designing heavy concrete compositions with microsilica additives for road construction.

A Growth Model for Academic Program Life Cycle (APLC): A Theoretical and Empirical Analysis

ERIC Educational Resources Information Center

Acquah, Edward H. K.

2010-01-01

Academic program life cycle concept states each program's life flows through several stages: introduction, growth, maturity, and decline. A mixed-influence diffusion growth model is fitted to enrolment data on academic programs to analyze the factors determining progress of academic programs through their life cycles. The regression analysis yield…

Estimating leaf area and above-ground biomass of forest regeneration areas using a corrected normalized difference vegetation index

Treesearch

Tommy L. Coleman; James H. Miller; Bruce R. Zutter

1992-01-01

The objective of this study was to investigate the regression relations between vegetation indices derived from remotely-sensed data of single and mixed forest regeneration plots. Loblolly pine (Pinus taeda L.) seedlings, sweelgum (Liquidambar styraciflua L.) seedlings and broomsedge (Andropogon virginicus L.)...

Multi Objective Optimization of Multi Wall Carbon Nanotube Based Nanogrinding Wheel Using Grey Relational and Regression Analysis

NASA Astrophysics Data System (ADS)

Sethuramalingam, Prabhu; Vinayagam, Babu Kupusamy

2016-07-01

Carbon nanotube mixed grinding wheel is used in the grinding process to analyze the surface characteristics of AISI D2 tool steel material. Till now no work has been carried out using carbon nanotube based grinding wheel. Carbon nanotube based grinding wheel has excellent thermal conductivity and good mechanical properties which are used to improve the surface finish of the workpiece. In the present study, the multi response optimization of process parameters like surface roughness and metal removal rate of grinding process of single wall carbon nanotube (CNT) in mixed cutting fluids is undertaken using orthogonal array with grey relational analysis. Experiments are performed with designated grinding conditions obtained using the L9 orthogonal array. Based on the results of the grey relational analysis, a set of optimum grinding parameters is obtained. Using the analysis of variance approach the significant machining parameters are found. Empirical model for the prediction of output parameters has been developed using regression analysis and the results are compared empirically, for conditions of with and without CNT grinding wheel in grinding process.

Fungicide application practices and personal protective equipment use among orchard farmers in the agricultural health study.

PubMed

Hines, C J; Deddens, J A; Coble, J; Alavanja, M C R

2007-04-01

Fungicides are routinely applied to deciduous tree fruits for disease management. Seventy-four private orchard applicators enrolled in the Agricultural Health Study participated in the Orchard Fungicide Exposure Study in 2002-2003. During 144 days of observation, information was obtained on chemicals applied and applicator mixing, application, personal protective, and hygiene practices. At least half of the applicators had orchards with <100 trees. Air blast was the most frequent application method used (55%), followed by hand spray (44%). Rubber gloves were the most frequently worn protective equipment (68% mix; 59% apply), followed by respirators (45% mix; 49% apply), protective outerwear (36% mix; 37% apply), and rubber boots (35% mix; 36% apply). Eye protection was worn while mixing and applying on only 35% and 41% of the days, respectively. Bivariate analyses were performed using repeated logistic or repeated linear regression. Mean duration of mixing, pounds of captan applied, total acres sprayed, and number of tank mixes sprayed were greater for air blast than for hand spray (p < 0.05). Spraying from a tractor/vehicle without an enclosed cab was associated with wearing some type of coverall (p < 0.05). Applicators often did not wash their hands after mixing (77%), a finding not explained by glove use. Glove use during mixing was associated with younger age, while wearing long-sleeve shirts was associated with older age (p < 0.05 each). Self-reported unusually high fungicide exposures were more likely on days applicators performed repairs (p < 0.05). These data will be useful for evaluating fungicide exposure determinants among orchard applicators.

Growth rate characteristics of acidophilic heterotrophic organisms from mine waste rock piles

NASA Astrophysics Data System (ADS)

Yacob, T. W.; Silverstein, J.; Jenkins, J.; Andre, B. J.; Rajaram, H.

2010-12-01

Autotrophic iron oxidizing bacteria play a key role in pyrite oxidation and generation of acid mine drainage AMD. Scarcity of organic substrates in many disturbed sites insures that IOB have sufficient oxygen and other nutrients for growth. It is proposed that addition of organic carbon substrate to waste rock piles will result in enrichment of heterotrophic microorganisms limiting the role of IOB in AMD generation. Previous researchers have used the acidophilic heterotroph Acidiphilium cryptum as a model to study the effects of organic substrate addition on the pyrite oxidation/AMD cycle. In order to develop a quantitative model of effects such as competition for oxygen, it is necessary to use growth and substrate consumption rate expressions, and one approach is to choose a model strain such as A. cryptum for kinetic studies. However we have found that the growth rate characteristics of A. cryptum may not provide an accurate model of the remediation effects of organic addition to subsurface mined sites. Fluorescent in-situ hybridization (FISH) assays of extracts of mine waste rock enriched with glucose and yeast extract did not produce countable numbers of cells in the Acidiphilium genus, with a detection limit of3 x 104 cells/gram rock, despite evidence of the presence of well established heterotrophic organisms. However, an MPN enrichment produced heterotrophic population estimates of 1x107 and 1x109 cells/gram rock. Growth rate studies of A. cryptum showed that cultures took 120 hours to degrade 50% of an initial glucose concentration of 2,000 mg/L. However a mixed culture enriched from mine waste rock consumed 100% of the same amount of glucose in 24 hours. Substrate consumption data for the mixed culture were fit to a Monod growth model: {dS}/{dt} = μ_{max}S {( {X_0}/{Y} + S_0 -S )}/{(K_s +S)} Kinetic parameters were estimated utilizing a non linear regression method coupled with an ODE solver. The maximum specific growth rate of the mixed population with μ max was calculated to be 0.13 hr-1 and a yield of 0.52 g cells/g glucose and Ks of 0.2 g/L glucose. The effect of pH on growth was compared for A. cryptum and the mixed population. It was found that the mixed culture had a higher tolerance for extremely low pH conditions, with no growth at pH = 1; whereas no growth of A cryptum was observed at pH = 1.5. Both A. cryptum and the mixed cultures grew within a pH range of 2.5 - 6. A phospholipid fatty acid analysis (PLFA) of the mixed culture indicated that both eukaryotic and prokaryotic organisms are present at a ratio of approximately 1:1, indicating that organisms such as fungi may be important in carbon cycling in these acidic subsurface formations. The results from this research show that utilization of mixed wild cultures for environmental modeling may yield better results than selection of a single strain to represent populations in a quantitative model.

"Mad or bad?": burden on caregivers of patients with personality disorders.

PubMed

Bauer, Rita; Döring, Antje; Schmidt, Tanja; Spießl, Hermann

2012-12-01

The burden on caregivers of patients with personality disorders is often greatly underestimated or completely disregarded. Possibilities for caregiver support have rarely been assessed. Thirty interviews were conducted with caregivers of such patients to assess illness-related burden. Responses were analyzed with a mixed method of qualitative and quantitative analysis in a sequential design. Patient and caregiver data, including sociodemographic and disease-related variables, were evaluated with regression analysis and regression trees. Caregiver statements (n = 404) were summarized into 44 global statements. The most frequent global statements were worries about the burden on other family members (70.0%), poor cooperation with clinical centers and other institutions (60.0%), financial burden (56.7%), worry about the patient's future (53.3%), and dissatisfaction with the patient's treatment and rehabilitation (53.3%). Linear regression and regression tree analysis identified predictors for more burdened caregivers. Caregivers of patients with personality disorders experience a variety of burdens, some disorder specific. Yet these caregivers often receive little attention or support.

