Sample records for adjusted regression analyses

  1. Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

    PubMed Central

    Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

    2014-01-01

    In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

  2. Difficulties with Regression Analysis of Age-Adjusted Rates.

    DTIC Science & Technology

    1982-09-01

    variables used in those analyses, such as death rates in various states, have been age adjusted, whereas the predictor variables have not been age adjusted...The use of crude state death rates as the outcome variable with crude covariates and age as predictors can avoid the problem, at least under some...should be regressed on age-adjusted exposure Z+B+ Although age-specific death rates , Yas+’ may be available, it is often difficult to obtain age

  3. Alternatives for using multivariate regression to adjust prospective payment rates

    PubMed Central

    Sheingold, Steven H.

    1990-01-01

    Multivariate regression analysis has been used in structuring three of the adjustments to Medicare's prospective payment rates. Because the indirect-teaching adjustment, the disproportionate-share adjustment, and the adjustment for large cities are responsible for distributing approximately $3 billion in payments each year, the specification of regression models for these adjustments is of critical importance. In this article, the application of regression for adjusting Medicare's prospective rates is discussed, and the implications that differing specifications could have for these adjustments are demonstrated. PMID:10113271

  4. Adjusted variable plots for Cox's proportional hazards regression model.

    PubMed

    Hall, C B; Zeger, S L; Bandeen-Roche, K J

    1996-01-01

    Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.

  5. Procedures for adjusting regional regression models of urban-runoff quality using local data

    USGS Publications Warehouse

    Hoos, A.B.; Sisolak, J.K.

    1993-01-01

    Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for

  6. Adjusted regression trend test for a multicenter clinical trial.

    PubMed

    Quan, H; Capizzi, T

    1999-06-01

    Studies using a series of increasing doses of a compound, including a zero dose control, are often conducted to study the effect of the compound on the response of interest. For a one-way design, Tukey et al. (1985, Biometrics 41, 295-301) suggested assessing trend by examining the slopes of regression lines under arithmetic, ordinal, and arithmetic-logarithmic dose scalings. They reported the smallest p-value for the three significance tests on the three slopes for safety assessments. Capizzi et al. (1992, Biometrical Journal 34, 275-289) suggested an adjusted trend test, which adjusts the p-value using a trivariate t-distribution, the joint distribution of the three slope estimators. In this paper, we propose an adjusted regression trend test suitable for two-way designs, particularly for multicenter clinical trials. In a step-down fashion, the proposed trend test can be applied to a multicenter clinical trial to compare each dose with the control. This sequential procedure is a closed testing procedure for a trend alternative. Therefore, it adjusts p-values and maintains experimentwise error rate. Simulation results show that the step-down trend test is overall more powerful than a step-down least significant difference test.

  7. Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

    PubMed

    Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

    2017-01-01

    Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  8. Adjustment of regional regression equations for urban storm-runoff quality using at-site data

    USGS Publications Warehouse

    Barks, C.S.

    1996-01-01

    Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.

  9. Weather adjustment using seemingly unrelated regression

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

    Noll, T.A.

    1995-05-01

    Seemingly unrelated regression (SUR) is a system estimation technique that accounts for time-contemporaneous correlation between individual equations within a system of equations. SUR is suited to weather adjustment estimations when the estimation is: (1) composed of a system of equations and (2) the system of equations represents either different weather stations, different sales sectors or a combination of different weather stations and different sales sectors. SUR utilizes the cross-equation error values to develop more accurate estimates of the system coefficients than are obtained using ordinary least-squares (OLS) estimation. SUR estimates can be generated using a variety of statistical software packagesmore » including MicroTSP and SAS.« less

  10. Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

    PubMed

    Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

    2016-01-01

    Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

  11. Using Quantile and Asymmetric Least Squares Regression for Optimal Risk Adjustment.

    PubMed

    Lorenz, Normann

    2017-06-01

    In this paper, we analyze optimal risk adjustment for direct risk selection (DRS). Integrating insurers' activities for risk selection into a discrete choice model of individuals' health insurance choice shows that DRS has the structure of a contest. For the contest success function (csf) used in most of the contest literature (the Tullock-csf), optimal transfers for a risk adjustment scheme have to be determined by means of a restricted quantile regression, irrespective of whether insurers are primarily engaged in positive DRS (attracting low risks) or negative DRS (repelling high risks). This is at odds with the common practice of determining transfers by means of a least squares regression. However, this common practice can be rationalized for a new csf, but only if positive and negative DRSs are equally important; if they are not, optimal transfers have to be calculated by means of a restricted asymmetric least squares regression. Using data from German and Swiss health insurers, we find considerable differences between the three types of regressions. Optimal transfers therefore critically depend on which csf represents insurers' incentives for DRS and, if it is not the Tullock-csf, whether insurers are primarily engaged in positive or negative DRS. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

    PubMed

    Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

    2009-11-01

    G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

  13. An evaluation of bias in propensity score-adjusted non-linear regression models.

    PubMed

    Wan, Fei; Mitra, Nandita

    2018-03-01

    Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.

  14. Direct comparison of risk-adjusted and non-risk-adjusted CUSUM analyses of coronary artery bypass surgery outcomes.

    PubMed

    Novick, Richard J; Fox, Stephanie A; Stitt, Larry W; Forbes, Thomas L; Steiner, Stefan

    2006-08-01

    We previously applied non-risk-adjusted cumulative sum methods to analyze coronary bypass outcomes. The objective of this study was to assess the incremental advantage of risk-adjusted cumulative sum methods in this setting. Prospective data were collected in 793 consecutive patients who underwent coronary bypass grafting performed by a single surgeon during a period of 5 years. The composite occurrence of an "adverse outcome" included mortality or any of 10 major complications. An institutional logistic regression model for adverse outcome was developed by using 2608 contemporaneous patients undergoing coronary bypass. The predicted risk of adverse outcome in each of the surgeon's 793 patients was then calculated. A risk-adjusted cumulative sum curve was then generated after specifying control limits and odds ratio. This risk-adjusted curve was compared with the non-risk-adjusted cumulative sum curve, and the clinical significance of this difference was assessed. The surgeon's adverse outcome rate was 96 of 793 (12.1%) versus 270 of 1815 (14.9%) for all the other institution's surgeons combined (P = .06). The non-risk-adjusted curve reached below the lower control limit, signifying excellent outcomes between cases 164 and 313, 323 and 407, and 667 and 793, but transgressed the upper limit between cases 461 and 478. The risk-adjusted cumulative sum curve never transgressed the upper control limit, signifying that cases preceding and including 461 to 478 were at an increased predicted risk. Furthermore, if the risk-adjusted cumulative sum curve was reset to zero whenever a control limit was reached, it still signaled a decrease in adverse outcome at 166, 653, and 782 cases. Risk-adjusted cumulative sum techniques provide incremental advantages over non-risk-adjusted methods by not signaling a decrement in performance when preoperative patient risk is high.

  15. Money illusion among health care providers: should we adjust for inflation in analyses of provider behavior?

    PubMed

    Mayer, M L; Rozier, R G

    2000-08-01

    This analysis questions the appropriateness of inflation adjustment in analyses of provider behavior by comparing results from estimations using adjusted financial variables with those from estimations using unadjusted financial variables. Using Medicaid claims from 1984-1991, we explored the effects of Medicaid reimbursement increases on dentists' participation. Using results from inflation adjusted analyses, we would conclude that a 23% nominal increase in Medicaid reimbursement rates yields no increase in the number of Medicaid children seen by dentists. In contrast, estimations based on unadjusted reimbursement rates suggest that this same 23% nominal increase in reimbursement leads to an expected 16-person (15.4%) increase in the number of Medicaid patients seen per provider per year. These analyses demonstrate that results are sensitive to adjustment for inflation. While adjusting for inflation is a generally accepted practice in health services research, doing so without evidence that providers respond to adjusted reimbursement may be unjustified. More research is needed to determine the appropriateness of inflation adjustment in analyses of provider behavior, and the circumstances under which it should or should not be done.

  16. On causal interpretation of race in regressions adjusting for confounding and mediating variables

    PubMed Central

    VanderWeele, Tyler J.; Robinson, Whitney R.

    2014-01-01

    We consider several possible interpretations of the “effect of race” when regressions are run with race as an exposure variable, controlling also for various confounding and mediating variables. When adjustment is made for socioeconomic status early in a person’s life, we discuss under what contexts the regression coefficients for race can be interpreted as corresponding to the extent to which a racial inequality would remain if various socioeconomic distributions early in life across racial groups could be equalized. When adjustment is also made for adult socioeconomic status, we note how the overall racial inequality can be decomposed into the portion that would be eliminated by equalizing adult socioeconomic status across racial groups and the portion of the inequality that would remain even if adult socioeconomic status across racial groups were equalized. We also discuss a stronger interpretation of the “effect of race” (stronger in terms of assumptions) involving the joint effects of race-associated physical phenotype (e.g. skin color), parental physical phenotype, genetic background and cultural context when such variables are thought to be hypothetically manipulable and if adequate control for confounding were possible. We discuss some of the challenges with such an interpretation. Further discussion is given as to how the use of selected populations in examining racial disparities can additionally complicate the interpretation of the effects. PMID:24887159

  17. Random regression analyses using B-splines to model growth of Australian Angus cattle

    PubMed Central

    Meyer, Karin

    2005-01-01

    Regression on the basis function of B-splines has been advocated as an alternative to orthogonal polynomials in random regression analyses. Basic theory of splines in mixed model analyses is reviewed, and estimates from analyses of weights of Australian Angus cattle from birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 animals in 43 herds, with a high proportion of animals with 4 or more weights recorded. Changes in weights with age were modelled through B-splines of age at recording. A total of thirteen analyses, considering different combinations of linear, quadratic and cubic B-splines and up to six knots, were carried out. Results showed good agreement for all ages with many records, but fluctuated where data were sparse. On the whole, analyses using B-splines appeared more robust against "end-of-range" problems and yielded more consistent and accurate estimates of the first eigenfunctions than previous, polynomial analyses. A model fitting quadratic B-splines, with knots at 0, 200, 400, 600 and 821 days and a total of 91 covariance components, appeared to be a good compromise between detailedness of the model, number of parameters to be estimated, plausibility of results, and fit, measured as residual mean square error. PMID:16093011

  18. A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

    PubMed

    Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne

    2016-11-03

    Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the

  19. Adjustment of regional regression models of urban-runoff quality using data for Chattanooga, Knoxville, and Nashville, Tennessee

    USGS Publications Warehouse

    Hoos, Anne B.; Patel, Anant R.

    1996-01-01

    Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.

  20. Regression Analysis of Optical Coherence Tomography Disc Variables for Glaucoma Diagnosis.

    PubMed

    Richter, Grace M; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Chopra, Vikas; Greenfield, David S; Varma, Rohit; Schuman, Joel S; Huang, David

    2016-08-01

    To report diagnostic accuracy of optical coherence tomography (OCT) disc variables using both time-domain (TD) and Fourier-domain (FD) OCT, and to improve the use of OCT disc variable measurements for glaucoma diagnosis through regression analyses that adjust for optic disc size and axial length-based magnification error. Observational, cross-sectional. In total, 180 normal eyes of 112 participants and 180 eyes of 138 participants with perimetric glaucoma from the Advanced Imaging for Glaucoma Study. Diagnostic variables evaluated from TD-OCT and FD-OCT were: disc area, rim area, rim volume, optic nerve head volume, vertical cup-to-disc ratio (CDR), and horizontal CDR. These were compared with overall retinal nerve fiber layer thickness and ganglion cell complex. Regression analyses were performed that corrected for optic disc size and axial length. Area-under-receiver-operating curves (AUROC) were used to assess diagnostic accuracy before and after the adjustments. An index based on multiple logistic regression that combined optic disc variables with axial length was also explored with the aim of improving diagnostic accuracy of disc variables. Comparison of diagnostic accuracy of disc variables, as measured by AUROC. The unadjusted disc variables with the highest diagnostic accuracies were: rim volume for TD-OCT (AUROC=0.864) and vertical CDR (AUROC=0.874) for FD-OCT. Magnification correction significantly worsened diagnostic accuracy for rim variables, and while optic disc size adjustments partially restored diagnostic accuracy, the adjusted AUROCs were still lower. Axial length adjustments to disc variables in the form of multiple logistic regression indices led to a slight but insignificant improvement in diagnostic accuracy. Our various regression approaches were not able to significantly improve disc-based OCT glaucoma diagnosis. However, disc rim area and vertical CDR had very high diagnostic accuracy, and these disc variables can serve to complement

  1. What We Have Learned from the Recent Meta-analyses on Diagnostic Methods for Atherosclerotic Plaque Regression.

    PubMed

    Biondi-Zoccai, Giuseppe; Mastrangeli, Simona; Romagnoli, Enrico; Peruzzi, Mariangela; Frati, Giacomo; Roever, Leonardo; Giordano, Arturo

    2018-01-17

    Atherosclerosis has major morbidity and mortality implications globally. While it has often been considered an irreversible degenerative process, recent evidence provides compelling proof that atherosclerosis can be reversed. Plaque regression is however difficult to appraise and quantify, with competing diagnostic methods available. Given the potential of evidence synthesis to provide clinical guidance, we aimed to review recent meta-analyses on diagnostic methods for atherosclerotic plaque regression. We identified 8 meta-analyses published between 2015 and 2017, including 79 studies and 14,442 patients, followed for a median of 12 months. They reported on atherosclerotic plaque regression appraised with carotid duplex ultrasound, coronary computed tomography, carotid magnetic resonance, coronary intravascular ultrasound, and coronary optical coherence tomography. Overall, all meta-analyses showed significant atherosclerotic plaque regression with lipid-lowering therapy, with the most notable effects on echogenicity, lipid-rich necrotic core volume, wall/plaque volume, dense calcium volume, and fibrous cap thickness. Significant interactions were found with concomitant changes in low density lipoprotein cholesterol, high density lipoprotein cholesterol, and C-reactive protein levels, and with ethnicity. Atherosclerotic plaque regression and conversion to a stable phenotype is possible with intensive medical therapy and can be demonstrated in patients using a variety of non-invasive and invasive imaging modalities.

  2. Three methods to construct predictive models using logistic regression and likelihood ratios to facilitate adjustment for pretest probability give similar results.

    PubMed

    Chan, Siew Foong; Deeks, Jonathan J; Macaskill, Petra; Irwig, Les

    2008-01-01

    To compare three predictive models based on logistic regression to estimate adjusted likelihood ratios allowing for interdependency between diagnostic variables (tests). This study was a review of the theoretical basis, assumptions, and limitations of published models; and a statistical extension of methods and application to a case study of the diagnosis of obstructive airways disease based on history and clinical examination. Albert's method includes an offset term to estimate an adjusted likelihood ratio for combinations of tests. Spiegelhalter and Knill-Jones method uses the unadjusted likelihood ratio for each test as a predictor and computes shrinkage factors to allow for interdependence. Knottnerus' method differs from the other methods because it requires sequencing of tests, which limits its application to situations where there are few tests and substantial data. Although parameter estimates differed between the models, predicted "posttest" probabilities were generally similar. Construction of predictive models using logistic regression is preferred to the independence Bayes' approach when it is important to adjust for dependency of tests errors. Methods to estimate adjusted likelihood ratios from predictive models should be considered in preference to a standard logistic regression model to facilitate ease of interpretation and application. Albert's method provides the most straightforward approach.

  3. 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.

  4. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

    PubMed

    Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

    2016-12-01

    : MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We

  5. Factors influencing psychosocial adjustment and quality of life in Parkinson patients and informal caregivers.

    PubMed

    Navarta-Sánchez, María Victoria; Senosiain García, Juana M; Riverol, Mario; Ursúa Sesma, María Eugenia; Díaz de Cerio Ayesa, Sara; Anaut Bravo, Sagrario; Caparrós Civera, Neus; Portillo, Mari Carmen

    2016-08-01

    The influence that social conditions and personal attitudes may have on the quality of life (QoL) of Parkinson's disease (PD) patients and informal caregivers does not receive enough attention in health care, as a result of it not being clearly identified, especially in informal caregivers. The aim of this study was to provide a comprehensive analysis of psychosocial adjustment and QoL determinants in PD patients and informal caregivers. Ninety-one PD patients and 83 caregivers participated in the study. Multiple regression analyses were performed including benefit finding, coping, disease severity and socio-demographic factors, in order to determine how these aspects influence the psychosocial adjustment and QoL in PD patients and caregivers. Regression models showed that severity of PD was the main predictor of psychosocial adjustment and QoL in patients. Nevertheless, multiple regression analyses also revealed that coping was a significant predictor of psychosocial adjustment in patients and caregivers. Furthermore, psychosocial adjustment was significantly related to QoL in patients and caregivers. Also, coping and benefit finding were predictors of QoL in caregivers but not in patients. Multidisciplinary interventions aimed at improving PD patients' QoL may have more effective outcomes if education about coping skills, and how these can help towards a positive psychosocial adjustment to illness, were included, and targeted not only at patients, but also at informal caregivers.

  6. Shrinkage regression-based methods for microarray missing value imputation.

    PubMed

    Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

    2013-01-01

    Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

  7. Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

    Treesearch

    John W. Edwards; Susan C. Loeb; David C. Guynn

    1994-01-01

    Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

  8. The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care.

    PubMed

    Taljaard, Monica; McKenzie, Joanne E; Ramsay, Craig R; Grimshaw, Jeremy M

    2014-06-19

    An interrupted time series design is a powerful quasi-experimental approach for evaluating effects of interventions introduced at a specific point in time. To utilize the strength of this design, a modification to standard regression analysis, such as segmented regression, is required. In segmented regression analysis, the change in intercept and/or slope from pre- to post-intervention is estimated and used to test causal hypotheses about the intervention. We illustrate segmented regression using data from a previously published study that evaluated the effectiveness of a collaborative intervention to improve quality in pre-hospital ambulance care for acute myocardial infarction (AMI) and stroke. In the original analysis, a standard regression model was used with time as a continuous variable. We contrast the results from this standard regression analysis with those from segmented regression analysis. We discuss the limitations of the former and advantages of the latter, as well as the challenges of using segmented regression in analysing complex quality improvement interventions. Based on the estimated change in intercept and slope from pre- to post-intervention using segmented regression, we found insufficient evidence of a statistically significant effect on quality of care for stroke, although potential clinically important effects for AMI cannot be ruled out. Segmented regression analysis is the recommended approach for analysing data from an interrupted time series study. Several modifications to the basic segmented regression analysis approach are available to deal with challenges arising in the evaluation of complex quality improvement interventions.

  9. Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: Evidence from Quantile Regression Analyses

    ERIC Educational Resources Information Center

    Shafiq, M. Najeeb

    2011-01-01

    Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15 year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

  10. Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

    PubMed

    Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

    2016-10-01

    In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value <0.001). However, the flexible piecewise exponential model showed the smallest overdispersion parameter (3.2 versus 21.3) for non-flexible piecewise exponential models. We showed that there were no major differences between methods. However, using a flexible piecewise regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

  11. Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

    PubMed

    Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

    2009-04-01

    Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

  12. Disability and Coping as Predictors of Psychological Adjustment to Rheumatoid Arthritis.

    ERIC Educational Resources Information Center

    Revenson, Tracey A.; Felton, Barbara J.

    1989-01-01

    Examined degree to which self-reported functional disability and coping efforts contributed to psychological adjustment among 45 rheumatoid arthritis patients over six months. Hierarchical multiple regression analyses indicated that increases in disability were related to decreased acceptance of illness and increased negative affect, while coping…

  13. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

    PubMed Central

    Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

    2016-01-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis. PMID:27274911

  14. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

    PubMed

    Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

    2016-04-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

  15. Personality, cognitive appraisal and adjustment in chronic pain patients.

    PubMed

    Herrero, Ana M; Ramírez-Maestre, Carmen; González, Vanessa

    2008-11-01

    This study investigated the relationship between clinical personality patterns and cognitive appraisal as well as their repercussions on adjustment to chronic pain in a sample of 91 patients. It was predicted that clinical personality patterns would be related to adjustment and cognitive appraisal processes, whereas cognitive appraisals would be related to anxiety, depression and levels of perceived pain. The instruments used were as follows: the Millon Clinical Multiaxial Inventory, the Cognitive Appraisal Questionnaire, the Hospital Anxiety and Depression Scale, and the McGill Pain Questionnaire. Multiple regression analyses, the Kruskal-Wallis test, and the Mann Whitney U-test were used to analyse the data obtained. The results show that certain clinical personality patterns were associated with poor adjustment to chronic pain. The use of cognitive appraisal of harm predicted higher anxiety levels and greater perceived pain in chronic pain patients. The use of cognitive appraisals of challenge predicted lower depression levels.

  16. Relationship of early-life stress and resilience to military adjustment in a young adulthood population.

    PubMed

    Choi, Kang; Im, Hyoungjune; Kim, Joohan; Choi, Kwang H; Jon, Duk-In; Hong, Hyunju; Hong, Narei; Lee, Eunjung; Seok, Jeong-Ho

    2013-11-01

    Early-life stress (ELS) may mediate adjustment problems while resilience may protect individuals against adjustment problems during military service. We investigated the relationship of ELS and resilience with adjustment problem factor scores in the Korea Military Personality Test (KMPT) in candidates for the military service. Four hundred and sixty-one candidates participated in this study. Vulnerability traits for military adjustment, ELS, and resilience were assessed using the KMPT, the Korean Early-Life Abuse Experience Questionnaire, and the Resilience Quotient Test, respectively. Data were analyzed using multiple linear regression analyses. The final model of the multiple linear regression analyses explained 30.2 % of the total variances of the sum of the adjustment problem factor scores of the KMPT. Neglect and exposure to domestic violence had a positive association with the total adjustment problem factor scores of the KMPT, but emotion control, impulse control, and optimism factor scores as well as education and occupational status were inversely associated with the total military adjustment problem score. ELS and resilience are important modulating factors in adjusting to military service. We suggest that neglect and exposure to domestic violence during early life may increase problem with adjustment, but capacity to control emotion and impulse as well as optimistic attitude may play protective roles in adjustment to military life. The screening procedures for ELS and the development of psychological interventions may be helpful for young adults to adjust to military service.

  17. Fitness adjusted racial disparities in central adiposity among women in the USA using quantile regression.

    PubMed

    McDonald, S; Ortaglia, A; Supino, C; Kacka, M; Clenin, M; Bottai, M

    2017-06-01

    This study comprehensively explores racial/ethnic disparities in waist circumference (WC) after adjusting for cardiorespiratory fitness (CRF), among both adult and adolescent women, across WC percentiles. Analysis was conducted using data from the 1999 to 2004 National Health and Nutrition Examination Survey. Female participants ( n  = 3,977) aged 12-49 years with complete data on CRF, height, weight and WC were included. Quantile regression models, stratified by age groups (12-15, 16-19 and 20-49 years), were used to assess the association between WC and race/ethnicity adjusting for CRF, height and age across WC percentiles (10th, 25th, 50th, 75th, 90th and 95th). For non-Hispanic (NH) Black, in both the 16-19 and 20-49 years age groups, estimated WC was significantly greater than for NH White across percentiles above the median with estimates ranging from 5.2 to 11.5 cm. For Mexican Americans, in all age groups, estimated WC tended to be significantly greater than for NH White particularly for middle percentiles (50th and 75th) with point estimates ranging from 1.9 to 8.4 cm. Significant disparities in WC between NH Black and Mexican women, as compared to NH White, remain even after adjustment for CRF. The magnitude of the disparities associated with race/ethnicity differs across WC percentiles and age groups.

  18. [Applying temporally-adjusted land use regression models to estimate ambient air pollution exposure during pregnancy].

    PubMed

    Zhang, Y J; Xue, F X; Bai, Z P

    2017-03-06

    The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression (LUR) models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.

  19. Exploring Mexican American adolescent romantic relationship profiles and adjustment

    PubMed Central

    Moosmann, Danyel A.V.; Roosa, Mark W.

    2015-01-01

    Although Mexican Americans are the largest ethnic minority group in the nation, knowledge is limited regarding this population's adolescent romantic relationships. This study explored whether 12th grade Mexican Americans’ (N = 218; 54% female) romantic relationship characteristics, cultural values, and gender created unique latent classes and if so, whether they were linked to adjustment. Latent class analyses suggested three profiles including, relatively speaking, higher, satisfactory, and lower quality romantic relationships. Regression analyses indicated these profiles had distinct associations with adjustment. Specifically, adolescents with higher and satisfactory quality romantic relationships reported greater future family expectations, higher self-esteem, and fewer externalizing symptoms than those with lower quality romantic relationships. Similarly, adolescents with higher quality romantic relationships reported greater academic self-efficacy and fewer sexual partners than those with lower quality romantic relationships. Overall, results suggested higher quality romantic relationships were most optimal for adjustment. Future research directions and implications are discussed. PMID:26141198

  20. Acculturative Stress, Parental and Professor Attachment, and College Adjustment in Asian International Students

    ERIC Educational Resources Information Center

    Han, Suejung; Pistole, M. Carole; Caldwell, Jarred M.

    2017-01-01

    This study examined parental and professor attachment as buffers against acculturative stress and as predictors of college adjustment of 210 Asian international students (AISs). Moderated hierarchical regression analyses revealed that acculturative stress negatively and secure parental and professor attachment positively predicted academic…

  1. Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data.

    PubMed

    Holsclaw, Tracy; Hallgren, Kevin A; Steyvers, Mark; Smyth, Padhraic; Atkins, David C

    2015-12-01

    Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials. (c) 2016 APA, all rights reserved).

  2. Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data

    PubMed Central

    Holsclaw, Tracy; Hallgren, Kevin A.; Steyvers, Mark; Smyth, Padhraic; Atkins, David C.

    2015-01-01

    Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non-normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased type-I and type-II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally-technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in supplementary materials. PMID:26098126

  3. Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

    PubMed Central

    Nickerson, Lisa D.; Smith, Stephen M.; Öngür, Döst; Beckmann, Christian F.

    2017-01-01

    Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude

  4. Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

    USGS Publications Warehouse

    Brown, C. Erwin

    1993-01-01

    Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

  5. A regression-adjusted approach can estimate competing biomass

    Treesearch

    James H. Miller

    1983-01-01

    A method is presented for estimating above-ground herbaceous and woody biomass on competition research plots. On a set of destructively-sampled plots, an ocular estimate of biomass by vegetative component is first made, after which vegetation is clipped, dried, and weighed. Linear regressions are then calculated for each component between estimated and actual weights...

  6. Adjusting for publication biases across similar interventions performed well when compared with gold standard data.

    PubMed

    Moreno, Santiago G; Sutton, Alex J; Ades, A E; Cooper, Nicola J; Abrams, Keith R

    2011-11-01

    To extend, apply, and evaluate a regression-based approach to adjusting meta-analysis for publication and related biases. The approach uses related meta-analyses to improve estimation by borrowing strength on the degree of bias. The proposed adjustment approach is described. Adjustments are applied both independently and by borrowing strength across journal-extracted data on the effectiveness of 12 antidepressant drugs from placebo-controlled trials. The methods are also applied to Food and Drug Administration (FDA) data obtained on the same 12 drugs. Results are compared, viewing the FDA observed data as gold standard. Estimates adjusted for publication biases made independently for each drug were very uncertain using both the journal and FDA data. Adjusted estimates were much more precise when borrowing strength across meta-analyses. Reassuringly, adjustments in this way made to the journal data agreed closely with the observed estimates from the FDA data, while the adjusted FDA results changed only minimally from those observed from the FDA data. The method worked well in the case study considered and therefore further evaluation is encouraged. It is suggested that this approach may be especially useful when adjusting several meta-analyses on similar interventions and outcomes, particularly when there are small numbers of studies. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle.

    PubMed

    Baldi, F; Alencar, M M; Albuquerque, L G

    2010-12-01

    The objective of this work was to estimate covariance functions using random regression models on B-splines functions of animal age, for weights from birth to adult age in Canchim cattle. Data comprised 49,011 records on 2435 females. The model of analysis included fixed effects of contemporary groups, age of dam as quadratic covariable and the population mean trend taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were modelled through a step function with four classes. The direct and maternal additive genetic effects, and animal and maternal permanent environmental effects were included as random effects in the model. A total of seventeen analyses, considering linear, quadratic and cubic B-splines functions and up to seven knots, were carried out. B-spline functions of the same order were considered for all random effects. Random regression models on B-splines functions were compared to a random regression model on Legendre polynomials and with a multitrait model. Results from different models of analyses were compared using the REML form of the Akaike Information criterion and Schwarz' Bayesian Information criterion. In addition, the variance components and genetic parameters estimated for each random regression model were also used as criteria to choose the most adequate model to describe the covariance structure of the data. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most adequate to describe the covariance structure of the data. Random regression models using B-spline functions as base functions fitted the data better than Legendre polynomials, especially at mature ages, but higher number of parameters need to be estimated with B-splines functions. © 2010 Blackwell Verlag GmbH.

  8. Adjustment of geochemical background by robust multivariate statistics

    USGS Publications Warehouse

    Zhou, D.

    1985-01-01

    Conventional analyses of exploration geochemical data assume that the background is a constant or slowly changing value, equivalent to a plane or a smoothly curved surface. However, it is better to regard the geochemical background as a rugged surface, varying with changes in geology and environment. This rugged surface can be estimated from observed geological, geochemical and environmental properties by using multivariate statistics. A method of background adjustment was developed and applied to groundwater and stream sediment reconnaissance data collected from the Hot Springs Quadrangle, South Dakota, as part of the National Uranium Resource Evaluation (NURE) program. Source-rock lithology appears to be a dominant factor controlling the chemical composition of groundwater or stream sediments. The most efficacious adjustment procedure is to regress uranium concentration on selected geochemical and environmental variables for each lithologic unit, and then to delineate anomalies by a common threshold set as a multiple of the standard deviation of the combined residuals. Robust versions of regression and RQ-mode principal components analysis techniques were used rather than ordinary techniques to guard against distortion caused by outliers Anomalies delineated by this background adjustment procedure correspond with uranium prospects much better than do anomalies delineated by conventional procedures. The procedure should be applicable to geochemical exploration at different scales for other metals. ?? 1985.

  9. Adjustments to de Leva-anthropometric regression data for the changes in body proportions in elderly humans.

    PubMed

    Ho Hoang, Khai-Long; Mombaur, Katja

    2015-10-15

    Dynamic modeling of the human body is an important tool to investigate the fundamentals of the biomechanics of human movement. To model the human body in terms of a multi-body system, it is necessary to know the anthropometric parameters of the body segments. For young healthy subjects, several data sets exist that are widely used in the research community, e.g. the tables provided by de Leva. None such comprehensive anthropometric parameter sets exist for elderly people. It is, however, well known that body proportions change significantly during aging, e.g. due to degenerative effects in the spine, such that parameters for young people cannot be used for realistically simulating the dynamics of elderly people. In this study, regression equations are derived from the inertial parameters, center of mass positions, and body segment lengths provided by de Leva to be adjustable to the changes in proportion of the body parts of male and female humans due to aging. Additional adjustments are made to the reference points of the parameters for the upper body segments as they are chosen in a more practicable way in the context of creating a multi-body model in a chain structure with the pelvis representing the most proximal segment. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Zero adjusted models with applications to analysing helminths count data.

    PubMed

    Chipeta, Michael G; Ngwira, Bagrey M; Simoonga, Christopher; Kazembe, Lawrence N

    2014-11-27

    It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts. The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared. Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models. This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

  11. [Risk-adjusted assessment: late-onset infection in neonates].

    PubMed

    Gmyrek, Dieter; Koch, Rainer; Vogtmann, Christoph; Kaiser, Annette; Friedrich, Annette

    2011-01-01

    The weak point of the countrywide perinatal/neonatal quality surveillance is the ignorance of interhospital differences in the case mix of patients. As a result, this approach does not produce reliable benchmarking. The objective of this study was to adjust the result of the late-onset infection incidence of different hospitals according to their risk profile of patients by multivariate analysis. The perinatal/neonatal database of 41,055 newborns of the Saxonian quality surveillance from 1998 to 2004 was analysed. Based on 18 possible risk factors, a logistic regression model was used to develop a specific risk predictor for the quality indicator "late-onset infection". The developed risk predictor for the incidence of late-onset infection could be described by 4 of the 18 analysed risk factors, namely gestational age, admission from home, hypoxic ischemic encephalopathy and B-streptococcal infection. The AUC(ROC) value of this quality indicator was 83.3%, which demonstrates its reliability. The hospital ranking based on the adjusted risk assessment was very different from hospital rankings before this adjustment. The average correction of ranking position was 4.96 for 35 clinics. The application of the risk adjustment method proposed here allows for a more objective comparison of the incidence of the quality indicator "late onset infection" among different hospitals. Copyright © 2011. Published by Elsevier GmbH.