Evaluation of multisystemic therapy pilot services in the Systemic Therapy for At Risk Teens (START) trial: study protocol for a randomised controlled trial

PubMed Central

2013-01-01

Background There is an urgent need for clinically effective and cost-effective methods to manage antisocial and criminal behaviour in adolescents. Youth conduct disorder is increasingly prevalent in the UK and is associated with a range of negative outcomes. Quantitative systematic reviews carried out for the National Institute for Health and Clinical Excellence have identified multisystemic therapy, an intensive, multimodal, home-based, family intervention for youth with serious antisocial behaviour, as one of the most promising interventions for reducing antisocial or offending behaviour and improving individual and family functioning. Previous international trials of multisystemic therapy have yielded mixed outcomes, and it is questionable to what extent positive US findings can be generalised to a wider UK mental health and juvenile justice context. This paper describes the protocol for the Systemic Therapy for At Risk Teens (START) trial, a multicentre UK-wide randomised controlled trial of multisystemic therapy in antisocial adolescents at high risk of out-of-home placement. Methods/Design The trial is being conducted at 10 sites across the UK. Seven hundred participants and their families will be recruited and randomised on a 1:1 basis to multisystemic therapy or management as usual. Treatments are offered over a period of 3 to 5 months, with follow-up to 18 months post-randomisation. The primary outcome is out-of-home placement at 18 months. Secondary outcomes include offending rates, total service and criminal justice sector costs, and participant well-being and educational outcomes. Data will be gathered from police computer records, the National Pupil Database, and interview and self-report measures administered to adolescents, parents and teachers. Outcomes will be analysed on an intention-to-treat basis, using a logistic regression with random effects for the primary outcome and Cox regressions and linear mixed-effects models for secondary outcomes depending on whether the outcome is time-to-event or continuous. Discussion The START trial is a pragmatic national trial of sufficient size to evaluate multisystemic therapy, to inform policymakers, service commissioners, professionals, service users and their families about its potential in the UK. It will also provide data on the clinical and cost-effectiveness of usual services provided to youth with serious antisocial behaviour problems. Trial registration ISRCTN77132214 PMID:23962220

First and second year medical students identify and self-stereotype more as doctors than as students: a questionnaire study.

PubMed

Burford, Bryan; Rosenthal-Stott, Harriet E S

2017-11-13

The emergence of medical students' professional identity is important. This paper considers this in a snapshot of the early years of undergraduate medical education. From the perspective of social identity theory, it also considers self-stereotyping, the extent to which individuals associate with attributes identified as typical of groups. Paper questionnaires were completed by first and second year medical students following teaching sessions at the beginning (October) and end (April) of the academic year. Questionnaires consisted of scales measuring the strength and importance of identity and self-stereotyping, referent to 'doctors' and 'students'. Linear mixed effects regression considered longitudinal and cross-sectional effects of progress through the course, and differences in responses to 'doctor' and 'student' measures. In October, responses were received from 99% (n = 102) and 75% (n = 58) of first and second year cohorts respectively, and in April from 81% (n = 83) and 73% (n = 56). Response rates were over 95% of those present. Linear mixed effects regression found that all 'doctor'-referent measures were higher than 'student' measures. Strength of identity and self-stereotyping decreased between beginning and end of the year (across both groups). Men indicated lower importance of identity than women, also across both groups. There were no differences between year groups. Self-stereotyping was predicted more by importance of identification with a group than by strength of identification. Findings reinforce observations that medical students identify strongly as doctors from early in their studies, and that this identification is greater than as students. Decreases over time are surprising, but may be explained by changing group salience towards the end of the academic year. The lack of a gender effect on strength of identification contrasts with the literature, but may reflect students' lack of 'performance' of professional identity, while the effect on importance is speculated to be linked to social identity complexity. Identification with professional group may have implications for how medical schools treat students. The findings on self-stereotyping have relevance to recruitment if applicant populations are limited to those already internalising a stereotype. There may be consequences for the wellbeing of those who feel they cannot fulfil stereotypes when in training.

Evaluation of multisystemic therapy pilot services in the Systemic Therapy for At Risk Teens (START) trial: study protocol for a randomised controlled trial.

PubMed

Fonagy, Peter; Butler, Stephen; Goodyer, Ian; Cottrell, David; Scott, Stephen; Pilling, Stephen; Eisler, Ivan; Fuggle, Peter; Kraam, Abdullah; Byford, Sarah; Wason, James; Haley, Rachel

2013-08-20

There is an urgent need for clinically effective and cost-effective methods to manage antisocial and criminal behaviour in adolescents. Youth conduct disorder is increasingly prevalent in the UK and is associated with a range of negative outcomes. Quantitative systematic reviews carried out for the National Institute for Health and Clinical Excellence have identified multisystemic therapy, an intensive, multimodal, home-based, family intervention for youth with serious antisocial behaviour, as one of the most promising interventions for reducing antisocial or offending behaviour and improving individual and family functioning. Previous international trials of multisystemic therapy have yielded mixed outcomes, and it is questionable to what extent positive US findings can be generalised to a wider UK mental health and juvenile justice context. This paper describes the protocol for the Systemic Therapy for At Risk Teens (START) trial, a multicentre UK-wide randomised controlled trial of multisystemic therapy in antisocial adolescents at high risk of out-of-home placement. The trial is being conducted at 10 sites across the UK. Seven hundred participants and their families will be recruited and randomised on a 1:1 basis to multisystemic therapy or management as usual. Treatments are offered over a period of 3 to 5 months, with follow-up to 18 months post-randomisation. The primary outcome is out-of-home placement at 18 months. Secondary outcomes include offending rates, total service and criminal justice sector costs, and participant well-being and educational outcomes. Data will be gathered from police computer records, the National Pupil Database, and interview and self-report measures administered to adolescents, parents and teachers. Outcomes will be analysed on an intention-to-treat basis, using a logistic regression with random effects for the primary outcome and Cox regressions and linear mixed-effects models for secondary outcomes depending on whether the outcome is time-to-event or continuous. The START trial is a pragmatic national trial of sufficient size to evaluate multisystemic therapy, to inform policymakers, service commissioners, professionals, service users and their families about its potential in the UK. It will also provide data on the clinical and cost-effectiveness of usual services provided to youth with serious antisocial behaviour problems. ISRCTN77132214.

Impact of new technologies on stress, attrition and well-being in emergency call centers: the NextGeneration 9-1-1 study protocol.

PubMed

Baseman, Janet; Revere, Debra; Painter, Ian; Stangenes, Scott; Lilly, Michelle; Beaton, Randal; Calhoun, Rebecca; Meischke, Hendrika

2018-05-04

Our public health emergency response system relies on the "first of the first responders"-the emergency call center workforce that handles the emergency needs of a public in distress. Call centers across the United States have been preparing for the "Next Generation 9-1-1" initiative, which will allow citizens to place 9-1-1 calls using a variety of digital technologies. The impacts of this initiative on a workforce that is already highly stressed is unknown. There is concern that these technology changes will increase stress, reduce job performance, contribute to maladaptive coping strategies, lower employee retention, or change morale in the workplace. Understanding these impacts to inform approaches for mitigating the health and performance risks associated with new technologies is crucial for ensuring the 911 system fulfills its mission of providing optimal emergency response to the public. Our project is an observational, prospective cohort study framed by the first new technology that will be implemented: text-to-911 calling. Emergency center call takers will be recruited nationwide. Data will be collected by online surveys distributed at each center before text-to-911 implementation; within the first month of implementation; and 6 months after implementation. Primary outcome measures are stress as measured by the Calgary Symptoms of Stress Index, use of sick leave, job performance, and job satisfaction. Primary analyses will use mixed effects regression models and mixed effects logistic regression models to estimate the change in outcome variables associated with text-to-911 implementation. Multiple secondary analyses will examine effects of stress on absenteeism; associations between technology attitudes and stress; effects of implementation on attitudes towards technology; and mitigating effects of job demands, job satisfaction, attitudes towards workplace technology and workplace support on change in stress. Our public health dependence on this workforce for our security and safety makes it imperative that the impact of technological changes such as text-to-911 are researched so appropriate intervention efforts to can be developed. Failing to protect our 9-1-1 call takers from predictable health risks would be similar to knowingly exposing field emergency responders to a toxic situation without following OSHA required training and practice standards assuring their protection.