  12. College student engaging in cyberbullying victimization: cognitive appraisals, coping strategies, and psychological adjustments.

    PubMed

    Na, Hyunjoo; Dancy, Barbara L; Park, Chang

    2015-06-01

    The study's purpose was to explore whether frequency of cyberbullying victimization, cognitive appraisals, and coping strategies were associated with psychological adjustments among college student cyberbullying victims. A convenience sample of 121 students completed questionnaires. Linear regression analyses found frequency of cyberbullying victimization, cognitive appraisals, and coping strategies respectively explained 30%, 30%, and 27% of the variance in depression, anxiety, and self-esteem. Frequency of cyberbullying victimization and approach and avoidance coping strategies were associated with psychological adjustments, with avoidance coping strategies being associated with all three psychological adjustments. Interventions should focus on teaching cyberbullying victims to not use avoidance coping strategies. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Association between subjective memory complaints and depressive symptoms after adjustment for genetic and family environmental factors in a Japanese twin study.

    PubMed

    Tanaka, Haruka; Ogata, Soshiro; Omura, Kayoko; Honda, Chika; Kamide, Kei; Hayakawa, Kazuo

    2016-03-01

    The aim of this study was to investigate the association between subjective memory complaints (SMCs) and depressive symptoms, with and without adjustment for genetic and family environmental factors. We conducted a cross-sectional study using twins and measured SMCs and depressive symptoms as outcomes and explanatory variables, respectively. First, we performed regression analyses using generalized estimating equations to investigate the associations between SMCs and depressive symptoms without adjustment for genetic and family environmental factors (individual-level analyses). We then performed regression analyses for within-pair differences using monozygotic (MZ) and dizygotic (DZ) twin pairs and MZ twin pairs to investigate these associations with adjustment for genetic and family environmental factors by subtracting the values of one twin from those of co-twin variables (within-pair level analyses). Therefore, differences between the associations at individual- and within-pair level analyses suggested confounding by genetic factors. We included 556 twins aged ≥ 20 years. In the individual-level analyses, SMCs were significantly associated with depressive symptoms in both males and females [standardized coefficients: males, 0.23 (95% CI 0.08-0.38); females, 0.35 (95% CI 0.23-0.46)]. In the within-pair level analyses using MZ and same-sex DZ twin pairs, SMCs were significantly associated with depressive symptoms. In the within-pair level analyses using the MZ twin pairs, SMCs were significantly associated with depressive symptoms [standardized coefficients: males, 0.32 (95% CI 0.08-0.56); females, 0.24 (95% CI 0.13-0.42)]. This study suggested that SMCs were significantly associated with depressive symptoms after adjustment for genetic and family environmental factors.

  14. A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake

    PubMed Central

    Agogo, George O.

    2017-01-01

    Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR). The 24HR intakes are used as response in regression calibration to adjust for bias in the association. For foods not consumed daily, 24HR-reported intakes are usually characterized by excess zeroes, right skewness, and heteroscedasticity posing serious challenge in regression calibration modeling. We proposed a zero-augmented calibration model to adjust for measurement error in reported intake, while handling excess zeroes, skewness, and heteroscedasticity simultaneously without transforming 24HR intake values. We compared the proposed calibration method with the standard method and with methods that ignore measurement error by estimating long-term intake with 24HR and FFQ-reported intakes. The comparison was done in real and simulated datasets. With the 24HR, the mean increase in mercury level per ounce fish intake was about 0.4; with the FFQ intake, the increase was about 1.2. With both calibration methods, the mean increase was about 2.0. Similar trend was observed in the simulation study. In conclusion, the proposed calibration method performs at least as good as the standard method. PMID:27704599

  15. Fragile--Handle with Care: Regression Analyses That Include Categorical Data.

    ERIC Educational Resources Information Center

    Brown, Diane Peacock

    In education and the social sciences, problems of interest to researchers and users of research often involve variables that do not meet the assumptions of regression in the area of an equal interval scale relative to a zero point. Various coding schemes exist that allow the use of regression while still answering the researcher's questions of…

  16. Refining cost-effectiveness analyses using the net benefit approach and econometric methods: an example from a trial of anti-depressant treatment.

    PubMed

    Sabes-Figuera, Ramon; McCrone, Paul; Kendricks, Antony

    2013-04-01

    Economic evaluation analyses can be enhanced by employing regression methods, allowing for the identification of important sub-groups and to adjust for imperfect randomisation in clinical trials or to analyse non-randomised data. To explore the benefits of combining regression techniques and the standard Bayesian approach to refine cost-effectiveness analyses using data from randomised clinical trials. Data from a randomised trial of anti-depressant treatment were analysed and a regression model was used to explore the factors that have an impact on the net benefit (NB) statistic with the aim of using these findings to adjust the cost-effectiveness acceptability curves. Exploratory sub-samples' analyses were carried out to explore possible differences in cost-effectiveness. Results The analysis found that having suffered a previous similar depression is strongly correlated with a lower NB, independent of the outcome measure or follow-up point. In patients with previous similar depression, adding an selective serotonin reuptake inhibitors (SSRI) to supportive care for mild-to-moderate depression is probably cost-effective at the level used by the English National Institute for Health and Clinical Excellence to make recommendations. This analysis highlights the need for incorporation of econometric methods into cost-effectiveness analyses using the NB approach.

  17. A regularization corrected score method for nonlinear regression models with covariate error.

    PubMed

    Zucker, David M; Gorfine, Malka; Li, Yi; Tadesse, Mahlet G; Spiegelman, Donna

    2013-03-01

    Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and interval estimates of the regression coefficients. We present here a new general method for adjusting for covariate error. Our method consists of an approximate version of the Stefanski-Nakamura corrected score approach, using the method of regularization to obtain an approximate solution of the relevant integral equation. We develop the theory in the setting of classical likelihood models; this setting covers, for example, linear regression, nonlinear regression, logistic regression, and Poisson regression. The method is extremely general in terms of the types of measurement error models covered, and is a functional method in the sense of not involving assumptions on the distribution of the true covariate. We discuss the theoretical properties of the method and present simulation results in the logistic regression setting (univariate and multivariate). For illustration, we apply the method to data from the Harvard Nurses' Health Study concerning the relationship between physical activity and breast cancer mortality in the period following a diagnosis of breast cancer. Copyright © 2013, The International Biometric Society.

  18. Effortful Control, Behavior Problems and Peer Relations: What Predicts Academic Adjustment in Kindergarteners from Low-income Families?

    PubMed Central

    Morris, Amanda Sheffield; John, Aesha; Halliburton, Amy L.; Morris, Michael D. S.; Robinson, Lara R.; Myers, Sonya S.; Aucoin, Katherine J.; Keyes, Angela W.; Terranova, Andrew

    2013-01-01

    This study examined the role of effortful control, behavior problems, and peer relations in the academic adjustment of 74 kindergarten children from primarily low-income families using a short-term longitudinal design. Teachers completed standardized measures of children’s effortful control, internalizing and externalizing problems, school readiness, and academic skills. Children participated in a sociometric interview to assess peer relations. Research Findings: Correlational analyses indicate that children’s effortful control, behavior problems in school, and peer relations are associated with academic adjustment variables at the end of the school year, including school readiness, reading skills, and math skills. Results of regression analyses indicate that household income and children’s effortful control primarily account for variation in children’s academic adjustment. The associations between children’s effortful control and academic adjustment did not vary across sex of the child or ethnicity. Mediational analyses indicate an indirect effect of effortful control on school readiness, through children’s internalizing problems. Practice or Policy: Effortful control emerged as a strong predictor of academic adjustment among kindergarten children from low-income families. Strategies for enhancing effortful control and school readiness among low-income children are discussed. PMID:24163572

  19. Regional regression of flood characteristics employing historical information

    USGS Publications Warehouse

    Tasker, Gary D.; Stedinger, J.R.

    1987-01-01

    Streamflow gauging networks provide hydrologic information for use in estimating the parameters of regional regression models. The regional regression models can be used to estimate flood statistics, such as the 100 yr peak, at ungauged sites as functions of drainage basin characteristics. A recent innovation in regional regression is the use of a generalized least squares (GLS) estimator that accounts for unequal station record lengths and sample cross correlation among the flows. However, this technique does not account for historical flood information. A method is proposed here to adjust this generalized least squares estimator to account for possible information about historical floods available at some stations in a region. The historical information is assumed to be in the form of observations of all peaks above a threshold during a long period outside the systematic record period. A Monte Carlo simulation experiment was performed to compare the GLS estimator adjusted for historical floods with the unadjusted GLS estimator and the ordinary least squares estimator. Results indicate that using the GLS estimator adjusted for historical information significantly improves the regression model. ?? 1987.

  20. Confounding adjustment in comparative effectiveness research conducted within distributed research networks.

    PubMed

    Toh, Sengwee; Gagne, Joshua J; Rassen, Jeremy A; Fireman, Bruce H; Kulldorff, Martin; Brown, Jeffrey S

    2013-08-01

    A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interests. We describe the strengths and limitations of different confounding adjustment approaches that can be considered in observational CER studies conducted within DRNs, and the theoretical and practical issues to consider when selecting among them in various study settings. Several methods can be used to adjust for multiple confounders simultaneously, either as individual covariates or as confounder summary scores (eg, propensity scores and disease risk scores), including: (1) centralized analysis of patient-level data, (2) case-centered logistic regression of risk set data, (3) stratified or matched analysis of aggregated data, (4) distributed regression analysis, and (5) meta-analysis of site-specific effect estimates. These methods require different granularities of information be shared across sites and afford investigators different levels of analytic flexibility. DRNs are growing in use and sharing of highly detailed patient-level information is not always feasible in DRNs. Methods that incorporate confounder summary scores allow investigators to adjust for a large number of confounding factors without the need to transfer potentially identifiable information in DRNs. They have the potential to let investigators perform many analyses traditionally conducted through a centralized dataset with detailed patient-level information.

  1. Methodological uncertainties in multi-regression analyses of middle-atmospheric data series.

    PubMed

    Kerzenmacher, Tobias E; Keckhut, Philippe; Hauchecorne, Alain; Chanin, Marie-Lise

    2006-07-01

    Multi-regression analyses have often been used recently to detect trends, in particular in ozone or temperature data sets in the stratosphere. The confidence in detecting trends depends on a number of factors which generate uncertainties. Part of these uncertainties comes from the random variability and these are what is usually considered. They can be statistically estimated from residual deviations between the data and the fitting model. However, interferences between different sources of variability affecting the data set, such as the Quasi-Biennal Oscillation (QBO), volcanic aerosols, solar flux variability and the trend can also be a critical source of errors. This type of error has hitherto not been well quantified. In this work an artificial data series has been generated to carry out such estimates. The sources of errors considered here are: the length of the data series, the dependence on the choice of parameters used in the fitting model and the time evolution of the trend in the data series. Curves provided here, will permit future studies to test the magnitude of the methodological bias expected for a given case, as shown in several real examples. It is found that, if the data series is shorter than a decade, the uncertainties are very large, whatever factors are chosen to identify the source of the variability. However the errors can be limited when dealing with natural variability, if a sufficient number of periods (for periodic forcings) are covered by the analysed dataset. However when analysing the trend, the response to volcanic eruption induces a bias, whatever the length of the data series. The signal to noise ratio is a key factor: doubling the noise increases the period for which data is required in order to obtain an error smaller than 10%, from 1 to 3-4 decades. Moreover, if non-linear trends are superimposed on the data, and if the length of the series is longer than five years, a non-linear function has to be used to estimate trends. When

  2. The relationship between perceived parental rearing behaviors and school adjustment of adolescent cancer survivors in Korea

    PubMed Central

    Lee, Sunhee; Kim, Dong Hee

    2017-01-01

    Abstract Return and adjustment to school in adolescents who have survived cancer have become of increasing interest as the numbers of childhood cancers survivors have grown due to advances in treatments. Perceived parental rearing behavior is an important factor related to school adjustment. This study examined the relationships between maternal and parental rearing practices, general characteristics, and school adjustment in adolescent cancer survivors in Korea. We conducted a descriptive, exploratory study of 84 adolescents with cancer using the Korean version of the Fragebogen zum erinnerten elterlichen Erziehungsverhalten: FEE (Recalled Parental Rearing Behavior) and a school adjustment measurement. Descriptive, Pearson correlational, and multiple regression analyses were used to investigate the data. In bivariate analysis, age (r = −0.358, P < .05), mother's emotional warmth (r = 0.549, P < .01), and father's emotional warmth (r = 0.391, P < .05) were significantly associated with school adjustment. However, the results of multiple regression analysis showed that only mother's emotional warmth (β = .720, P < .05) was significantly associated with school adjustment. Adolescent cancer survivors who reported higher mother's emotional warmth exhibited better school adjustment. This finding indicates that it is important to help parents of adolescent cancer survivors enhance their parental rearing behaviors, such as emotional warmth, to help adolescents adjust to school. PMID:28796068

  3. The Application of Censored Regression Models in Low Streamflow Analyses

    NASA Astrophysics Data System (ADS)

    Kroll, C.; Luz, J.

    2003-12-01

    Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

  4. Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

    PubMed

    Onder, Seyhan; Mutlu, Mert

    2017-09-01

    Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

  5. Random regression analyses using B-spline functions to model growth of Nellore cattle.

    PubMed

    Boligon, A A; Mercadante, M E Z; Lôbo, R B; Baldi, F; Albuquerque, L G

    2012-02-01

    The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions

  6. Logistic regression applied to natural hazards: rare event logistic regression with replications

    NASA Astrophysics Data System (ADS)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  7. Analysis of Palm Oil Production, Export, and Government Consumption to Gross Domestic Product of Five Districts in West Kalimantan by Panel Regression

    NASA Astrophysics Data System (ADS)

    Sulistianingsih, E.; Kiftiah, M.; Rosadi, D.; Wahyuni, H.

    2017-04-01

    Gross Domestic Product (GDP) is an indicator of economic growth in a region. GDP is a panel data, which consists of cross-section and time series data. Meanwhile, panel regression is a tool which can be utilised to analyse panel data. There are three models in panel regression, namely Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The models will be chosen based on results of Chow Test, Hausman Test and Lagrange Multiplier Test. This research analyses palm oil about production, export, and government consumption to five district GDP are in West Kalimantan, namely Sanggau, Sintang, Sambas, Ketapang and Bengkayang by panel regression. Based on the results of analyses, it concluded that REM, which adjusted-determination-coefficient is 0,823, is the best model in this case. Also, according to the result, only Export and Government Consumption that influence GDP of the districts.

  8. Predictors of sociocultural adjustment among sojourning Malaysian students in Britain.

    PubMed

    Swami, Viren

    2009-08-01

    The process of cross-cultural migration may be particularly difficult for students travelling overseas for further or higher education, especially where qualitative differences exist between the home and host nations. The present study examined the sociocultural adjustment of sojourning Malaysian students in Britain. Eighty-one Malay and 110 Chinese students enrolled in various courses answered a self-report questionnaire that examined various aspects of sociocultural adjustment. A series of one-way analyses of variance showed that Malay participants experienced poorer sociocultural adjustment in comparison with their Chinese counterparts. They were also less likely than Chinese students to have contact with co-nationals and host nationals, more likely to perceive their actual experience in Britain as worse than they had expected, and more likely to perceive greater cultural distance and greater discrimination. The results of regression analyses showed that, for Malay participants, perceived discrimination accounted for the greatest proportion of variance in sociocultural adjustment (73%), followed by English language proficiency (10%) and contact with host nationals (4%). For Chinese participants, English language proficiency was the strongest predictor of sociocultural adjustment (54%), followed by expectations of life in Britain (18%) and contact with host nationals (3%). By contrast, participants' sex, age, and length of residence failed to emerge as significant predictors for either ethnic group. Possible explanations for this pattern of findings are discussed, including the effects of Islamophobia on Malay-Muslims in Britain, possible socioeconomic differences between Malay and Chinese students, and personality differences between the two ethnic groups. The results are further discussed in relation to practical steps that can be taken to improve the sociocultural adjustment of sojourning students in Britain.

  9. Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

    PubMed

    Lang, Dean H; Sharkey, Neil A; Lionikas, Arimantas; Mack, Holly A; Larsson, Lars; Vogler, George P; Vandenbergh, David J; Blizard, David A; Stout, Joseph T; Stitt, Joseph P; McClearn, Gerald E

    2005-05-01

    The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted

  10. Prevalence and predictors of post-stroke mood disorders: A meta-analysis and meta-regression of depression, anxiety and adjustment disorder.

    PubMed

    Mitchell, Alex J; Sheth, Bhavisha; Gill, John; Yadegarfar, Motahare; Stubbs, Brendon; Yadegarfar, Mohammad; Meader, Nick

    2017-07-01

    To ascertain the prevalence and predictors of mood disorders, determined by structured clinical interviews (ICD or DSM criteria) in people after stroke. Major electronic databases were searched from inception to June 2016 for studies involving major depression (MDD), minor depression (MnD), dysthymia, adjustment disorder, any depressive disorder (any depressive disorder) and anxiety disorders. Studies were combined using both random and fixed effects meta-analysis and results were stratified as appropriate. Depression was examined on 147 occasions from 2days to 7years after stroke (mean 6.87months, N=33 in acute, N=43 in rehabilitation and N=69 in the community/outpatients). Across 128 analyses involving 15,573 patients assessed for major depressive disorder (MDD), the point prevalence of depression was 17.7% (95% CI=15.6% to 20.0%) 0.65 analyses involving 9720 patients determined MnD was present in 13.1% in all settings (95% CI=10.9% to 15.8%). Dysthymia was present in 3.1% (95% CI=2.1% to 5.3%), adjustment disorder in 6.9% (95% CI=4.6 to 9.7%) and anxiety in 9.8% (95% CI=5.9% to 14.8%). Any depressive disorder was present in 33.5% (95% CI=30.3% to 36.8%). The relative risk of any depressive disorder was higher following left (dominant) hemisphere stroke, aphasia, and among people with a family history and past history of mood disorders. Depression, adjustment disorder and anxiety are common after stroke. Risk factors are aphasia, dominant hemispheric lesions and past personal/family history of depression but not time since stroke. Copyright © 2017. Published by Elsevier Inc.

  11. Parental warmth, control, and indulgence and their relations to adjustment in Chinese children: a longitudinal study.

    PubMed

    Chen, X; Liu, M; Li, D

    2000-09-01

    A sample of children, initially 12 years old, in the People's Republic of China participated in this 2-year longitudinal study. Data on parental warmth, control, and indulgence were collected from children's self-reports. Information concerning social, academic, and psychological adjustment was obtained from multiple sources. The results indicated that parenting styles might be a function of child gender and change with age. Regression analyses revealed that parenting styles of fathers and mothers predicted different outcomes. Whereas maternal warmth had significant contributions to the prediction of emotional adjustment, paternal warmth significantly predicted later social and school achievement. It was also found that paternal, but not maternal, indulgence significantly predicted children's adjustment difficulties. The contributions of the parenting variables might be moderated by the child's initial conditions.

  12. Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

    PubMed

    Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

    2017-12-01

    1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

  13. Relations between life satisfaction, adjustment to illness, and emotional distress in a sample of men with ischemic cardiopathy.

    PubMed

    Ruiz, María Angeles; Sanjuan, Pilar; Pérez-García, Ana M; Rueda, Beatriz

    2011-05-01

    Fifty-two men who had suffered a first episode ischemic heart disease reported their degree of life satisfaction, the strategies they used to adjust to the illness, and the symptoms of anxiety and depression they felt. The multiple regression analyses carried out indicated that emotional distress was associated with a lower level of life satisfaction. In the analyses of anxiety symptoms, the use of negative adjustment strategies was also a significant predictor. Lastly, a significant Life Satisfaction x Type of Adjustment interaction was obtained. According to this, the patients who felt more satisfaction with their lives used more positive strategies to adjust to the illness and fewer negative ones, than the group of patients who were less satisfied. In conclusion, life satisfaction predicts emotional wellbeing of patients with ischemic heart disease and it enhances the implementation of appropriate strategies to cope with the disease. Moreover, although life satisfaction has been considered a stable measure, we suggest it may change as the experience of illness limits individuals' important goals.

  14. The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

    PubMed

    Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

    2017-12-28

    Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which

  15. A Machine Learning Framework for Plan Payment Risk Adjustment.

    PubMed

    Rose, Sherri

    2016-12-01

    To introduce cross-validation and a nonparametric machine learning framework for plan payment risk adjustment and then assess whether they have the potential to improve risk adjustment. 2011-2012 Truven MarketScan database. We compare the performance of multiple statistical approaches within a broad machine learning framework for estimation of risk adjustment formulas. Total annual expenditure was predicted using age, sex, geography, inpatient diagnoses, and hierarchical condition category variables. The methods included regression, penalized regression, decision trees, neural networks, and an ensemble super learner, all in concert with screening algorithms that reduce the set of variables considered. The performance of these methods was compared based on cross-validated R 2 . Our results indicate that a simplified risk adjustment formula selected via this nonparametric framework maintains much of the efficiency of a traditional larger formula. The ensemble approach also outperformed classical regression and all other algorithms studied. The implementation of cross-validated machine learning techniques provides novel insight into risk adjustment estimation, possibly allowing for a simplified formula, thereby reducing incentives for increased coding intensity as well as the ability of insurers to "game" the system with aggressive diagnostic upcoding. © Health Research and Educational Trust.

  16. Treatment of patent ductus arteriosus and neonatal mortality/morbidities: adjustment for treatment selection bias.

    PubMed

    Mirea, Lucia; Sankaran, Koravangattu; Seshia, Mary; Ohlsson, Arne; Allen, Alexander C; Aziz, Khalid; Lee, Shoo K; Shah, Prakesh S

    2012-10-01

    To examine the association between treatment for patent ductus arteriosus (PDA) and neonatal outcomes in preterm infants, after adjustment for treatment selection bias. Secondary analyses were conducted using data collected by the Canadian Neonatal Network for neonates born at a gestational age ≤ 32 weeks and admitted to neonatal intensive care units in Canada between 2004 and 2008. Infants who had PDA and survived beyond 72 hours were included in multivariable logistic regression analyses that compared mortality or any severe neonatal morbidity (intraventricular hemorrhage grades ≥ 3, retinopathy of prematurity stages ≥ 3, bronchopulmonary dysplasia, or necrotizing enterocolitis stages ≥ 2) between treatment groups (conservative management, indomethacin only, surgical ligation only, or both indomethacin and ligation). Propensity scores (PS) were estimated for each pair of treatment comparisons, and used in PS-adjusted and PS-matched analyses. Among 3556 eligible infants with a diagnosis of PDA, 577 (16%) were conservatively managed, 2026 (57%) received indomethacin only, 327 (9%) underwent ligation only, and 626 (18%) were treated with both indomethacin and ligation. All multivariable and PS-based analyses detected significantly higher mortality/morbidities for surgically ligated infants, irrespective of prior indomethacin treatment (OR ranged from 1.25-2.35) compared with infants managed conservatively or those who received only indomethacin. No significant differences were detected between infants treated with only indomethacin and those managed conservatively. Surgical ligation of PDA in preterm neonates was associated with increased neonatal mortality/morbidity in all analyses adjusted for measured confounders that attempt to account for treatment selection bias. Copyright © 2012 Mosby, Inc. All rights reserved.

  17. 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.

  18. Utility-Based Instruments for People with Dementia: A Systematic Review and Meta-Regression Analysis.

    PubMed

    Li, Li; Nguyen, Kim-Huong; Comans, Tracy; Scuffham, Paul

    2018-04-01

    Several utility-based instruments have been applied in cost-utility analysis to assess health state values for people with dementia. Nevertheless, concerns and uncertainty regarding their performance for people with dementia have been raised. To assess the performance of available utility-based instruments for people with dementia by comparing their psychometric properties and to explore factors that cause variations in the reported health state values generated from those instruments by conducting meta-regression analyses. A literature search was conducted and psychometric properties were synthesized to demonstrate the overall performance of each instrument. When available, health state values and variables such as the type of instrument and cognitive impairment levels were extracted from each article. A meta-regression analysis was undertaken and available covariates were included in the models. A total of 64 studies providing preference-based values were identified and included. The EuroQol five-dimension questionnaire demonstrated the best combination of feasibility, reliability, and validity. Meta-regression analyses suggested that significant differences exist between instruments, type of respondents, and mode of administration and the variations in estimated utility values had influences on incremental quality-adjusted life-year calculation. This review finds that the EuroQol five-dimension questionnaire is the most valid utility-based instrument for people with dementia, but should be replaced by others under certain circumstances. Although no utility estimates were reported in the article, the meta-regression analyses that examined variations in utility estimates produced by different instruments impact on cost-utility analysis, potentially altering the decision-making process in some circumstances. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  19. The stress-buffering effects of hope on adjustment to multiple sclerosis.

    PubMed

    Madan, Sindia; Pakenham, Kenneth I

    2014-12-01

    Hope is an important resource for coping with chronic illness; however, the role of hope in adjusting to multiple sclerosis (MS) has been neglected, and the mechanisms by which hope exerts beneficial impacts are not well understood. This study aims to examine the direct and stress-moderating effects of dispositional hope and its components (agency and pathways) on adjustment to MS. A total of 296 people with MS completed questionnaires at time 1 at 12 months later and time 2. Focal predictors were stress, hope, agency and pathways, and the adjustment outcomes were anxiety, depression, positive affect, positive states of mind and life satisfaction. Results of regression analyses showed that as predicted, greater hope was associated with better adjustment after controlling for the effects of time 1 adjustment and relevant demographics and illness variables. However, these direct effects of hope were subsumed by stress-buffering effects. Regarding the hope components, the beneficial impacts of agency emerged via a direct effects mechanism, whereas the effects of pathways were evidenced via a moderating mechanism. Findings highlight hope as an important protective coping resource for coping with MS and accentuate the roles of both agency and pathways thinking and their different modes of influence in this process.

  20. Gender adjustment or stratification in discerning upper extremity musculoskeletal disorder risk?

    PubMed

    Silverstein, Barbara; Fan, Z Joyce; Smith, Caroline K; Bao, Stephen; Howard, Ninica; Spielholz, Peregrin; Bonauto, David; Viikari-Juntura, Eira

    2009-03-01

    The aim was to explore whether "adjustment" for gender masks important exposure differences between men and women in a study of rotator cuff syndrome (RCS) and carpal tunnel syndrome (CTS) and work exposures. This cross-sectional study of 733 subjects in 12 health care and manufacturing workplaces used detailed individual health and work exposure assessment methods. Multiple logistic regression analysis was used to compare gender stratified and adjusted models. Prevalence of RCS and CTS among women was 7.1% and 11.3% respectively, and among men 7.8% and 6.4%. In adjusted (gender, age, body mass index) multivariate analyses of RCS and CTS, gender was not statistically significantly different. For RCS, upper arm flexion >/=45 degrees and forceful pinch increased the odds in the gender-adjusted model (OR 2.66, 95% CI 1.26-5.59) but primarily among women in the stratified analysis (OR 6.68, 95% CI 1.81-24.66 versus OR 1.45, 95% CI 0.53-4.00). For CTS, wrist radial/ulnar deviation >/=4% time and lifting >/=4.5kg >3% time, the adjusted OR was higher for women (OR 4.85, 95% CI 2.12-11.11) and in the gender stratified analyses, the odds were increased for both genders (women OR 5.18, 95% CI 1.70-15.81 and men OR 3.63, 95% CI 1.08-12.18). Gender differences in response to physical work exposures may reflect gender segregation in work and potential differences in pinch and lifting capacity. Reduction in these exposures may reduce prevalence of upper extremity disorders for all workers.

  1. Length bias correction in gene ontology enrichment analysis using logistic regression.

    PubMed

    Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

    2012-01-01

    When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

  2. Factors associated with positive adjustment in siblings of children with severe emotional disturbance: the role of family resources and community life.

    PubMed

    Kilmer, Ryan P; Cook, James R; Munsell, Eylin Palamaro; Salvador, Samantha Kane

    2010-10-01

    This study builds on the scant research involving siblings of children with severe emotional disturbances (SED) and examines: associations between adversity experiences and adjustment among 5- to 10-year-old siblings, and relations among family resources, community life, and sibling adjustment. Caregivers from 100 families completed standardized indicators of sibling adjustment and scales reflecting multiple contextual variables. Results document negative associations between stress exposure and sibling adjustment. Regression models also indicate positive associations between the caregiver-child relationship and broader family resources on sibling behavioral and emotional strengths, even after accounting for adversity experiences; adversity exposure was the prime correlate in regression models involving sibling oppositional behavior. Analyses also suggest that strain related to parenting a child with SED is associated with sibling adjustment. This work documents the needs of these siblings and their family systems and highlights the relevance of not only core proximal influences (e.g., child-caregiver relationship) but also elements of their broader contexts. Implications and recommendations are described, including the need to support plans of care that involve services, supports, or preventive strategies for these siblings. © 2010 American Orthopsychiatric Association.

  3. The importance of mean time in therapeutic range for complication rates in warfarin therapy of patients with atrial fibrillation: A systematic review and meta-regression analysis.

    PubMed

    Vestergaard, Anne Sig; Skjøth, Flemming; Larsen, Torben Bjerregaard; Ehlers, Lars Holger

    2017-01-01

    \\Anticoagulation is used for stroke prophylaxis in non-valvular atrial fibrillation, amongst other by use of the vitamin K antagonist, warfarin. Quality in warfarin therapy is often summarized by the time patients spend within the therapeutic range (percent time in therapeutic range, TTR). The correlation between TTR and the occurrence of complications during warfarin therapy has been established, but the influence of patient characteristics in that respect remains undetermined. The objective of the present papers was to examine the association between mean TTR and complication rates with adjustment for differences in relevant patient cohort characteristics. A systematic literature search was conducted in MEDLINE and Embase (2005-2015) to identify eligible studies reporting on use of warfarin therapy by patients with non-valvular atrial fibrillation and the occurrence of hemorrhage and thromboembolism. Both randomized controlled trials and observational cohort studies were included. The association between the reported mean TTR and major bleeding and stroke/systemic embolism was analyzed by random-effects meta-regression with and without adjustment for relevant clinical cohort characteristics. In the adjusted meta-regressions, the impact of mean TTR on the occurrence of hemorrhage was adjusted for the mean age and the proportion of populations with prior stroke or transient ischemic attack. In the adjusted analyses on thromboembolism, the proportion of females was, furthermore, included. Of 2169 papers, 35 papers met pre-specified inclusion criteria, holding relevant information on 31 patient cohorts. In univariable meta-regression, increasing mean TTR was significantly associated with a decreased rate of both major bleeding and stroke/systemic embolism. However, after adjustment mean TTR was no longer significantly associated with stroke/systemic embolism. The proportion of residual variance composed by between-study heterogeneity was substantial for all analyses

  4. Methods for detecting, quantifying, and adjusting for dissemination bias in meta-analysis are described.

    PubMed

    Mueller, Katharina Felicitas; Meerpohl, Joerg J; Briel, Matthias; Antes, Gerd; von Elm, Erik; Lang, Britta; Motschall, Edith; Schwarzer, Guido; Bassler, Dirk

    2016-12-01

    To systematically review methodological articles which focus on nonpublication of studies and to describe methods of detecting and/or quantifying and/or adjusting for dissemination in meta-analyses. To evaluate whether the methods have been applied to an empirical data set for which one can be reasonably confident that all studies conducted have been included. We systematically searched Medline, the Cochrane Library, and Web of Science, for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for dissemination bias in meta-analyses. The literature search retrieved 2,224 records, of which we finally included 150 full-text articles. A great variety of methods to detect, quantify, or adjust for dissemination bias were described. Methods included graphical methods mainly based on funnel plot approaches, statistical methods, such as regression tests, selection models, sensitivity analyses, and a great number of more recent statistical approaches. Only few methods have been validated in empirical evaluations using unpublished studies obtained from regulators (Food and Drug Administration, European Medicines Agency). We present an overview of existing methods to detect, quantify, or adjust for dissemination bias. It remains difficult to advise which method should be used as they are all limited and their validity has rarely been assessed. Therefore, a thorough literature search remains crucial in systematic reviews, and further steps to increase the availability of all research results need to be taken. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Alternative evaluation metrics for risk adjustment methods.