Mangroves Enhance Reef Fish Abundance at the Caribbean Regional Scale.

PubMed

Serafy, Joseph E; Shideler, Geoffrey S; Araújo, Rafael J; Nagelkerken, Ivan

2015-01-01

Several studies conducted at the scale of islands, or small sections of continental coastlines, have suggested that mangrove habitats serve to enhance fish abundances on coral reefs, mainly by providing nursery grounds for several ontogenetically-migrating species. However, evidence of such enhancement at a regional scale has not been reported, and recently, some researchers have questioned the mangrove-reef subsidy effect. In the present study, using two different regression approaches, we pursued two questions related to mangrove-reef connectivity at the Caribbean regional scale: (1) Are reef fish abundances limited by mangrove forest area?; and (2) Are mean reef fish abundances proportional to mangrove forest area after taking human population density and latitude into account? Specifically, we tested for Caribbean-wide mangrove forest area effects on the abundances of 12 reef fishes that have been previously characterized as "mangrove-dependent". Analyzed were data from an ongoing, long-term (20-year) citizen-scientist fish monitoring program; coastal human population censuses; and several wetland forest information sources. Quantile regression results supported the notion that mangrove forest area limits the abundance of eight of the 12 fishes examined. Linear mixed-effects regression results, which considered potential human (fishing and habitat degradation) and latitudinal influences, suggested that average reef fish densities of at least six of the 12 focal fishes were directly proportional to mangrove forest area. Recent work questioning the mangrove-reef fish subsidy effect likely reflects a failure to: (1) focus analyses on species that use mangroves as nurseries, (2) consider more than the mean fish abundance response to mangrove forest extent; and/or (3) quantitatively account for potentially confounding human impacts, such as fishing pressure and habitat degradation. Our study is the first to demonstrate at a large regional scale (i.e., the Wider Caribbean) that greater mangrove forest size generally functions to increase the densities on neighboring reefs of those fishes that use these shallow, vegetated habitats as nurseries.

Mangroves Enhance Reef Fish Abundance at the Caribbean Regional Scale

PubMed Central

Serafy, Joseph E.; Shideler, Geoffrey S.; Araújo, Rafael J.; Nagelkerken, Ivan

2015-01-01

Several studies conducted at the scale of islands, or small sections of continental coastlines, have suggested that mangrove habitats serve to enhance fish abundances on coral reefs, mainly by providing nursery grounds for several ontogenetically-migrating species. However, evidence of such enhancement at a regional scale has not been reported, and recently, some researchers have questioned the mangrove-reef subsidy effect. In the present study, using two different regression approaches, we pursued two questions related to mangrove-reef connectivity at the Caribbean regional scale: (1) Are reef fish abundances limited by mangrove forest area?; and (2) Are mean reef fish abundances proportional to mangrove forest area after taking human population density and latitude into account? Specifically, we tested for Caribbean-wide mangrove forest area effects on the abundances of 12 reef fishes that have been previously characterized as “mangrove-dependent”. Analyzed were data from an ongoing, long-term (20-year) citizen-scientist fish monitoring program; coastal human population censuses; and several wetland forest information sources. Quantile regression results supported the notion that mangrove forest area limits the abundance of eight of the 12 fishes examined. Linear mixed-effects regression results, which considered potential human (fishing and habitat degradation) and latitudinal influences, suggested that average reef fish densities of at least six of the 12 focal fishes were directly proportional to mangrove forest area. Recent work questioning the mangrove-reef fish subsidy effect likely reflects a failure to: (1) focus analyses on species that use mangroves as nurseries, (2) consider more than the mean fish abundance response to mangrove forest extent; and/or (3) quantitatively account for potentially confounding human impacts, such as fishing pressure and habitat degradation. Our study is the first to demonstrate at a large regional scale (i.e., the Wider Caribbean) that greater mangrove forest size generally functions to increase the densities on neighboring reefs of those fishes that use these shallow, vegetated habitats as nurseries. PMID:26536478

Walkability parameters, active transportation and objective physical activity: moderating and mediating effects of motor vehicle ownership in a cross-sectional study

PubMed Central

2012-01-01

Background Neighborhood walkability has been associated with physical activity in several studies. However, as environmental correlates of physical activity may be context specific, walkability parameters need to be investigated separately in various countries and contexts. Furthermore, the mechanisms by which walkability affects physical activity have been less investigated. Based on previous research, we hypothesized that vehicle ownership is a potential mediator. We investigated the associations between walkability parameters and physical activity, and the mediating and moderating effects of vehicle ownership on these associations in a large sample of Swedish adults. Methods Residential density, street connectivity and land use mix were assessed within polygon-based network buffers (using Geographic Information Systems) for 2,178 men and women. Time spent in moderate to vigorous physical activity was assessed by accelerometers, and walking and cycling for transportation were assessed by the International Physical Activity Questionnaire. Associations were examined by linear regression and adjusted for socio-demographic characteristics. The product of coefficients approach was used to investigate the mediating effect of vehicle ownership. Results Residential density and land use mix, but not street connectivity, were significantly associated with time spent in moderate to vigorous physical activity and walking for transportation. Cycling for transportation was not associated with any of the walkability parameters. Vehicle ownership mediated a significant proportion of the association between the walkability parameters and physical activity outcomes. For residential density, vehicle ownership mediated 25% of the association with moderate to vigorous physical activity and 20% of the association with the amount of walking for transportation. For land use mix, the corresponding proportions were 34% and 14%. Vehicle ownership did not moderate any of the associations between the walkability parameters and physical activity outcomes. Conclusions Residential density and land use mix were associated with time spent in moderate to vigorous physical activity and walking for transportation. Vehicle ownership was a mediator but not a moderator of these associations. The present findings may be useful for policy makers and city planners when designing neighborhoods that promote physical activity. PMID:23035633

Walkability parameters, active transportation and objective physical activity: moderating and mediating effects of motor vehicle ownership in a cross-sectional study.