    PubMed

    Park, Sungchul; Basu, Anirban

    2018-06-01

    Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk-adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high-expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk-adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013-2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution-based estimators achieve higher group-level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual-level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade-off in selecting an appropriate risk-adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors. Copyright © 2018 John Wiley & Sons, Ltd.

  6. Treatment regimen, sexual attractiveness concerns and psychological adjustment among African American breast cancer patients.

    PubMed

    Taylor, Kathryn L; Lamdan, Ruth M; Siegel, Jamie E; Shelby, Rebecca; Hrywna, Mary; Moran-Klimi, Karen

    2002-01-01

    Among a sample of African American women recently diagnosed with breast cancer, we assessed the consequences of different treatment regimens on sexual attractiveness concerns, and the impact of sexual attractiveness concerns on current and subsequent psychological adjustment. The sample included 91 African American women with breast cancer; 90% had Stage I or II disease, 48% had chemotherapy, 47% had a lumpectomy, and 53% received a mastectomy. Feelings of sexual attractiveness and psychological adjustment were assessed an average of 3 months following surgery and again 4 months post-baseline. Regression analyses revealed that chemotherapy was associated with greater concerns about sexual attractiveness among lumpectomy patients (p<0.05), but not among mastectomy patients (p>0.20). The interaction also suggested that chemotherapy equalized the impact of types of surgery, as there was no difference on sexual attractiveness between surgery groups among women who had received chemotherapy (p>0.20). However, among women who had not received chemotherapy, mastectomy patients reported greater sexual attractiveness concerns (p<0.01). Finally, regression analyses revealed that feelings of sexual attractiveness were an important component of psychological well-being, both cross-sectionally (p<0.001) and longitudinally (p<0.001). Assessment of the combined impact of different treatment regimens on feelings of sexual attractiveness is particularly important given the current consensus that all breast cancer patients should receive chemotherapy, regardless of nodal status. Further, concerns about sexual attractiveness should be considered for inclusion as one component of psychosocial support programs for African American women with breast cancer, as our results suggested that they played a significant role in psychological adjustment. Copyright 2002 John Wiley & Sons, Ltd.

  7. Severity-Adjusted Mortality in Trauma Patients Transported by Police

    PubMed Central

    Band, Roger A.; Salhi, Rama A.; Holena, Daniel N.; Powell, Elizabeth; Branas, Charles C.; Carr, Brendan G.

    2018-01-01

    Study objective Two decades ago, Philadelphia began allowing police transport of patients with penetrating trauma. We conduct a large, multiyear, citywide analysis of this policy. We examine the association between mode of out-of-hospital transport (police department versus emergency medical services [EMS]) and mortality among patients with penetrating trauma in Philadelphia. Methods This is a retrospective cohort study of trauma registry data. Patients who sustained any proximal penetrating trauma and presented to any Level I or II trauma center in Philadelphia between January 1, 2003, and December 31, 2007, were included. Analyses were conducted with logistic regression models and were adjusted for injury severity with the Trauma and Injury Severity Score and for case mix with a modified Charlson index. Results Four thousand one hundred twenty-two subjects were identified. Overall mortality was 27.4%. In unadjusted analyses, patients transported by police were more likely to die than patients transported by ambulance (29.8% versus 26.5%; OR 1.18; 95% confidence interval [CI] 1.00 to 1.39). In adjusted models, no significant difference was observed in overall mortality between the police department and EMS groups (odds ratio [OR] 0.78; 95% CI 0.61 to 1.01). In subgroup analysis, patients with severe injury (Injury Severity Score >15) (OR 0.73; 95% CI 0.59 to 0.90), patients with gunshot wounds (OR 0.70; 95% CI 0.53 to 0.94), and patients with stab wounds (OR 0.19; 95% CI 0.08 to 0.45) were more likely to survive if transported by police. Conclusion We found no significant overall difference in adjusted mortality between patients transported by the police department compared with EMS but found increased adjusted survival among 3 key subgroups of patients transported by police. This practice may augment traditional care. PMID:24387925

  8. Herd-specific random regression carcass profiles for beef cattle after adjustment for animal genetic merit.

    PubMed

    Englishby, Tanya M; Moore, Kirsty L; Berry, Donagh P; Coffey, Mike P; Banos, Georgios

    2017-07-01

    Abattoir data are an important source of information for the genetic evaluation of carcass traits, but also for on-farm management purposes. The present study aimed to quantify the contribution of herd environment to beef carcass characteristics (weight, conformation score and fat score) with particular emphasis on generating finishing herd-specific profiles for these traits across different ages at slaughter. Abattoir records from 46,115 heifers and 78,790 steers aged between 360 and 900days, and from 22,971 young bulls aged between 360 and 720days, were analysed. Finishing herd-year and animal genetic (co)variance components for each trait were estimated using random regression models. Across slaughter age and gender, the ratio of finishing herd-year to total phenotypic variance ranged from 0.31 to 0.72 for carcass weight, 0.21 to 0.57 for carcass conformation and 0.11 to 0.44 for carcass fat score. These parameters indicate that the finishing herd environment is an important contributor to carcass trait variability and amenable to improvement with management practices. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Time series regression model for infectious disease and weather.

    PubMed

    Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

    2015-10-01

    Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Complementary nonparametric analysis of covariance for logistic regression in a randomized clinical trial setting.

    PubMed

    Tangen, C M; Koch, G G

    1999-03-01

    In the randomized clinical trial setting, controlling for covariates is expected to produce variance reduction for the treatment parameter estimate and to adjust for random imbalances of covariates between the treatment groups. However, for the logistic regression model, variance reduction is not obviously obtained. This can lead to concerns about the assumptions of the logistic model. We introduce a complementary nonparametric method for covariate adjustment. It provides results that are usually compatible with expectations for analysis of covariance. The only assumptions required are based on randomization and sampling arguments. The resulting treatment parameter is a (unconditional) population average log-odds ratio that has been adjusted for random imbalance of covariates. Data from a randomized clinical trial are used to compare results from the traditional maximum likelihood logistic method with those from the nonparametric logistic method. We examine treatment parameter estimates, corresponding standard errors, and significance levels in models with and without covariate adjustment. In addition, we discuss differences between unconditional population average treatment parameters and conditional subpopulation average treatment parameters. Additional features of the nonparametric method, including stratified (multicenter) and multivariate (multivisit) analyses, are illustrated. Extensions of this methodology to the proportional odds model are also made.

  11. Bayesian regression analyses of radiation modality effects on pericardial and pleural effusion and survival in esophageal cancer.

    PubMed

    He, Liru; Chapple, Andrew; Liao, Zhongxing; Komaki, Ritsuko; Thall, Peter F; Lin, Steven H

    2016-10-01

    To evaluate radiation modality effects on pericardial effusion (PCE), pleural effusion (PE) and survival in esophageal cancer (EC) patients. We analyzed data from 470 EC patients treated with definitive concurrent chemoradiotherapy (CRT). Bayesian semi-competing risks (SCR) regression models were fit to assess effects of radiation modality and prognostic covariates on the risks of PCE and PE, and death either with or without these preceding events. Bayesian piecewise exponential regression models were fit for overall survival, the time to PCE or death, and the time to PE or death. All models included propensity score as a covariate to correct for potential selection bias. Median times to onset of PCE and PE after RT were 7.1 and 6.1months for IMRT, and 6.5 and 5.4months for 3DCRT, respectively. Compared to 3DCRT, the IMRT group had significantly lower risks of PE, PCE, and death. The respective probabilities of a patient being alive without either PCE or PE at 3-years and 5-years were 0.29 and 0.21 for IMRT compared to 0.13 and 0.08 for 3DCRT. In the SCR regression analyses, IMRT was associated with significantly lower risks of PCE (HR=0.26) and PE (HR=0.49), and greater overall survival (probability of beneficial effect (pbe)>0.99), after controlling for known clinical prognostic factors. IMRT reduces the incidence and postpones the onset of PCE and PE, and increases survival probability, compared to 3DCRT. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  12. An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan.

    PubMed

    Chang, Hsien-Yen; Weiner, Jonathan P

    2010-01-18

    Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI) programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG) case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234), while those in both 2002 and 2003 were included for prospective analyses (n = 164,562). Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group) model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster). When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Given the widespread availability of claims data and the superior explanatory

  13. Bayesian Unimodal Density Regression for Causal Inference

    ERIC Educational Resources Information Center

    Karabatsos, George; Walker, Stephen G.

    2011-01-01

    Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…

  14. The relationship between the C-statistic of a risk-adjustment model and the accuracy of hospital report cards: a Monte Carlo Study.

    PubMed

    Austin, Peter C; Reeves, Mathew J

    2013-03-01

    Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards. To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards. Monte Carlo simulations were used to examine this issue. We examined the influence of 3 factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada. The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact. The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card.

  15. The relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards: A Monte Carlo study

    PubMed Central

    Austin, Peter C.; Reeves, Mathew J.

    2015-01-01

    Background Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk-adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards. Objectives To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards. Research Design Monte Carlo simulations were used to examine this issue. We examined the influence of three factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk-adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada. Results The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact. Conclusions The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card. PMID:23295579

  16. Behavioral adjustment of siblings of children with autism engaged in applied behavior analysis early intervention programs: the moderating role of social support.

    PubMed

    Hastings, Richard P

    2003-04-01

    There have been few studies of the impact of intensive home-based early applied behavior analysis (ABA) intervention for children with autism on family functioning. In the present study, behavioral adjustment was explored in 78 siblings of children with autism on ABA programs. First, mothers' ratings of sibling adjustment were compared to a normative sample. There were no reported increases in behavioral adjustment problems in the present sample. Second, regression analyses revealed that social support functioned as a moderator of the impact of autism severity on sibling adjustment rather than a mediator or compensatory variable. In particular, siblings in families with a less severely autistic child had fewer adjustment problems when more formal social support was also available to the family. The implications of these data for future research and for practice are discussed.

  17. Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

    PubMed

    Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

    2009-07-01

    Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

  18. ASSOCIATIVE ADJUSTMENTS TO REDUCE ERRORS IN DOCUMENT SEARCHING.

    ERIC Educational Resources Information Center

    BRYANT, EDWARD C.; AND OTHERS

    ASSOCIATIVE ADJUSTMENTS TO A DOCUMENT FILE ARE CONSIDERED AS A MEANS FOR IMPROVING RETRIEVAL. A THEORETICAL INVESTIGATION OF THE STATISTICAL PROPERTIES OF A GENERALIZED MISMATCH MEASURE WAS CARRIED OUT AND IMPROVEMENTS IN RETRIEVAL RESULTING FROM PERFORMING ASSOCIATIVE REGRESSION ADJUSTMENTS ON DATA FILE WERE EXAMINED BOTH FROM THE THEORETICAL AND…

  19. Acculturation, personality, and psychological adjustment.

    PubMed

    Ahadi, Stephan A; Puente-Díaz, Rogelio

    2011-12-01

    Two studies investigated relationships between traditional indicators of acculturation, cultural distance, acculturation strategies, and basic dimensions of personality as they pertain to psychological adjustment among Hispanic students. Although personality characteristics have been shown to be important determinants of psychological well-being, acculturation research has put less emphasis on the role of personality in the well-being of immigrants. Hierarchical regression analysis showed that basic dimensions of personality such as extraversion and neuroticism were strongly related to psychological adjustment. Acculturation strategies did not mediate the effect of personality variables, but cultural resistance made a small, independent contribution to the explanation of some aspects of negative psychological adjustment. The implications of the results were discussed.

  20. A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

    USGS Publications Warehouse

    Robertson, Dale M.; Saad, D.A.; Heisey, D.M.

    2006-01-01

    Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

  1. The use of Quality-Adjusted Life Years in cost-effectiveness analyses in palliative care: Mapping the debate through an integrative review.

    PubMed

    Wichmann, Anne B; Adang, Eddy Mm; Stalmeier, Peep Fm; Kristanti, Sinta; Van den Block, Lieve; Vernooij-Dassen, Myrra Jfj; Engels, Yvonne

    2017-04-01

    In cost-effectiveness analyses in healthcare, Quality-Adjusted Life Years are often used as outcome measure of effectiveness. However, there is an ongoing debate concerning the appropriateness of its use for decision-making in palliative care. To systematically map pros and cons of using the Quality-Adjusted Life Year to inform decisions on resource allocation among palliative care interventions, as brought forward in the debate, and to discuss the Quality-Adjusted Life Year's value for palliative care. The integrative review method of Whittemore and Knafl was followed. Theoretical arguments and empirical findings were mapped. A literature search was conducted in PubMed, EMBASE, and CINAHL, in which MeSH (Medical Subject Headings) terms were Palliative Care, Cost-Benefit Analysis, Quality of Life, and Quality-Adjusted Life Years. Three themes regarding the pros and cons were identified: (1) restrictions in life years gained, (2) conceptualization of quality of life and its measurement, including suggestions to adapt this, and (3) valuation and additivity of time, referring to changing valuation of time. The debate is recognized in empirical studies, but alternatives not yet applied. The Quality-Adjusted Life Year might be more valuable for palliative care if specific issues are taken into account. Despite restrictions in life years gained, Quality-Adjusted Life Years can be achieved in palliative care. However, in measuring quality of life, we recommend to-in addition to the EQ-5D- make use of quality of life or capability instruments specifically for palliative care. Also, we suggest exploring the possibility of integrating valuation of time in a non-linear way in the Quality-Adjusted Life Year.

  2. The use of Quality-Adjusted Life Years in cost-effectiveness analyses in palliative care: Mapping the debate through an integrative review

    PubMed Central

    Wichmann, Anne B; Adang, Eddy MM; Stalmeier, Peep FM; Kristanti, Sinta; Van den Block, Lieve; Vernooij-Dassen, Myrra JFJ; Engels, Yvonne

    2017-01-01

    Background: In cost-effectiveness analyses in healthcare, Quality-Adjusted Life Years are often used as outcome measure of effectiveness. However, there is an ongoing debate concerning the appropriateness of its use for decision-making in palliative care. Aim: To systematically map pros and cons of using the Quality-Adjusted Life Year to inform decisions on resource allocation among palliative care interventions, as brought forward in the debate, and to discuss the Quality-Adjusted Life Year’s value for palliative care. Design: The integrative review method of Whittemore and Knafl was followed. Theoretical arguments and empirical findings were mapped. Data sources: A literature search was conducted in PubMed, EMBASE, and CINAHL, in which MeSH (Medical Subject Headings) terms were Palliative Care, Cost-Benefit Analysis, Quality of Life, and Quality-Adjusted Life Years. Findings: Three themes regarding the pros and cons were identified: (1) restrictions in life years gained, (2) conceptualization of quality of life and its measurement, including suggestions to adapt this, and (3) valuation and additivity of time, referring to changing valuation of time. The debate is recognized in empirical studies, but alternatives not yet applied. Conclusion: The Quality-Adjusted Life Year might be more valuable for palliative care if specific issues are taken into account. Despite restrictions in life years gained, Quality-Adjusted Life Years can be achieved in palliative care. However, in measuring quality of life, we recommend to—in addition to the EQ-5D— make use of quality of life or capability instruments specifically for palliative care. Also, we suggest exploring the possibility of integrating valuation of time in a non-linear way in the Quality-Adjusted Life Year. PMID:28190374

  3. Controlling Type I Error Rates in Assessing DIF for Logistic Regression Method Combined with SIBTEST Regression Correction Procedure and DIF-Free-Then-DIF Strategy

    ERIC Educational Resources Information Center

    Shih, Ching-Lin; Liu, Tien-Hsiang; Wang, Wen-Chung

    2014-01-01

    The simultaneous item bias test (SIBTEST) method regression procedure and the differential item functioning (DIF)-free-then-DIF strategy are applied to the logistic regression (LR) method simultaneously in this study. These procedures are used to adjust the effects of matching true score on observed score and to better control the Type I error…

  4. A Developmental Sequence Model to University Adjustment of International Undergraduate Students

    ERIC Educational Resources Information Center

    Chavoshi, Saeid; Wintre, Maxine Gallander; Dentakos, Stella; Wright, Lorna

    2017-01-01

    The current study proposes a Developmental Sequence Model to University Adjustment and uses a multifaceted measure, including academic, social and psychological adjustment, to examine factors predictive of undergraduate international student adjustment. A hierarchic regression model is carried out on the Student Adaptation to College Questionnaire…

  5. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD)-Level Meta-Regression Analyses

    PubMed Central

    Cashman, Kevin D.; Ritz, Christian; Kiely, Mairead

    2017-01-01

    Dietary Reference Values (DRVs) for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs) are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD)-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years) of the vitamin D intake–serum 25-hydroxyvitamin D (25(OH)D) dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OH)D concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years) from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OH)D >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OH)D to vitamin D intake. PMID:28481259

  6. Effects of early exposure and lifetime exposure to intimate partner violence (IPV) on child adjustment.

    PubMed

    Graham-Bermann, Sandra A; Perkins, Suzanne

    2010-01-01

    Children exposed to overwhelming and potentially traumatic events early in their lives are considered at-risk for problems in adjustment. Yet it is not known whether it is the age of first exposure (AFE) to violence or the amount of violence that the child witnessed in their lifetime that has the greatest impact on adjustment. For a sample of 190 children ages 6 to 12 exposed to intimate partner violence, their mothers reported that the average length of their abusive relationship was 10 years. The majority of children were first exposed to family violence as infants (64%), with only 12% first exposed when school-aged. Both the AFE and an estimate of the cumulative amount of violence were significantly and negatively related to children's behavioral problems. However, in regression analyses controlling for child sex, ethnicity, age, and family environment variables, cumulative violence exposure accounted for greater variance in adjustment than did AFE. Furthermore, cumulative violence exposure mediated the relationship between AFE and externalizing behavior problems, indicating that the cumulative exposure to IPV outweighed the AFE in its effect on child adjustment.

  7. Regression estimators for generic health-related quality of life and quality-adjusted life years.

    PubMed

    Basu, Anirban; Manca, Andrea

    2012-01-01

    To develop regression models for outcomes with truncated supports, such as health-related quality of life (HRQoL) data, and account for features typical of such data such as a skewed distribution, spikes at 1 or 0, and heteroskedasticity. Regression estimators based on features of the Beta distribution. First, both a single equation and a 2-part model are presented, along with estimation algorithms based on maximum-likelihood, quasi-likelihood, and Bayesian Markov-chain Monte Carlo methods. A novel Bayesian quasi-likelihood estimator is proposed. Second, a simulation exercise is presented to assess the performance of the proposed estimators against ordinary least squares (OLS) regression for a variety of HRQoL distributions that are encountered in practice. Finally, the performance of the proposed estimators is assessed by using them to quantify the treatment effect on QALYs in the EVALUATE hysterectomy trial. Overall model fit is studied using several goodness-of-fit tests such as Pearson's correlation test, link and reset tests, and a modified Hosmer-Lemeshow test. The simulation results indicate that the proposed methods are more robust in estimating covariate effects than OLS, especially when the effects are large or the HRQoL distribution has a large spike at 1. Quasi-likelihood techniques are more robust than maximum likelihood estimators. When applied to the EVALUATE trial, all but the maximum likelihood estimators produce unbiased estimates of the treatment effect. One and 2-part Beta regression models provide flexible approaches to regress the outcomes with truncated supports, such as HRQoL, on covariates, after accounting for many idiosyncratic features of the outcomes distribution. This work will provide applied researchers with a practical set of tools to model outcomes in cost-effectiveness analysis.

  8. Meta-regression analyses, meta-analyses, and trial sequential analyses of the effects of supplementation with beta-carotene, vitamin A, and vitamin E singly or in different combinations on all-cause mortality: do we have evidence for lack of harm?

    PubMed

    Bjelakovic, Goran; Nikolova, Dimitrinka; Gluud, Christian

    2013-01-01

    Evidence shows that antioxidant supplements may increase mortality. Our aims were to assess whether different doses of beta-carotene, vitamin A, and vitamin E affect mortality in primary and secondary prevention randomized clinical trials with low risk of bias. The present study is based on our 2012 Cochrane systematic review analyzing beneficial and harmful effects of antioxidant supplements in adults. Using random-effects meta-analyses, meta-regression analyses, and trial sequential analyses, we examined the association between beta-carotene, vitamin A, and vitamin E, and mortality according to their daily doses and doses below and above the recommended daily allowances (RDA). We included 53 randomized trials with low risk of bias (241,883 participants, aged 18 to 103 years, 44.6% women) assessing beta-carotene, vitamin A, and vitamin E. Meta-regression analysis showed that the dose of vitamin A was significantly positively associated with all-cause mortality. Beta-carotene in a dose above 9.6 mg significantly increased mortality (relative risk (RR) 1.06, 95% confidence interval (CI) 1.02 to 1.09, I(2) = 13%). Vitamin A in a dose above the RDA (> 800 µg) did not significantly influence mortality (RR 1.08, 95% CI 0.98 to 1.19, I(2) = 53%). Vitamin E in a dose above the RDA (> 15 mg) significantly increased mortality (RR 1.03, 95% CI 1.00 to 1.05, I(2) = 0%). Doses below the RDAs did not affect mortality, but data were sparse. Beta-carotene and vitamin E in doses higher than the RDA seem to significantly increase mortality, whereas we lack information on vitamin A. Dose of vitamin A was significantly associated with increased mortality in meta-regression. We lack information on doses below the RDA. All essential compounds to stay healthy cannot be synthesized in our body. Therefore, these compounds must be taken through our diet or obtained in other ways [1]. Oxidative stress has been suggested to cause a variety of diseases [2]. Therefore, it is speculated that

  9. Introduction to the use of regression models in epidemiology.

    PubMed

    Bender, Ralf

    2009-01-01

    Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

  10. Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

    PubMed

    Nixon, R M; Thompson, S G

    2003-09-15

    Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.

  11. Regression equations for estimation of annual peak-streamflow frequency for undeveloped watersheds in Texas using an L-moment-based, PRESS-minimized, residual-adjusted approach

    USGS Publications Warehouse

    Asquith, William H.; Roussel, Meghan C.

    2009-01-01

    Annual peak-streamflow frequency estimates are needed for flood-plain management; for objective assessment of flood risk; for cost-effective design of dams, levees, and other flood-control structures; and for design of roads, bridges, and culverts. Annual peak-streamflow frequency represents the peak streamflow for nine recurrence intervals of 2, 5, 10, 25, 50, 100, 200, 250, and 500 years. Common methods for estimation of peak-streamflow frequency for ungaged or unmonitored watersheds are regression equations for each recurrence interval developed for one or more regions; such regional equations are the subject of this report. The method is based on analysis of annual peak-streamflow data from U.S. Geological Survey streamflow-gaging stations (stations). Beginning in 2007, the U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, began a 3-year investigation concerning the development of regional equations to estimate annual peak-streamflow frequency for undeveloped watersheds in Texas. The investigation focuses primarily on 638 stations with 8 or more years of data from undeveloped watersheds and other criteria. The general approach is explicitly limited to the use of L-moment statistics, which are used in conjunction with a technique of multi-linear regression referred to as PRESS minimization. The approach used to develop the regional equations, which was refined during the investigation, is referred to as the 'L-moment-based, PRESS-minimized, residual-adjusted approach'. For the approach, seven unique distributions are fit to the sample L-moments of the data for each of 638 stations and trimmed means of the seven results of the distributions for each recurrence interval are used to define the station specific, peak-streamflow frequency. As a first iteration of regression, nine weighted-least-squares, PRESS-minimized, multi-linear regression equations are computed using the watershed

  12. Visual field progression in glaucoma: estimating the overall significance of deterioration with permutation analyses of pointwise linear regression (PoPLR).

    PubMed

    O'Leary, Neil; Chauhan, Balwantray C; Artes, Paul H

    2012-10-01

    To establish a method for estimating the overall statistical significance of visual field deterioration from an individual patient's data, and to compare its performance to pointwise linear regression. The Truncated Product Method was used to calculate a statistic S that combines evidence of deterioration from individual test locations in the visual field. The overall statistical significance (P value) of visual field deterioration was inferred by comparing S with its permutation distribution, derived from repeated reordering of the visual field series. Permutation of pointwise linear regression (PoPLR) and pointwise linear regression were evaluated in data from patients with glaucoma (944 eyes, median mean deviation -2.9 dB, interquartile range: -6.3, -1.2 dB) followed for more than 4 years (median 10 examinations over 8 years). False-positive rates were estimated from randomly reordered series of this dataset, and hit rates (proportion of eyes with significant deterioration) were estimated from the original series. The false-positive rates of PoPLR were indistinguishable from the corresponding nominal significance levels and were independent of baseline visual field damage and length of follow-up. At P < 0.05, the hit rates of PoPLR were 12, 29, and 42%, at the fifth, eighth, and final examinations, respectively, and at matching specificities they were consistently higher than those of pointwise linear regression. In contrast to population-based progression analyses, PoPLR provides a continuous estimate of statistical significance for visual field deterioration individualized to a particular patient's data. This allows close control over specificity, essential for monitoring patients in clinical practice and in clinical trials.

  13. Unemployment and psychosocial outcomes to age 30: A fixed-effects regression analysis.

    PubMed

    Fergusson, David M; McLeod, Geraldine F; Horwood, L John

    2014-08-01

    We aimed to examine the associations between exposure to unemployment and psychosocial outcomes over the period from 16 to 30 years, using data from a well-studied birth cohort. Data were collected over the course of the Christchurch Health and Development Study, a longitudinal study of a birth cohort of 1265 children, born in Christchurch in 1977, who have been studied to age 30. Assessments of unemployment and psychosocial outcomes (mental health, substance abuse/dependence, criminal offending, adverse life events and life satisfaction) were obtained at ages 18, 21, 25 and 30. Prior to adjustment, an increasing duration of unemployment was associated with significant increases in the risk of all psychosocial outcomes. These associations were adjusted for confounding using conditional, fixed-effects regression techniques. The analyses showed significant (p < 0.05) or marginally significant (p < 0.10) associations between the duration of unemployment and major depression (p = 0.05), alcohol abuse/dependence (p = 0.043), illicit substance abuse/dependence (p = 0.017), property/violent offending (p < 0.001), arrests/convictions (p = 0.052), serious financial problems (p = 0.007) and life satisfaction (p = 0.092). To test for reverse causality, the fixed-effects regression models were extended to include lagged, time-dynamic variables representing the respondent's psychosocial burden prior to the experience of unemployment. The findings suggested that the association between unemployment and psychosocial outcomes was likely to involve a causal process in which unemployment led to increased risks of adverse psychosocial outcomes. Effect sizes were estimated using attributable risk; exposure to unemployment accounted for between 4.2 and 14.0% (median 10.8%) of the risk of experiencing the significant psychosocial outcomes. The findings of this study suggest that exposure to unemployment had small but pervasive effects on psychosocial adjustment in adolescence and young

  14. Adjusting for partial verification or workup bias in meta-analyses of diagnostic accuracy studies.

    PubMed

    de Groot, Joris A H; Dendukuri, Nandini; Janssen, Kristel J M; Reitsma, Johannes B; Brophy, James; Joseph, Lawrence; Bossuyt, Patrick M M; Moons, Karel G M

    2012-04-15

    A key requirement in the design of diagnostic accuracy studies is that all study participants receive both the test under evaluation and the reference standard test. For a variety of practical and ethical reasons, sometimes only a proportion of patients receive the reference standard, which can bias the accuracy estimates. Numerous methods have been described for correcting this partial verification bias or workup bias in individual studies. In this article, the authors describe a Bayesian method for obtaining adjusted results from a diagnostic meta-analysis when partial verification or workup bias is present in a subset of the primary studies. The method corrects for verification bias without having to exclude primary studies with verification bias, thus preserving the main advantages of a meta-analysis: increased precision and better generalizability. The results of this method are compared with the existing methods for dealing with verification bias in diagnostic meta-analyses. For illustration, the authors use empirical data from a systematic review of studies of the accuracy of the immunohistochemistry test for diagnosis of human epidermal growth factor receptor 2 status in breast cancer patients.

  15. [Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

    PubMed

    Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

    2017-03-10

    To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

  16. Publication Bias and Nonreporting Found in Majority of Systematic Reviews and Meta-analyses in Anesthesiology Journals.

    PubMed

    Hedin, Riley J; Umberham, Blake A; Detweiler, Byron N; Kollmorgen, Lauren; Vassar, Matt

    2016-10-01

    Systematic reviews and meta-analyses are used by clinicians to derive treatment guidelines and make resource allocation decisions in anesthesiology. One cause for concern with such reviews is the possibility that results from unpublished trials are not represented in the review findings or data synthesis. This problem, known as publication bias, results when studies reporting statistically nonsignificant findings are left unpublished and, therefore, not included in meta-analyses when estimating a pooled treatment effect. In turn, publication bias may lead to skewed results with overestimated effect sizes. The primary objective of this study is to determine the extent to which evaluations for publication bias are conducted by systematic reviewers in highly ranked anesthesiology journals and which practices reviewers use to mitigate publication bias. The secondary objective of this study is to conduct publication bias analyses on the meta-analyses that did not perform these assessments and examine the adjusted pooled effect estimates after accounting for publication bias. This study considered meta-analyses and systematic reviews from 5 peer-reviewed anesthesia journals from 2007 through 2015. A PubMed search was conducted, and full-text systematic reviews that fit inclusion criteria were downloaded and coded independently by 2 authors. Coding was then validated, and disagreements were settled by consensus. In total, 207 systematic reviews were included for analysis. In addition, publication bias evaluation was performed for 25 systematic reviews that did not do so originally. We used Egger regression, Duval and Tweedie trim and fill, and funnel plots for these analyses. Fifty-five percent (n = 114) of the reviews discussed publication bias, and 43% (n = 89) of the reviews evaluated publication bias. Funnel plots and Egger regression were the most common methods for evaluating publication bias. Publication bias was reported in 34 reviews (16%). Thirty-six of the 45

  17. Wheat flour dough Alveograph characteristics predicted by Mixolab regression models.

    PubMed

    Codină, Georgiana Gabriela; Mironeasa, Silvia; Mironeasa, Costel; Popa, Ciprian N; Tamba-Berehoiu, Radiana

    2012-02-01

    In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P < 0.05 and P < 0.01) between the parameters of wheat dough studied by the Mixolab and its rheological properties measured with the Alveograph. A number of six predictive linear equations were obtained. Linear regression models gave multiple regression coefficients with R²(adjusted) > 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval. Copyright © 2011 Society of Chemical Industry.

  18. The influence of family stability on self-control and adjustment.

    PubMed

    Malatras, Jennifer Weil; Israel, Allen C

    2013-07-01

    The aim of the present study was to replicate previous evidence for a model in which self-control mediates the relationship between family stability and internalizing symptoms, and to evaluate a similar model with regard to externalizing problems. Participants were 155 female and 134 male undergraduates--mean age of 19.03 years. Participants completed measures of stability in the family of origin (Stability of Activities in the Family Environment), self-control (Self-Control scale), current externalizing (Adult Self-Report), and internalizing problems (Beck Depression Inventory II and Beck Anxiety Inventory). Multiple regression analyses largely support the proposed model for both the externalizing and internalizing domains. Family stability may foster the development of self-control and, in turn, lead to positive adjustment. © 2012 Wiley Periodicals, Inc.

  19. Physical Discipline and Children's Adjustment: Cultural Normativeness as a Moderator

    PubMed Central

    Lansford, Jennifer E.; Chang, Lei; Dodge, Kenneth A.; Malone, Patrick S.; Oburu, Paul; Palmérus, Kerstin; Bacchini, Dario; Pastorelli, Concetta; Bombi, Anna Silvia; Zelli, Arnaldo; Tapanya, Sombat; Chaudhary, Nandita; Deater-Deckard, Kirby; Manke, Beth; Quinn, Naomi

    2009-01-01

    Interviews were conducted with 336 mother – child dyads (children's ages ranged from 6 to 17 years; mothers' ages ranged from 20 to 59 years) in China, India, Italy, Kenya, the Philippines, and Thailand to examine whether normativeness of physical discipline moderates the link between mothers' use of physical discipline and children's adjustment. Multilevel regression analyses revealed that physical discipline was less strongly associated with adverse child outcomes in conditions of greater perceived normativeness, but physical discipline was also associated with more adverse outcomes regardless of its perceived normativeness. Countries with the lowest use of physical discipline showed the strongest association between mothers' use and children's behavior problems, but in all countries higher use of physical discipline was associated with more aggression and anxiety. PMID:16274437

  20. An interpersonal perspective on depression: the role of marital adjustment, conflict communication, attributions, and attachment within a clinical sample.