PubMed

Eriksson, Ulf; Arvidsson, Daniel; Gebel, Klaus; Ohlsson, Henrik; Sundquist, Kristina

2012-10-05

Neighborhood walkability has been associated with physical activity in several studies. However, as environmental correlates of physical activity may be context specific, walkability parameters need to be investigated separately in various countries and contexts. Furthermore, the mechanisms by which walkability affects physical activity have been less investigated. Based on previous research, we hypothesized that vehicle ownership is a potential mediator. We investigated the associations between walkability parameters and physical activity, and the mediating and moderating effects of vehicle ownership on these associations in a large sample of Swedish adults. Residential density, street connectivity and land use mix were assessed within polygon-based network buffers (using Geographic Information Systems) for 2,178 men and women. Time spent in moderate to vigorous physical activity was assessed by accelerometers, and walking and cycling for transportation were assessed by the International Physical Activity Questionnaire. Associations were examined by linear regression and adjusted for socio-demographic characteristics. The product of coefficients approach was used to investigate the mediating effect of vehicle ownership. Residential density and land use mix, but not street connectivity, were significantly associated with time spent in moderate to vigorous physical activity and walking for transportation. Cycling for transportation was not associated with any of the walkability parameters. Vehicle ownership mediated a significant proportion of the association between the walkability parameters and physical activity outcomes. For residential density, vehicle ownership mediated 25% of the association with moderate to vigorous physical activity and 20% of the association with the amount of walking for transportation. For land use mix, the corresponding proportions were 34% and 14%. Vehicle ownership did not moderate any of the associations between the walkability parameters and physical activity outcomes. Residential density and land use mix were associated with time spent in moderate to vigorous physical activity and walking for transportation. Vehicle ownership was a mediator but not a moderator of these associations. The present findings may be useful for policy makers and city planners when designing neighborhoods that promote physical activity.

Anti-tumor effects of nitrosylcobalamin against spontaneous tumors in dogs.

PubMed

Bauer, Joseph A; Frye, Gerald; Bahr, Anne; Gieg, Jennifer; Brofman, Peter

2010-10-01

Given the limited options available to treat canine cancers, the use of companion animals for evaluating new drugs may identify better therapies for veterinary and human oncology. The anti-tumor effects of nitrosylcobalamin (NO-Cbl), an apoptosis-inducing, vitamin B12-based carrier of nitric oxide (NO), was evaluated in four dogs with spontaneous cancer. (1) A 13 year-old female spayed Giant Schnauzer with inoperable thyroid carcinoma and hypercalcemia. (2) A 6 year-old male neutered Golden Retriever with a malignant peripheral nerve sheath tumor (MPNST). (3) A ten yr-old neutered male Bichon Frise with apocrine gland anal sac adenocarcinoma (AGACA). (4) A 7 year-old female spayed Labrador mix with spinal meningioma following partial surgical resection. Tumor regression was measured by physical exam and verified using ultrasound (case 1) and MRI (case 2-4). Serum chemistries and hematologic parameters were monitored throughout the studies. (1) The Giant Schnauzer demonstrated a 77% reduction in tumor volume after ten weeks of daily NO-Cbl treatment. (2) The Golden Retriever demonstrated a 53% reduction in tumor volume after 15 months of daily NO-Cbl therapy. (3) The Bichon Frise demonstrated a 43% regression of the primary tumor and a 90% regression of an iliac lymph node measured by MRI after 15 months of treatment. After 61 months, the dog currently has stable disease, normal liver enzymes, CBC analysis, and no evidence of toxicity. (4) The Labrador demonstrated complete regression of the residual tumor after 6 months of treatment. We have shown previously that NO-Cbl is endocytosed by malignant cells, resulting in intra-tumoral NO release. In this study, we have shown that daily long-term use of NO-Cbl induced responses in all dogs without any signs of toxicity. The use of NO-Cbl capitalizes on the tumor-specific properties of the vitamin B12 receptor and represents a promising anti-cancer therapy.

Blood Glucose Reduction by Diabetic Drugs with Minimal Hypoglycemia Risk for Cardiovascular Outcomes: Evidence from Meta-regression Analysis of Randomized Controlled Trials.

PubMed

Huang, Chi-Jung; Wang, Wei-Ting; Sung, Shih-Hsien; Chen, Chen-Huan; Lip, Gregory Yh; Cheng, Hao-Min; Chiang, Chern-En

2018-05-02

To investigate the effects of blood glucose control with antihyperglycemic agents with minimal hypoglycemia risk on cardiovascular outcomes in patients with type 2 diabetes (T2D). Randomized controlled trials (RCTs) comparing the relative efficacy and safety of antidiabetic drugs with less hypoglycemia risk were comprehensively searched in MEDLINE, Embase, and the Cochrane Library up to January 27, 2018. Mixed-effects meta-regression analysis was conducted to explore the relationship between haemoglobin A1c (HbA1c) reduction and the risk of major adverse cardiovascular events (MACE), myocardial infarction, stroke, cardiovascular death, all-cause death, and hospitalization for heart failure. Ten RCTs comprising 92400 participants with T2D were included and provided information on 9773 MACE during a median follow-up of 2.6 years. The mean HbA1c concentration was 0.42% lower (median, 0.27-0.86%) for participants given antihyperglycemic agents than those given placebo. The meta-regression analysis demonstrated that HbA1c reduction was significantly associated with a decreased risk of MACE (β value, -0.39 to -0.55; P<0.02) even after adjusting for each of the following possible confounding factors including age, sex, baseline HbA1c, duration of follow-up, difference in achieved systolic blood pressure, difference in achieved body weight, or risk difference in hypoglycemia. Lowering HbA1c by 1% conferred a significant risk reduction of 30% (95% CI, 17-40%) for MACE. By contrast, the meta-regression analysis for trials using conventional agents failed to demonstrate a significant relationship between achieved HbA1c difference and MACE risk (P>0.74). Compared with placebo, newer T2D agents with less hypoglycemic hazard significantly reduced the risk of MACE. The MACE reduction seems to be associated with HbA1c reduction in a linear relationship. This article is protected by copyright. All rights reserved.

Negative correlation between altitudes and oxygen isotope ratios of seeds: exploring its applicability to assess vertical seed dispersal.

PubMed

Naoe, Shoji; Tayasu, Ichiro; Masaki, Takashi; Koike, Shinsuke

2016-10-01

Vertical seed dispersal, which plays a key role in plant escape and/or expansion under climate change, was recently evaluated for the first time using negative correlation between altitudes and oxygen isotope ratio of seeds. Although this method is innovative, its applicability to other plants is unknown. To explore the applicability of the method, we regressed altitudes on δ 18 O of seeds of five woody species constituting three families in temperate forests in central Japan. Because climatic factors, including temperature and precipitation that influence δ 18 O of plant materials, demonstrate intensive seasonal fluctuation in the temperate zone, we also evaluated the effect of fruiting season of each species on δ 18 O of seeds using generalized linear mixed models (GLMM). Negative correlation between altitudes and δ 18 O of seeds was found in four of five species tested. The slope of regression lines tended to be lower in late-fruiting species. The GLMM analysis revealed that altitudes and date of fruiting peak negatively affected δ 18 O of seeds. These results indicate that the estimation of vertical seed dispersal using δ 18 O of seeds can be applicable for various species, not just confined to specific taxa, by identifying the altitudes of plants that produced seeds. The results also suggest that the regression line between altitudes and δ 18 O of seeds is rather species specific and that vertical seed dispersal in late-fruiting species is estimated at a low resolution due to their small regression slopes. A future study on the identification of environmental factors and plant traits that cause a difference in δ 18 O of seeds, combined with an improvement of analysis, will lead to effective evaluation of vertical seed dispersal in various species and thereby promote our understanding about the mechanism and ecological functions of vertical seed dispersal.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

PubMed Central

Müller, Christian; Schillert, Arne; Röthemeier, Caroline; Trégouët, David-Alexandre; Proust, Carole; Binder, Harald; Pfeiffer, Norbert; Beutel, Manfred; Lackner, Karl J.; Schnabel, Renate B.; Tiret, Laurence; Wild, Philipp S.; Blankenberg, Stefan

2016-01-01

Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data. PMID:27272489

Cost-effectiveness of cell saver in short-segment lumbar laminectomy and fusion (≤3 levels).

PubMed

Kelly, Patrick D; Parker, Scott L; Mendenhall, Stephen K; Bible, Jesse E; Sivasubramaniam, Priya; Shau, David N; McGirt, Matthew J; Devin, Clinton J

2015-09-01

Mixed retrospective-prospective cohort study. To characterize practice patterns for the use of Cell Saver at our institution, investigate its cost-effectiveness, and propose a new tool for patient selection. Blood loss is an exceedingly common complication of spine surgery, and Cell Saver intraoperative cell salvage has been used to decrease reliance on allogeneic blood transfusions for blood volume replacement. The cost-effectiveness of Cell Saver has not been established for lumbar spinal surgery, and no universal guidelines exist for clinicians to decide when to utilize this tool. Other authors have proposed cutoffs for anticipated blood loss volumes which indicate that Cell Saver should be used. Five hundred and eight patients undergoing lumbar laminectomy in 3 or fewer levels were reviewed from our prospective spinal outcomes registry. Cost information for Cell Saver and allogeneic transfusions was collected from our institution's billing and collections department. Logistic regression was used to identify patient characteristics associated with use of Cell Saver. An incremental cost effectiveness ratio was calculated based on transfusion and cost data. A clinical prediction score was derived using logistic regression. Use of Cell Saver correlated with increased age, higher body mass index, diabetes, greater American Society of Anesthesiologists classification, and greater number of previous spine surgeries. Outcomes for patients who did and did not have Cell Saver set up intraoperatively were equivocal. Cell Saver was not cost effective based on current usage patterns, but may become cost effective if used for patients with high expected blood loss. A simple clinical prediction rule is proposed which may aid in selection of patients to have Cell Saver present intraoperatively. Cell Saver is not a cost-effective intervention but may become cost effective if a threshold of expected intraoperative blood loss is used to select patients more judiciously. 3.

Prediction of utilizable true protein of mixed rations for sheep using an in vitro incubation technique.

PubMed

Li, Yuan-Xiao; Zhao, Guang-Yong

2007-04-01

The objective of the present experiment was to study the relationship between in vitro utilizable true protein (uTP) and in vivo-uTP of sheep rations by regression analysis. A further aim was to analyse if in vivo-uTP of mixed rations could be predicted by regression analysis between in vitro-uTP and in vivo-uTP, using N-retention of sheep as important evaluation criteria of protein value. Three adult male sheep (body weight [BW] 46 + 1.3 kg) fitted with rumen cannulas and simple T-type duodenal cannulas were fed with twelve typical rations with graded levels of crude protein and true protein in four experiments according a 3 x 3 Latin square design. Each experimental period included an adaptation (7 days), a N balance trial (4 days) and a collection of duodenal digesta (3 days). During collection of duodenal digesta, polyethylene glycol and chromium oxide were used as dual markers for the measurement of duodenal digesta flow and calculation of the in vivo-uTP of duodenal digesta. The in vitro-uTP of the rations was determined using the in vitro incubation technique of Zhao and Lebzien (2000). It was found that both in vitro-uTP intake and in vivo-uTP intake were significantly correlated with N-retention (p < 0.001) and that there was a significant linear relationship between the content of in vitro-uTP and in vivo-uTP in rations (p < 0.001). Therefore, it was concluded that the used in vitro incubation technique is suitable for the determination of in vitro-uTP of mixed rations for sheep, and that the amount of in vivo-uTP can be predicted by regression between in vitro-uTP and in vivo-uTP.

Self-rated health: small area large area comparisons amongst older adults at the state, district and sub-district level in India.

PubMed

Hirve, Siddhivinayak; Vounatsou, Penelope; Juvekar, Sanjay; Blomstedt, Yulia; Wall, Stig; Chatterji, Somnath; Ng, Nawi

2014-03-01

We compared prevalence estimates of self-rated health (SRH) derived indirectly using four different small area estimation methods for the Vadu (small) area from the national Study on Global AGEing (SAGE) survey with estimates derived directly from the Vadu SAGE survey. The indirect synthetic estimate for Vadu was 24% whereas the model based estimates were 45.6% and 45.7% with smaller prediction errors and comparable to the direct survey estimate of 50%. The model based techniques were better suited to estimate the prevalence of SRH than the indirect synthetic method. We conclude that a simplified mixed effects regression model can produce valid small area estimates of SRH. © 2013 Published by Elsevier Ltd.

Does smoking affect body weight and obesity in China?

PubMed

Fang, Hai; Ali, Mir M; Rizzo, John A

2009-12-01

An inverse relationship between smoking and body weight has been documented in the medical literature, but the effect of cigarette smoking on obesity remains inconclusive. In addition, the evidence is mixed on whether rising obesity rates are an unintended consequence of successful anti-smoking policies. This study re-examines these relationships using data from China, the largest consumer and manufacturer of tobacco in the world that is also experiencing a steady rise in obesity rates. We focus on the impact of the total number of cigarettes smoked per day on individuals' body mass index (BMI) and on the likelihood of being overweight and obese. Instrumental variables estimation is used to correct for the endogeneity of cigarette smoking. We find a moderate negative and significant relationship between cigarette smoking and BMI. Smoking is also negatively related to being overweight and obese, but the marginal effects are small and statistically insignificant for being obese. Quantile regression analyses reveal that the association between smoking and BMI is quite weak among subjects whose BMIs are at the high end of the distribution but are considerably stronger among subjects in the healthy weight range. Ordered probit regression analyses also confirm these findings. Our results thus reconcile an inverse average effect of smoking on body weight with the absence of any significant effect on obesity. From a policy perspective these findings suggest that, while smoking cessation may lead to moderate weight gain among subjects of healthy weight, the effects on obese subjects are modest and should not be expected to lead to a large increase in obesity prevalence rates.

Racial Differences in Satisfaction with VA Health Care: A Mixed Methods Pilot Study.

PubMed

Zickmund, Susan L; Burkitt, Kelly H; Gao, Shasha; Stone, Roslyn A; Rodriguez, Keri L; Switzer, Galen E; Shea, Judy A; Bayliss, Nichole K; Meiksin, Rebecca; Walsh, Mary B; Fine, Michael J

2015-09-01

As satisfied patients are more adherent and play a more active role in their own care, a better understanding of factors associated with patient satisfaction is important. In response to a United States Veterans Administration (VA) Hospital Report Card that revealed lower levels of satisfaction with health care for African Americans compared to Whites, we conducted a mixed methods pilot study to obtain preliminary qualitative and quantitative information about possible underlying reasons for these racial differences. We conducted telephone interviews with 30 African American and 31 White veterans with recent inpatient and/or outpatient health care visits at three urban VA Medical Centers. We coded the qualitative interviews in terms of identified themes within defined domains. We summarized racial differences using ordinal logistic regression for Likert scale outcomes and used random effects logistic regression to assess racial differences at the domain level. Compared to Whites, African Americans were younger (p < 0.001) and better educated (p = 0.04). Qualitatively, African Americans reported less satisfaction with trust/confidence in their VA providers and healthcare system and less satisfaction with patient-provider communication. Quantitatively, African Americans reported less satisfaction with outpatient care (odds ratio = 0.28; 95 % confidence interval (CI) 0.10-0.82), but not inpatient care. At the domain level, African Americans were significantly less likely than Whites to express satisfaction themes in the domain of trust/confidence (odds ratio = 0.36; 95 % CI 0.18-0.73). The current pilot study demonstrates racial differences in satisfaction with outpatient care and identifies some specific sources of dissatisfaction. Future research will include a large national cohort, including Hispanic veterans, in order to gain further insight into the sources of racial and ethnic differences in satisfaction with VA care and inform future interventions.

Dissecting HIV Virulence: Heritability of Setpoint Viral Load, CD4+ T-Cell Decline, and Per-Parasite Pathogenicity.