    PubMed

    Heene, Els; Buysse, Ann; Van Oost, Paulette

    2007-12-01

    Previous studies have focused on the difficulties in psychosocial functioning in depressed persons, underscoring the distress experienced by both spouses. We selected conflict communication, attribution, and attachment as important domains of depression in the context of marital adjustment, and we analyzed two hypotheses in one single study. First, we analyzed whether a clinical sample of couples with a depressed patient would differ significantly from a control group on these variables. Second, we explored to what degree these variables mediate/moderate the relationship between depressive symptoms and marital adjustment. The perspectives of both spouses were taken into account, as well as gender differences. In total, 69 clinical and 69 control couples were recruited, and a series of multivariate analyses of variance and regression analyses were conducted to test both hypotheses. Results indicated that both patients and their partners reported less marital adjustment associated with more negative perceptions on conflict communication, causal attributions, and insecure attachment. In addition, conflict communication and causal attributions were significant mediators of the association between depressive symptoms and marital adjustment for both depressed men and women, and causal attributions also moderated this link. Ambivalent attachment was a significant mediator only for the female identified patients. Several sex differences and clinical implications are discussed.

  1. A Simulation Investigation of Principal Component Regression.

    ERIC Educational Resources Information Center

    Allen, David E.

    Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

  2. Changes in social adjustment with cognitive processing therapy: effects of treatment and association with PTSD symptom change.

    PubMed

    Monson, Candice M; Macdonald, Alexandra; Vorstenbosch, Valerie; Shnaider, Philippe; Goldstein, Elizabeth S R; Ferrier-Auerbach, Amanda G; Mocciola, Katharine E

    2012-10-01

    The current study sought to determine if different spheres of social adjustment, social and leisure, family, and work and income improved immediately following a course of cognitive processing therapy (CPT) when compared with those on a waiting list in a sample of 46 U.S. veterans diagnosed with posttraumatic stress disorder (PTSD). We also sought to determine whether changes in different PTSD symptom clusters were associated with changes in these spheres of social adjustment. Overall social adjustment, extended family relationships, and housework completion significantly improved in the CPT versus waiting-list condition, η(2) = .08 to .11. Hierarchical multiple regression analyses revealed that improvements in total clinician-rated PTSD symptoms were associated with improvements in overall social and housework adjustment. When changes in reexperiencing, avoidance, emotional numbing, and hyperarousal were all in the model accounting for changes in total social adjustment, improvements in emotional numbing symptoms were associated with improvements in overall social, extended family, and housework adjustment (β = .38 to .55). In addition, improvements in avoidance symptoms were associated with improvements in housework adjustment (β = .30), but associated with declines in extended family adjustment (β = -.34). Results suggest that it is important to consider the extent to which PTSD treatments effectively reduce specific types of symptoms, particularly emotional numbing and avoidance, to generally improve social adjustment. Copyright © 2012 International Society for Traumatic Stress Studies.

  3. Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

    PubMed

    Henrard, S; Speybroeck, N; Hermans, C

    2015-11-01

    Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

  4. Case mix adjusted variation in cesarean section rate in Sweden.

    PubMed

    Mesterton, Johan; Ladfors, Lars; Ekenberg Abreu, Anna; Lindgren, Peter; Saltvedt, Sissel; Weichselbraun, Marianne; Amer-Wåhlin, Isis

    2017-05-01

    Cesarean section (CS) rate is a well-established indicator of performance in maternity care and is also related to resource use. Case mix adjustment of CS rates when performing comparisons between hospitals is important. The objective of this study was to estimate case mix adjusted variation in CS rate between hospitals in Sweden. In total, 139 756 deliveries in 2011 and 2012 were identified in administrative systems in seven regions covering 67% of all deliveries in Sweden. Data were linked to the Medical birth register and population data. Twenty-three different sociodemographic and clinical characteristics were used for adjustment. Analyses were performed for the entire study population as well as for two subgroups. Logistic regression was used to analyze differences between hospitals. The overall CS rate was 16.9% (hospital minimum-maximum 12.1-22.6%). Significant variations in CS rate between hospitals were observed after case mix adjustment: hospital odds ratios for CS varied from 0.62 (95% CI 0.53-0.73) to 1.45 (95% CI 1.37-1.52). In nulliparous, cephalic, full-term, singletons the overall CS rate was 14.3% (hospital minimum-maximum: 9.0-19.0%), whereas it was 4.7% for multiparous, cephalic, full-term, singletons with no previous CS (hospital minimum-maximum: 3.2-6.7%). In both subgroups significant variations were observed in case mix adjusted CS rates. Significant differences in CS rate between Swedish hospitals were found after adjusting for differences in case mix. This indicates a potential for fewer interventions and lower resource use in Swedish childbirth care. Best practice sharing and continuous monitoring are important tools for improving childbirth care. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  5. Logistic regression for circular data

    NASA Astrophysics Data System (ADS)

    Al-Daffaie, Kadhem; Khan, Shahjahan

    2017-05-01

    This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

  6. Temporal trends in sperm count: a systematic review and meta-regression analysis.

    PubMed

    Levine, Hagai; Jørgensen, Niels; Martino-Andrade, Anderson; Mendiola, Jaime; Weksler-Derri, Dan; Mindlis, Irina; Pinotti, Rachel; Swan, Shanna H

    2017-11-01

    Reported declines in sperm counts remain controversial today and recent trends are unknown. A definitive meta-analysis is critical given the predictive value of sperm count for fertility, morbidity and mortality. To provide a systematic review and meta-regression analysis of recent trends in sperm counts as measured by sperm concentration (SC) and total sperm count (TSC), and their modification by fertility and geographic group. PubMed/MEDLINE and EMBASE were searched for English language studies of human SC published in 1981-2013. Following a predefined protocol 7518 abstracts were screened and 2510 full articles reporting primary data on SC were reviewed. A total of 244 estimates of SC and TSC from 185 studies of 42 935 men who provided semen samples in 1973-2011 were extracted for meta-regression analysis, as well as information on years of sample collection and covariates [fertility group ('Unselected by fertility' versus 'Fertile'), geographic group ('Western', including North America, Europe Australia and New Zealand versus 'Other', including South America, Asia and Africa), age, ejaculation abstinence time, semen collection method, method of measuring SC and semen volume, exclusion criteria and indicators of completeness of covariate data]. The slopes of SC and TSC were estimated as functions of sample collection year using both simple linear regression and weighted meta-regression models and the latter were adjusted for pre-determined covariates and modification by fertility and geographic group. Assumptions were examined using multiple sensitivity analyses and nonlinear models. SC declined significantly between 1973 and 2011 (slope in unadjusted simple regression models -0.70 million/ml/year; 95% CI: -0.72 to -0.69; P < 0.001; slope in adjusted meta-regression models = -0.64; -1.06 to -0.22; P = 0.003). The slopes in the meta-regression model were modified by fertility (P for interaction = 0.064) and geographic group (P for interaction = 0.027). There was

  7. Regression Analysis: Legal Applications in Institutional Research

    ERIC Educational Resources Information Center

    Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.

    2008-01-01

    This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…

  8. 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.

  9. Survival Data and Regression Models

    NASA Astrophysics Data System (ADS)

    Grégoire, G.

    2014-12-01

    We start this chapter by introducing some basic elements for the analysis of censored survival data. Then we focus on right censored data and develop two types of regression models. The first one concerns the so-called accelerated failure time models (AFT), which are parametric models where a function of a parameter depends linearly on the covariables. The second one is a semiparametric model, where the covariables enter in a multiplicative form in the expression of the hazard rate function. The main statistical tool for analysing these regression models is the maximum likelihood methodology and, in spite we recall some essential results about the ML theory, we refer to the chapter "Logistic Regression" for a more detailed presentation.

  10. Discrimination and adjustment among Chinese American adolescents: family conflict and family cohesion as vulnerability and protective factors.

    PubMed

    Juang, Linda P; Alvarez, Alvin A

    2010-12-01

    We examined racial/ethnic discrimination experiences of Chinese American adolescents to determine how discrimination is linked to poor adjustment (i.e., loneliness, anxiety, and somatization) and how the context of the family can buffer or exacerbate these links. We collected survey data from 181 Chinese American adolescents and their parents in Northern California. We conducted hierarchical regression analyses to examine main effects and 2-way interactions of perceived discrimination with family conflict and family cohesion. Discrimination was related to poorer adjustment in terms of loneliness, anxiety, and somatization, but family conflict and cohesion modified these relations. Greater family conflict exacerbated the negative effects of discrimination, and greater family cohesion buffered the negative effects of discrimination. Our findings highlight the importance of identifying family-level moderators to help adolescents and their families handle experiences of discrimination.

  11. Physical disability, life stress, and psychosocial adjustment in multiple sclerosis.

    PubMed

    Zeldow, P B; Pavlou, M

    1984-02-01

    Eighty-one outpatients with diagnosed multiple sclerosis were studied in an effort to examine the relative contributions of physical health status, life stress, duration of illness, age, sex, marital status, and social class on various aspects of personal and interpersonal functioning. Stepwise multiple regression analyses were performed to identify the most significant discriminators of the seven psychosocial measures. Physical health status exerted the broadest influence, affecting personal efficiency and well-being, capacity for independent thought and action, self-confidence, self-reliance, and number of meaningful social contacts. Life stress was associated with lowered personal efficiency and sense of well-being. Duration of illness and the demographic variables had few or no effects on psychosocial adjustment. Discussion contrasts the present findings with others in the rehabilitation literature and specifies certain limitations of the study's design.

  12. Reliable change indices and regression-based measures for the Rey-Osterreith Complex Figure test in partial epilepsy patients.

    PubMed

    Nakhutina, L; Pramataris, P; Morrison, C; Devinsky, O; Barr, W B

    2010-01-01

    The Rey-Osterreith Complex Figure (ROCF) is commonly used in evaluations of patients undergoing epilepsy surgery. We assessed test-retest performance on ROCF in 30 partial epilepsy patients (mean interval = 33.7 months) to derive reliable change indices (RCIs) and regression-based measures for change. ROCF reproductions were rescored by three raters (IRR Copy: 0.963; Delayed Recall: 0.986). The derived adjusted RC (90% CI) cutoff values for the ROCF Copy were (or=8.4) and were (or=10.0) for the Delayed Recall. Results from regression-based analyses were negative, using age, education, seizure duration, and age of onset, whereas a baseline score was a significant predictor of a follow-up score. The results provide a means to evaluate long-term outcome in epilepsy patients using the ROCF.

  13. Linear regression metamodeling as a tool to summarize and present simulation model results.

    PubMed

    Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

    2013-10-01

    Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

  14. Preoperative psychological adjustment and surgical outcome are determinants of psychosocial status after anterior temporal lobectomy.

    PubMed Central

    Hermann, B P; Wyler, A R; Somes, G

    1992-01-01

    This investigation evaluated the role of preoperative psychological adjustment, degree of postoperative seizure reduction, and other relevant variables (age, education, IQ, age at onset of epilepsy, laterality of resection) in determining emotional/psychosocial outcome following anterior temporal lobectomy. Ninety seven patients with complex partial seizures of temporal lobe origin were administered the Minnesota Multiphasic Personality Inventory (MMPI), Washington Psychosocial Seizure Inventory (WPSI), and the General Health Questionnaire (GHQ) both before and six to eight months after anterior temporal lobectomy. The data were subjected to a nonparametric rank sum technique (O'Brien's procedure) which combined the test scores to form a single outcome index (TOTAL PSYCHOSOCIAL OUTCOME) that was analysed by multiple regression procedures. Results indicated that the most powerful predictors of patients' overall postoperative psychosocial outcome were: 1) The adequacy of their preoperative psychosocial adjustment, and 2) A totally seizure-free outcome. Additional analyses were carried out separately on the MMPI, WPSI, and GHQ to determine whether findings varied as a function of the specific outcome measure. These results were related to the larger literature concerned with the psychological outcome of anterior temporal lobectomy. PMID:1619418

  15. Uncertainty and psychological adjustment in patients with lung cancer

    PubMed Central

    Kurita, Keiko; Garon, Edward B.; Stanton, Annette L.; Meyerowitz, Beth E.

    2014-01-01

    Background For many patients with lung cancer, disease progression occurs without notice or with vague symptoms, and unfortunately, most treatments are not curative. Given this unpredictability, we hypothesized the following: (1) poorer psychological adjustment (specifically, more depressive symptoms, higher perceptions of stress, and poorer emotional well-being) would be associated with higher intolerance for uncertainty, higher perceived illness-related ambiguity, and their interaction; and (2) greater avoidance would mediate associations between higher intolerance of uncertainty and poorer psychological adjustment. Methods Participants (N = 49) diagnosed with lung cancer at least 6 months prior to enrollment completed the Center for Epidemiologic Studies – Depression Scale, the Functional Assessment of Cancer Therapy – Lung Emotional Well-being subscale, the Perceived Stress scale, the Intolerance of Uncertainty scale, the Mishel Uncertainty in Illness Scale Ambiguity subscale, the Impact of Event – Revised Avoidance subscale, and the Short-scale Eysenck Personality Questionnaire – Revised Neuroticism subscale. Mean age was 64.2 years (standard deviation [SD] = 11.0), mean years of education was 15.6 (SD = 3.1), and 71.4% were female. Hypotheses were tested with regression analyses, adjusted for neuroticism. Results Higher perceptions of stress and poorer emotional well-being were associated with higher levels of intolerance of uncertainty and higher perceived illness-related ambiguity. Non-somatic depressive symptoms were associated with higher levels of intolerance of uncertainty. Avoidance was found to mediate relations of intolerance of uncertainty with non-somatic depressive symptoms and emotional well-being only. Conclusions Findings suggest that interventions to address avoidance and intolerance of uncertainty in individuals with lung cancer may help improve psychological adjustment. PMID:22887017

  16. Regression approaches in the test-negative study design for assessment of influenza vaccine effectiveness.

    PubMed

    Bond, H S; Sullivan, S G; Cowling, B J

    2016-06-01

    Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.

  17. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus.

    PubMed

    Cohen, Mark E; Ko, Clifford Y; Bilimoria, Karl Y; Zhou, Lynn; Huffman, Kristopher; Wang, Xue; Liu, Yaoming; Kraemer, Kari; Meng, Xiangju; Merkow, Ryan; Chow, Warren; Matel, Brian; Richards, Karen; Hart, Amy J; Dimick, Justin B; Hall, Bruce L

    2013-08-01

    The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) collects detailed clinical data from participating hospitals using standardized data definitions, analyzes these data, and provides participating hospitals with reports that permit risk-adjusted comparisons with a surgical quality standard. Since its inception, the ACS NSQIP has worked to refine surgical outcomes measurements and enhance statistical methods to improve the reliability and validity of this hospital profiling. From an original focus on controlling for between-hospital differences in patient risk factors with logistic regression, ACS NSQIP has added a variable to better adjust for the complexity and risk profile of surgical procedures (procedure mix adjustment) and stabilized estimates derived from small samples by using a hierarchical model with shrinkage adjustment. New models have been developed focusing on specific surgical procedures (eg, "Procedure Targeted" models), which provide opportunities to incorporate indication and other procedure-specific variables and outcomes to improve risk adjustment. In addition, comparative benchmark reports given to participating hospitals have been expanded considerably to allow more detailed evaluations of performance. Finally, procedures have been developed to estimate surgical risk for individual patients. This article describes the development of, and justification for, these new statistical methods and reporting strategies in ACS NSQIP. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  18. Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

    PubMed

    Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

    2006-11-01

    We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

  19. Parental Psychological Control and Adolescent Adjustment: The Role of Adolescent Emotion Regulation

    PubMed Central

    Cui, Lixian; Morris, Amanda Sheffield; Criss, Michael M.; Houltberg, Benjamin J.; Silk, Jennifer S.

    2014-01-01

    SYNOPSIS Objective This study investigated associations between parental psychological control and aggressive behavior and depressive symptoms among adolescents from predominantly disadvantaged backgrounds. The indirect effects of psychological control on adolescent adjustment through adolescent emotion regulation (anger and sadness regulation) were examined as well as the moderating effects of adolescent emotion regulation. Design 206 adolescents (ages 10–18) reported on parental psychological control and their own depressive symptoms, and parents and adolescents reported on adolescent emotion regulation and aggressive behavior. Indirect effect models were tested using structural equation modeling; moderating effects were tested using hierarchical multiple regression. Results The associations between parental psychological control and adolescent aggressive behavior and depressive symptoms were indirect through adolescents’ anger regulation. Moderation analyses indicated that the association between parental psychological control and adolescent depressive symptoms was stronger among adolescents with poor sadness regulation and the association between psychological control and aggressive behavior was stronger among older adolescents with poor anger regulation. Conclusions Psychological control is negatively associated with adolescent adjustment, particularly among adolescents who have difficulty regulating emotions. Emotion regulation is one mechanism through which psychological control is linked to adolescent adjustment, particularly anger dysregulation, and this pattern holds for both younger and older adolescents and for both boys and girls. PMID:25057264

  20. Risk-adjusted monitoring of survival times

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

    Sego, Landon H.; Reynolds, Marion R.; Woodall, William H.