PubMed

Bertels, Frederic; Marzel, Alex; Leventhal, Gabriel; Mitov, Venelin; Fellay, Jacques; Günthard, Huldrych F; Böni, Jürg; Yerly, Sabine; Klimkait, Thomas; Aubert, Vincent; Battegay, Manuel; Rauch, Andri; Cavassini, Matthias; Calmy, Alexandra; Bernasconi, Enos; Schmid, Patrick; Scherrer, Alexandra U; Müller, Viktor; Bonhoeffer, Sebastian; Kouyos, Roger; Regoes, Roland R

2018-01-01

Pathogen strains may differ in virulence because they attain different loads in their hosts, or because they induce different disease-causing mechanisms independent of their load. In evolutionary ecology, the latter is referred to as "per-parasite pathogenicity". Using viral load and CD4+ T-cell measures from 2014 HIV-1 subtype B-infected individuals enrolled in the Swiss HIV Cohort Study, we investigated if virulence-measured as the rate of decline of CD4+ T cells-and per-parasite pathogenicity are heritable from donor to recipient. We estimated heritability by donor-recipient regressions applied to 196 previously identified transmission pairs, and by phylogenetic mixed models applied to a phylogenetic tree inferred from HIV pol sequences. Regressing the CD4+ T-cell declines and per-parasite pathogenicities of the transmission pairs did not yield heritability estimates significantly different from zero. With the phylogenetic mixed model, however, our best estimate for the heritability of the CD4+ T-cell decline is 17% (5-30%), and that of the per-parasite pathogenicity is 17% (4-29%). Further, we confirm that the set-point viral load is heritable, and estimate a heritability of 29% (12-46%). Interestingly, the pattern of evolution of all these traits differs significantly from neutrality, and is most consistent with stabilizing selection for the set-point viral load, and with directional selection for the CD4+ T-cell decline and the per-parasite pathogenicity. Our analysis shows that the viral genotype affects virulence mainly by modulating the per-parasite pathogenicity, while the indirect effect via the set-point viral load is minor. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Dissecting HIV Virulence: Heritability of Setpoint Viral Load, CD4+ T-Cell Decline, and Per-Parasite Pathogenicity

PubMed Central

Bertels, Frederic; Marzel, Alex; Leventhal, Gabriel; Mitov, Venelin; Fellay, Jacques; Günthard, Huldrych F; Böni, Jürg; Yerly, Sabine; Klimkait, Thomas; Aubert, Vincent; Battegay, Manuel; Rauch, Andri; Cavassini, Matthias; Calmy, Alexandra; Bernasconi, Enos; Schmid, Patrick; Scherrer, Alexandra U; Müller, Viktor; Bonhoeffer, Sebastian; Kouyos, Roger; Regoes, Roland R

2018-01-01

Abstract Pathogen strains may differ in virulence because they attain different loads in their hosts, or because they induce different disease-causing mechanisms independent of their load. In evolutionary ecology, the latter is referred to as “per-parasite pathogenicity”. Using viral load and CD4+ T-cell measures from 2014 HIV-1 subtype B-infected individuals enrolled in the Swiss HIV Cohort Study, we investigated if virulence—measured as the rate of decline of CD4+ T cells—and per-parasite pathogenicity are heritable from donor to recipient. We estimated heritability by donor–recipient regressions applied to 196 previously identified transmission pairs, and by phylogenetic mixed models applied to a phylogenetic tree inferred from HIV pol sequences. Regressing the CD4+ T-cell declines and per-parasite pathogenicities of the transmission pairs did not yield heritability estimates significantly different from zero. With the phylogenetic mixed model, however, our best estimate for the heritability of the CD4+ T-cell decline is 17% (5–30%), and that of the per-parasite pathogenicity is 17% (4–29%). Further, we confirm that the set-point viral load is heritable, and estimate a heritability of 29% (12–46%). Interestingly, the pattern of evolution of all these traits differs significantly from neutrality, and is most consistent with stabilizing selection for the set-point viral load, and with directional selection for the CD4+ T-cell decline and the per-parasite pathogenicity. Our analysis shows that the viral genotype affects virulence mainly by modulating the per-parasite pathogenicity, while the indirect effect via the set-point viral load is minor. PMID:29029206

Using quantile regression to examine the effects of inequality across the mortality distribution in the U.S. counties

PubMed Central

Yang, Tse-Chuan; Chen, Vivian Yi-Ju; Shoff, Carla; Matthews, Stephen A.

2012-01-01

The U.S. has experienced a resurgence of income inequality in the past decades. The evidence regarding the mortality implications of this phenomenon has been mixed. This study employs a rarely used method in mortality research, quantile regression (QR), to provide insight into the ongoing debate of whether income inequality is a determinant of mortality and to investigate the varying relationship between inequality and mortality throughout the mortality distribution. Analyzing a U.S. dataset where the five-year (1998–2002) average mortality rates were combined with other county-level covariates, we found that the association between inequality and mortality was not constant throughout the mortality distribution and the impact of inequality on mortality steadily increased until the 80th percentile. When accounting for all potential confounders, inequality was significantly and positively related to mortality; however, this inequality–mortality relationship did not hold across the mortality distribution. A series of Wald tests confirmed this varying inequality–mortality relationship, especially between the lower and upper tails. The large variation in the estimated coefficients of the Gini index suggested that inequality had the greatest influence on those counties with a mortality rate of roughly 9.95 deaths per 1000 population (80th percentile) compared to any other counties. Furthermore, our results suggest that the traditional analytic methods that focus on mean or median value of the dependent variable can be, at most, applied to a narrow 20 percent of observations. This study demonstrates the value of QR. Our findings provide some insight as to why the existing evidence for the inequality–mortality relationship is mixed and suggest that analytical issues may play a role in clarifying whether inequality is a robust determinant of population health. PMID:22497847

Patterns of Drug Use, Risky Behavior, and Health Status Among Persons Who Inject Drugs Living in San Diego, California: A Latent Class Analysis

PubMed Central

Roth, Alexis M.; Armenta, Richard A.; Wagner, Karla D.; Roesch, Scott C.; Bluthenthal, Ricky N.; Cuevas-Mota, Jazmine; Garfein, Richard S.

2015-01-01

Background Among persons who inject drugs (PWID), polydrug use (the practice of mixing multiple drugs/alcohol sequentially or simultaneously) increases risk for HIV transmission and unintentional overdose deaths. Research has shown local drug markets influence drug use practices. However, little is known about the impact of drug mixing in markets dominated by black tar heroin and methamphetamine, such as the western United States. Methods Data were collected through an ongoing longitudinal study examining drug use, risk behavior, and health status among PWID. Latent class analysis (LCA) was used to identify patterns of substance use (heroin, methamphetamine, prescription drugs, alcohol, and marijuana) via multiple administration routes (injecting, smoking, and swallowing). Logistic regression was used to identify behaviors and health indicators associated with drug use class. Results The sample included 511 mostly white (51.5%) males (73.8%), with mean age of 43.5 years. Two distinct classes of drug users predominated: methamphetamine by multiple routes (51%) and heroin by injection (49%). In multivariable logistic regression, class membership was associated with age, race, and housing status. PWID who were HIV-seropositive and reported prior sexually transmitted infections had increased odds of belonging to the methamphetamine class. Those who were HCV positive and reported previous opioid overdose had an increased odds of being in the primarily heroin injection class (all P-values < .05). Conclusion Risk behaviors and health outcomes differed between PWID who primarily inject heroin vs. those who use methamphetamine. The findings suggest that in a region where PWID mainly use black tar heroin or methamphetamine, interventions tailored to sub-populations of PWID could improve effectiveness. PMID:25313832

Follow-up and timeliness after an abnormal cancer screening among underserved, urban women in a patient navigation program

PubMed Central

Markossian, Talar W.; Darnell, Julie S.; Calhoun, Elizabeth A.

2012-01-01

Background We evaluated the efficacy of a Chicago-based cancer patient navigation program developed to increase the proportion of patients reaching diagnostic resolution and reduce the time from abnormal screening test to definitive diagnostic resolution. Methods Women with an abnormal breast (n=352) or cervical (n=545) cancer screening test were recruited for the quasi-experimental study. Navigation subjects originated from five federally qualified health center sites and one safety net hospital. Records-based concurrent control subjects were selected from 20 sites. Control sites had similar characteristics to the navigated sites in terms of patient volume, racial/ethnic composition, and payor mix. Mixed-effects logistic regression and Cox proportional hazard regression analyses were conducted to compare navigation and control patients reaching diagnostic resolution by 60 days and time to resolution, adjusting for demographic covariates and site. Results Compared to controls, the breast navigation group had shorter time to diagnostic resolution (aHR=1.65, CI=1.20–2.28) and the cervical navigation group had shorter time to diagnostic resolution for those who resolved after 30 days (aHR= 2.31, CI=1.75–3.06), with no difference before 30 days (aHR= 1.42, CI=0.83–2.43). Variables significantly associated with longer time to resolution for breast cancer screening abnormalities were being older, never partnered, abnormal mammogram and BI-RADS 3, and being younger and Black for cervical abnormalities. Conclusions Patient navigation reduces time from abnormal cancer finding to definitive diagnosis in underserved women. Impact Results support efforts to use patient navigation as a strategy to reduce cancer disparities among socioeconomically disadvantaged women. PMID:23045544

Follow-up and timeliness after an abnormal cancer screening among underserved, urban women in a patient navigation program.

PubMed

Markossian, Talar W; Darnell, Julie S; Calhoun, Elizabeth A

2012-10-01

We evaluated the efficacy of a Chicago-based cancer patient navigation program developed to increase the proportion of patients reaching diagnostic resolution and reduce the time from abnormal screening test to definitive diagnostic resolution. Women with an abnormal breast (n = 352) or cervical (n = 545) cancer screening test were recruited for the quasi-experimental study. Navigation subjects originated from five federally qualified health center sites and one safety net hospital. Records-based concurrent control subjects were selected from 20 sites. Control sites had similar characteristics to the navigated sites in terms of patient volume, racial/ethnic composition, and payor mix. Mixed-effects logistic regression and Cox proportional hazard regression analyses were conducted to compare navigation and control patients reaching diagnostic resolution by 60 days and time to resolution, adjusting for demographic covariates and site. Compared with controls, the breast navigation group had shorter time to diagnostic resolution (aHR = 1.65, CI = 1.20-2.28) and the cervical navigation group had shorter time to diagnostic resolution for those who resolved after 30 days (aHR = 2.31, CI = 1.75-3.06), with no difference before 30 days (aHR = 1.42, CI = 0.83-2.43). Variables significantly associated with longer time to resolution for breast cancer screening abnormalities were being older, never partnered, abnormal mammogram and BI-RADS 3, and being younger and Black for cervical abnormalities. Patient navigation reduces time from abnormal cancer finding to definitive diagnosis in underserved women. Results support efforts to use patient navigation as a strategy to reduce cancer disparities among socioeconomically disadvantaged women. 2012 AACR

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks.

PubMed

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  < .001), and Gini coefficients and number of posts (0.342-0.725, p  < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p  < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t  = 3.346-7.381, p  < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t  = -4.305 and -5.934, p  < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

IMPACT: Investigating the impact of Models of Practice for Allied health Care in subacuTe settings. A protocol for a quasi-experimental mixed methods study of cost effectiveness and outcomes for patients exposed to different models of allied health care.

PubMed

Coker, Freya; Williams, Cylie M; Taylor, Nicholas F; Caspers, Kirsten; McAlinden, Fiona; Wilton, Anita; Shields, Nora; Haines, Terry P

2018-05-10

This protocol considers three allied health staffing models across public health subacute hospitals. This quasi-experimental mixed-methods study, including qualitative process evaluation, aims to evaluate the impact of additional allied health services in subacute care, in rehabilitation and geriatric evaluation management settings, on patient, health service and societal outcomes. This health services research will analyse outcomes of patients exposed to different allied health models of care at three health services. Each health service will have a control ward (routine care) and an intervention ward (additional allied health). This project has two parts. Part 1: a whole of site data extraction for included wards. Outcome measures will include: length of stay, rate of readmissions, discharge destinations, community referrals, patient feedback and staff perspectives. Part 2: Functional Independence Measure scores will be collected every 2-3 days for the duration of 60 patient admissions.Data from part 1 will be analysed by linear regression analysis for continuous outcomes using patient-level data and logistic regression analysis for binary outcomes. Qualitative data will be analysed using a deductive thematic approach. For part 2, a linear mixed model analysis will be conducted using therapy service delivery and days since admission to subacute care as fixed factors in the model and individual participant as a random factor. Graphical analysis will be used to examine the growth curve of the model and transformations. The days since admission factor will be used to examine non-linear growth trajectories to determine if they lead to better model fit. Findings will be disseminated through local reports and to the Department of Health and Human Services Victoria. Results will be presented at conferences and submitted to peer-reviewed journals. The Monash Health Human Research Ethics committee approved this multisite research (HREC/17/MonH/144 and HREC/17/MonH/547). © 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.

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

The "Nursing Home Compare" measure of urinary/fecal incontinence: cross-sectional variation, stability over time, and the impact of case mix.

PubMed

Li, Yue; Schnelle, John; Spector, William D; Glance, Laurent G; Mukamel, Dana B

2010-02-01

To assess the impact of facility case mix on cross-sectional variations and short-term stability of the "Nursing Home Compare" incontinence quality measure (QM) and to determine whether multivariate risk adjustment can minimize such impacts. Retrospective analyses of the 2005 national minimum data set (MDS) that included approximately 600,000 long-term care residents in over 10,000 facilities in each quarterly sample. Mixed logistic regression was used to construct the risk-adjusted QM (nonshrinkage estimator). Facility-level ordinary least-squares models and adjusted R(2) were used to estimate the impact of case mix on cross-sectional and short-term longitudinal variations of currently published and risk-adjusted QMs. At least 50 percent of the cross-sectional variation and 25 percent of the short-term longitudinal variation of the published QM are explained by facility case mix. In contrast, the cross-sectional and short-term longitudinal variations of the risk-adjusted QM are much less susceptible to case-mix variations (adjusted R(2)<0.10), even for facilities with more extreme or more unstable outcome. Current "Nursing Home Compare" incontinence QM reflects considerable case-mix variations across facilities and over time, and therefore it may be biased. This issue can be largely addressed by multivariate risk adjustment using risk factors available in the MDS.

Optimization of Orifice Geometry for Cross-Flow Mixing in a Cylindrical Duct

NASA Technical Reports Server (NTRS)

Kroll, J. T.; Sowa, W. A.; Samuelsen, G. S.

1996-01-01

Mixing of gaseous jets in a cross-flow has significant applications in engineering, one example of which is the dilution zone of a gas turbine combustor. Despite years of study, the design of the jet injection in combustors is largely based on practical experience. The emergence of NO(x) regulations for stationary gas turbines and the anticipation of aero-engine regulations requires an improved understanding of jet mixing as new combustor concepts are introduced. For example, the success of the staged combustor to reduce the emission of NO(x) is almost entirely dependent upon the rapid and complete dilution of the rich zone products within the mixing section. It is these mixing challenges to which the present study is directed. A series of experiments was undertaken to delineate the optimal mixer orifice geometry. A cross-flow to core-flow momentum-flux ratio of 40 and a mass flow ratio of 2.5 were selected as representative of a conventional design. An experimental test matrix was designed around three variables: the number of orifices, the orifice length-to- width ratio, and the orifice angle. A regression analysis was performed on the data to arrive at an interpolating equation that predicted the mixing performance of orifice geometry combinations within the range of the test matrix parameters. Results indicate that the best mixing orifice geometry tested involves eight orifices with a long-to-short side aspect ratio of 3.5 at a twenty-three degree inclination from the center-line of the mixing section.

When patients govern: federal grant funding and uncompensated care at federally qualified health centers.

PubMed

Wright, Brad; Ricketts, Thomas C

2013-05-01

To determine if the proportion of consumers on federally qualified health center (FQHC) governing boards is associated with their use of federal grant funds to provide uncompensated care. Using FQHC data from the Uniform Data System, county-level data from the Area Resource File and governing board data from FQHC grant applications, the uncompensated care an FQHC provides relative to the amount of its federal funding is modeled as a function of board and executive committee composition using fixed-effects regression with FQHC and county-level controls. Consumer governance does not predict how much uncompensated care an FQHC provides relative to the size of its federal grant. Rather, the proportion of an FQHC's patient-mix that is uninsured drives uncompensated care provision. Aside from a small executive committee effect, consumer governance does not influence FQHCs' provision of uncompensated care. More work is needed to understand the role of consumer governance.

Estimating the Prevalence of Childhood Obesity in Alaska Using Partial, Nonrandom Measurement Data

PubMed Central

Boles, Myde; Fink, Karol; Topol, Rebecca; Fenaughty, Andrea

2016-01-01

Although monitoring childhood obesity prevalence is critical for state public health programs to assess trends and the effectiveness of interventions, few states have comprehensive body mass index measurement systems in place. In some states, however, assorted school districts collect measurements on student height and weight as part of annual health screenings. To estimate childhood obesity prevalence in Alaska, we created a logistic regression model using such annual measurements along with public data on demographics and socioeconomic status. Our mixed-effects model-generated prevalence estimates validated well against weighted estimates, with 95% confidence intervals overlapping between methodologies among 7 of 8 participating school districts. Our methodology accounts for variation in school-level and student-level demographic factors across the state, and the approach we describe can be applied by other states that have existing nonrandom student measurement data to estimate childhood obesity prevalence. PMID:27010843

Predicting Upscaled Behavior of Aqueous Reactants in Heterogeneous Porous Media

NASA Astrophysics Data System (ADS)

Wright, E. E.; Hansen, S. K.; Bolster, D.; Richter, D. H.; Vesselinov, V. V.

2017-12-01

When modeling reactive transport, reaction rates are often overestimated due to the improper assumption of perfect mixing at the support scale of the transport model. In reality, fronts tend to form between participants in thermodynamically favorable reactions, leading to segregation of reactants into islands or fingers. When such a configuration arises, reactions are limited to the interface between the reactive solutes. Closure methods for estimating control-volume-effective reaction rates in terms of quantities defined at the control volume scale do not presently exist, but their development is crucial for effective field-scale modeling. We attack this problem through a combination of analytical and numerical means. Specifically, we numerically study reactive transport through an ensemble of realizations of two-dimensional heterogeneous porous media. We then employ regression analysis to calibrate an analytically-derived relationship between reaction rate and various dimensionless quantities representing conductivity-field heterogeneity and the respective strengths of diffusion, reaction and advection.

Paying for Primary Care: The Factors Associated with Physician Self-selection into Payment Models.

PubMed

Rudoler, David; Deber, Raisa; Barnsley, Janet; Glazier, Richard H; Dass, Adrian Rohit; Laporte, Audrey

2015-09-01

To determine the factors associated with primary care physician self-selection into different payment models, we used a panel of eight waves of administrative data for all primary care physicians who practiced in Ontario between 2003/2004 and 2010/2011. We used a mixed effects logistic regression model to estimate physicians' choice of three alternative payment models: fee for service, enhanced fee for service, and blended capitation. We found that primary care physicians self-selected into payment models based on existing practice characteristics. Physicians with more complex patient populations were less likely to switch into capitation-based payment models where higher levels of effort were not financially rewarded. These findings suggested that investigations aimed at assessing the impact of different primary care reimbursement models on outcomes, including costs and access, should first account for potential selection effects. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating life expectancies for US small areas: a regression framework

NASA Astrophysics Data System (ADS)

Congdon, Peter

2014-01-01

Analysis of area mortality variations and estimation of area life tables raise methodological questions relevant to assessing spatial clustering, and socioeconomic inequalities in mortality. Existing small area analyses of US life expectancy variation generally adopt ad hoc amalgamations of counties to alleviate potential instability of mortality rates involved in deriving life tables, and use conventional life table analysis which takes no account of correlated mortality for adjacent areas or ages. The alternative strategy here uses structured random effects methods that recognize correlations between adjacent ages and areas, and allows retention of the original county boundaries. This strategy generalizes to include effects of area category (e.g. poverty status, ethnic mix), allowing estimation of life tables according to area category, and providing additional stabilization of estimated life table functions. This approach is used here to estimate stabilized mortality rates, derive life expectancies in US counties, and assess trends in clustering and in inequality according to county poverty category.

Does competitive employment improve nonvocational outcomes for people with severe mental illness?

PubMed

Bond, G R; Resnick, S G; Drake, R E; Xie, H; McHugo, G J; Bebout, R R

2001-06-01

The authors examined the cumulative effects of work on symptoms, quality of life, and self-esteem for 149 unemployed clients with severe mental illness receiving vocational rehabilitation. Nonvocational measures were assessed at 6-month intervals throughout the 18-month study period, and vocational activity was tracked continuously. On the basis of their predominant work activity over the study period, participants were classified into 4 groups: competitive work, sheltered work, minimal work, and no work. The groups did not differ at baseline on any of the nonvocational measures. Using mixed effects regression analysis to examine rates of change over time, the authors found that the competitive work group showed higher rates of improvement in symptoms; in satisfaction with vocational services, leisure, and finances; and in self-esteem than did participants in a combined minimal work-no work group. The sheltered work group showed no such advantage.

[Theory, method and application of method R on estimation of (co)variance components].

PubMed

Liu, Wen-Zhong

2004-07-01

Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.

[Experience in treating patients with chronic obstructive bronchitis with fenspirid].

PubMed

Kirichenko, A A; Shabanova, T M

2002-01-01

To study a clinical effect of fenspirid and its impact on external respiration function in patients with chronic obstructive bronchitis (COB) in the exacerbation phase. 30 COB patients participated in the trial (20 males, 10 females, age 39-80 years). The severity of clinical symptoms (cough, sputum, dyspnea) was studied using special scales. External respiration function was examined by a spirometric system "Tamrac system spiro sense Y2 14". Fenspirid treatment was conducted in a dose 80 mg twice a day for 3 months. Control examinations were made 2 weeks, 1 and 3 months after the treatment start. A 3-month treatment with fenspirid resulted in regression of COB symptoms: cough and sputum ceased, dyspnea decreased. This led to improvement in external respiration function, especially in patients with mixed ventilatory disorders with prevailing restriction. Fenspirid is an effective and well tolerated treatment of chronic obstructive bronchitis.