    2009-02-26

    We consider the monitoring of clinical outcomes, where each patient has a di®erent risk of death prior to undergoing a health care procedure.We propose a risk-adjusted survival time CUSUM chart (RAST CUSUM) for monitoring clinical outcomes where the primary endpoint is a continuous, time-to-event variable that may be right censored. Risk adjustment is accomplished using accelerated failure time regression models. We compare the average run length performance of the RAST CUSUM chart to the risk-adjusted Bernoulli CUSUM chart, using data from cardiac surgeries to motivate the details of the comparison. The comparisons show that the RAST CUSUM chart is moremore » efficient at detecting a sudden decrease in the odds of death than the risk-adjusted Bernoulli CUSUM chart, especially when the fraction of censored observations is not too high. We also discuss the implementation of a prospective monitoring scheme using the RAST CUSUM chart.« less

  1. The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

    PubMed

    Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

    2017-01-01

    Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

  2. The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses

    PubMed Central

    Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

    2017-01-01

    Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = −0.11, 95% CI = [−0.19, −0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = −0.70, 95% CI = [−1.02, −0.38], p < 0.001), as well as dtransfer for cueing (β = −0.60, 95% CI = [−0.92, −0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning. PMID:28854205

  3. Predicting Word Reading Ability: A Quantile Regression Study

    ERIC Educational Resources Information Center

    McIlraith, Autumn L.

    2018-01-01

    Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

  4. [Relationship between family variables and conjugal adjustment].

    PubMed

    Jiménez-Picón, Nerea; Lima-Rodríguez, Joaquín-Salvador; Lima-Serrano, Marta

    2018-04-01

    To determine whether family variables, such as type of relationship, years of marriage, existence of offspring, number of members of family, stage of family life cycle, transition between stages, perceived social support, and/or stressful life events are related to conjugal adjustment. A cross-sectional and correlational study using questionnaires. Primary care and hospital units of selected centres in the province of Seville, Spain. Consecutive stratified sampling by quotas of 369 heterosexual couples over 18years of age, who maintained a relationship, with or without children, living in Seville. A self-report questionnaire for the sociodemographic variables, and the abbreviated version of the Dyadic Adjustment Scale, Questionnaire MOS Perceived Social Support, and Social Readjustment Rating Scale, were used. Descriptive and inferential statistics were performed with correlation analysis and multivariate regression. Statistically significant associations were found between conjugal adjustment and marriage years (r=-10: P<.05), stage of family life cycle (F=2.65; P<.05), the transition between stages (RPB=.11; P<.05) and perceived social support (r=.44; P<.001). The regression model showed the predictive power of perceived social support and the family life cycle stage (mature-aged stage) on conjugal adjustment (R2=.21; F=9.9; df=356; P<.001). Couples may be assessed from Primary Care and be provide with resources and support. In addition, it can identify variables that may help improve the conjugal relationship. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

  5. Estimating regression to the mean and true effects of an intervention in a four-wave panel study.

    PubMed

    Gmel, Gerhard; Wicki, Matthias; Rehm, Jürgen; Heeb, Jean-Luc

    2008-01-01

    First, to analyse whether a taxation-related decrease in spirit prices had a similar effect on spirit consumption for low-, medium- and high-level drinkers. Secondly, as the relationship between baseline values and post-intervention changes is confounded with regression to the mean (RTM) effects, to apply different approaches for estimating the RTM effect and true change. Consumption of spirits and total alcohol consumption were analysed in a four-wave panel study (one pre-intervention and three post-intervention measurements) of 889 alcohol consumers sampled from the general population of Switzerland. Two correlational methods, one method quantitatively estimating the RTM effect and one growth curve approach based on hierarchical linear models (HLM), were used to estimate RTM effects among low-, medium- and high-level drinkers. Adjusted for RTM effects, high-level drinkers increased consumption more than lighter drinkers in the short term, but this was not a persisting effect. Changes in taxation affected mainly light and moderate drinkers in the long term. All methods concurred that RTM effects were present to a considerable degree, and methods quantifying the RTM effect or adjusting for it yielded similar estimates. Intervention studies have to consider RTM effects both in the study design and in the evaluation methods. Observed changes can be adjusted for RTM effects and true change can be estimated. The recommended method, particularly if the aim is to estimate change not only for the sample as a whole, but for groups of drinkers with different baseline consumption levels, is growth curve modelling. If reliability of measurement instruments cannot be increased, the incorporation of more than one pre-intervention measurement point may be a valuable adjustment of the study design.

  6. Simple and multiple linear regression: sample size considerations.

    PubMed

    Hanley, James A

    2016-11-01

    The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Adjusted Analyses in Studies Addressing Therapy and Harm: Users' Guides to the Medical Literature.

    PubMed

    Agoritsas, Thomas; Merglen, Arnaud; Shah, Nilay D; O'Donnell, Martin; Guyatt, Gordon H

    2017-02-21

    Observational studies almost always have bias because prognostic factors are unequally distributed between patients exposed or not exposed to an intervention. The standard approach to dealing with this problem is adjusted or stratified analysis. Its principle is to use measurement of risk factors to create prognostically homogeneous groups and to combine effect estimates across groups.The purpose of this Users' Guide is to introduce readers to fundamental concepts underlying adjustment as a way of dealing with prognostic imbalance and to the basic principles and relative trustworthiness of various adjustment strategies.One alternative to the standard approach is propensity analysis, in which groups are matched according to the likelihood of membership in exposed or unexposed groups. Propensity methods can deal with multiple prognostic factors, even if there are relatively few patients having outcome events. However, propensity methods do not address other limitations of traditional adjustment: investigators may not have measured all relevant prognostic factors (or not accurately), and unknown factors may bias the results.A second approach, instrumental variable analysis, relies on identifying a variable associated with the likelihood of receiving the intervention but not associated with any prognostic factor or with the outcome (other than through the intervention); this could mimic randomization. However, as with assumptions of other adjustment approaches, it is never certain if an instrumental variable analysis eliminates bias.Although all these approaches can reduce the risk of bias in observational studies, none replace the balance of both known and unknown prognostic factors offered by randomization.

  8. Contextual variables associated with psychosocial adjustment of adolescents.

    PubMed

    Sbicigo, Juliana Burges; Dell'Aglio, Débora Dalbosco

    2013-01-01

    This study investigated associations of contextual variables of risk (stressful events and exposure to community violence), variables of protection (family environment, connectivity to the school and community perceptions) and demographic variables (gender and age) with indicators of psychosocial adjustment (self-esteem, involvement in illegal activities and alcohol use in past month) among adolescents. The participants were 685 students (61.5% girls) aged between 12 and 18 years (M = 15.10, SD = 1.52) of public schools in southern Brazil. They answered a questionnaire with 77 questions and an inventory for assessment of family relationships. Logistic regression analyses indicated that the negative perception of family environment, poor connectivity to the school and exposure to community violence were associated with low self-esteem. Involvement in illegal activities was associated with low connectivity to school, stressful events, exposure to community violence and male sex. Finally, alcohol use/month was associated with negative perception of the community, community violence, stressful events, and particularly at the ages of 15-16 years.

  9. Psychosocial Predictors of Adjustment among First Year College of Education Students

    ERIC Educational Resources Information Center

    Salami, Samuel O.

    2011-01-01

    The purpose of this study was to examine the contribution of psychological and social factors to the prediction of adjustment to college. A total of 250 first year students from colleges of education in Kwara State, Nigeria, completed measures of self-esteem, emotional intelligence, stress, social support and adjustment. Regression analyses…

  10. [The Relationship Between Marital Adjustment and Psychological Symptoms in Women: The Mediator Roles of Coping Strategies and Gender Role Attitudes].

    PubMed

    Yüksel, Özge; Dağ, İhsan

    2015-01-01

    The aim of this study were to investigate the mediator role of coping strategies and gender roles attitudes on the relationship between women's marital adjustment and psychological symptoms. 248 married women participated in the study. Participants completed Marital Adjustment Scale, Ways of Coping Questionnaire, Brief Symptom Inventory, Gender Role Attitudes Scale and Demographic Information Form. Regression analyses revealed that Submissive (Sobel z= -2.47, p<.01) and Helpless Coping Approach (Sobel z=-2.95, p<.001) have partial mediator role on the relationship between marital relationship score and psychological symptom level. Also, having Egalitarian Gender Role Attitude effects the psychological symptoms in relation with the marital relationship, but it is seen that this effect is not higher enough to play a mediator role (Sobel z =-1.21, p>.05). Regression analysis showed that there is a statistically significant correlation between women's marital adjustment and their psychological symptoms, indicating that the marital adjustment decreases as the psychological symptoms increases. It is also found out that submissive and helpless coping approach have mediator roles in this relationship. Also, contrary to expectations, having egalitarian gender role attitude effects the psychological symptoms in relation with the marital relationship, but this effect does not seem to play a mediator role. It is thought that the effects of marriage and couple therapy approaches considering couples’s problem solving and coping styles should be examined in further studies.

  11. Bisphenol-A exposures and behavioural aberrations: median and linear spline and meta-regression analyses of 12 toxicity studies in rodents.

    PubMed

    Peluso, Marco E M; Munnia, Armelle; Ceppi, Marcello

    2014-11-05

    Exposures to bisphenol-A, a weak estrogenic chemical, largely used for the production of plastic containers, can affect the rodent behaviour. Thus, we examined the relationships between bisphenol-A and the anxiety-like behaviour, spatial skills, and aggressiveness, in 12 toxicity studies of rodent offspring from females orally exposed to bisphenol-A, while pregnant and/or lactating, by median and linear splines analyses. Subsequently, the meta-regression analysis was applied to quantify the behavioural changes. U-shaped, inverted U-shaped and J-shaped dose-response curves were found to describe the relationships between bisphenol-A with the behavioural outcomes. The occurrence of anxiogenic-like effects and spatial skill changes displayed U-shaped and inverted U-shaped curves, respectively, providing examples of effects that are observed at low-doses. Conversely, a J-dose-response relationship was observed for aggressiveness. When the proportion of rodents expressing certain traits or the time that they employed to manifest an attitude was analysed, the meta-regression indicated that a borderline significant increment of anxiogenic-like effects was present at low-doses regardless of sexes (β)=-0.8%, 95% C.I. -1.7/0.1, P=0.076, at ≤120 μg bisphenol-A. Whereas, only bisphenol-A-males exhibited a significant inhibition of spatial skills (β)=0.7%, 95% C.I. 0.2/1.2, P=0.004, at ≤100 μg/day. A significant increment of aggressiveness was observed in both the sexes (β)=67.9,C.I. 3.4, 172.5, P=0.038, at >4.0 μg. Then, bisphenol-A treatments significantly abrogated spatial learning and ability in males (P<0.001 vs. females). Overall, our study showed that developmental exposures to low-doses of bisphenol-A, e.g. ≤120 μg/day, were associated to behavioural aberrations in offspring. Copyright © 2014. Published by Elsevier Ireland Ltd.

  12. The impact of adjustment latitude on self-assessed work ability in regard to gender and occupational type.

    PubMed

    Johansson, Gun; Hultin, Hanna; Möller, Jette; Hallqvist, Johan; Kjellberg, Katarina

    2012-07-01

    Adjustment latitude describes opportunities to change demands at work when ill and may affect work ability. The aim here is to study the association between adjustment latitude and self-assessed work ability among men and women and employees from different occupational sectors. This cross-sectional study used data from a questionnaire sent to 3020 employees in three occupational sectors in Sweden; 1430 responded. Subjects were divided into: full, moderately reduced, and greatly reduced work ability. Presence of nine adjustment opportunities was requested and subjects were divided into three groups. Each specific opportunity was also analyzed in relation to work ability. Multinomial logistic regression was used for analyses. Number of opportunities to adjust was associated with work ability among men and employees in health care. "Shortening the working day" was associated with work ability in most groups. For men and industrial employees, "postponing work", "going home and working later", and "working without disturbance" were associated with work ability. "To work from home" was associated with work ability among women and employees in insurance. The assumption that adjustment latitude affects work ability is supported. Associations differ with regard to gender and occupational sectors. Further studies with longitudinal design and alternative samples are needed.

  13. New ventures require accurate risk analyses and adjustments.

    PubMed

    Eastaugh, S R

    2000-01-01

    For new business ventures to succeed, healthcare executives need to conduct robust risk analyses and develop new approaches to balance risk and return. Risk analysis involves examination of objective risks and harder-to-quantify subjective risks. Mathematical principles applied to investment portfolios also can be applied to a portfolio of departments or strategic business units within an organization. The ideal business investment would have a high expected return and a low standard deviation. Nonetheless, both conservative and speculative strategies should be considered in determining an organization's optimal service line and helping the organization manage risk.

  14. Complex regression Doppler optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Elahi, Sahar; Gu, Shi; Thrane, Lars; Rollins, Andrew M.; Jenkins, Michael W.

    2018-04-01

    We introduce a new method to measure Doppler shifts more accurately and extend the dynamic range of Doppler optical coherence tomography (OCT). The two-point estimate of the conventional Doppler method is replaced with a regression that is applied to high-density B-scans in polar coordinates. We built a high-speed OCT system using a 1.68-MHz Fourier domain mode locked laser to acquire high-density B-scans (16,000 A-lines) at high enough frame rates (˜100 fps) to accurately capture the dynamics of the beating embryonic heart. Flow phantom experiments confirm that the complex regression lowers the minimum detectable velocity from 12.25 mm / s to 374 μm / s, whereas the maximum velocity of 400 mm / s is measured without phase wrapping. Complex regression Doppler OCT also demonstrates higher accuracy and precision compared with the conventional method, particularly when signal-to-noise ratio is low. The extended dynamic range allows monitoring of blood flow over several stages of development in embryos without adjusting the imaging parameters. In addition, applying complex averaging recovers hidden features in structural images.

  15. Application of Regression-Discontinuity Analysis in Pharmaceutical Health Services Research

    PubMed Central

    Zuckerman, Ilene H; Lee, Euni; Wutoh, Anthony K; Xue, Zhenyi; Stuart, Bruce

    2006-01-01

    Objective To demonstrate how a relatively underused design, regression-discontinuity (RD), can provide robust estimates of intervention effects when stronger designs are impossible to implement. Data Sources/Study Setting Administrative claims from a Mid-Atlantic state Medicaid program were used to evaluate the effectiveness of an educational drug utilization review intervention. Study Design Quasi-experimental design. Data Collection/Extraction Methods A drug utilization review study was conducted to evaluate a letter intervention to physicians treating Medicaid children with potentially excessive use of short-acting β2-agonist inhalers (SAB). The outcome measure is change in seasonally-adjusted SAB use 5 months pre- and postintervention. To determine if the intervention reduced monthly SAB utilization, results from an RD analysis are compared to findings from a pretest–posttest design using repeated-measure ANOVA. Principal Findings Both analyses indicated that the intervention significantly reduced SAB use among the high users. Average monthly SAB use declined by 0.9 canisters per month (p<.001) according to the repeated-measure ANOVA and by 0.2 canisters per month (p<.001) from RD analysis. Conclusions Regression-discontinuity design is a useful quasi-experimental methodology that has significant advantages in internal validity compared to other pre–post designs when assessing interventions in which subjects' assignment is based on cutoff scores for a critical variable. PMID:16584464

  16. Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing

    PubMed Central

    Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

    2018-01-01

    Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393

  17. Job adjustment and absence from work in mid-pregnancy in the Norwegian Mother and Child Cohort Study (MoBa).

    PubMed

    Kristensen, P; Nordhagen, R; Wergeland, E; Bjerkedal, T

    2008-08-01

    Pregnant women at work have special needs, and sick leave is common. However, job adjustment in pregnancy is addressed in European legislation. Our main objective was to examine if job adjustment was associated with reduced absence. This study is based on the Norwegian Mother and Child Cohort Study (MoBa) conducted by the Norwegian Institute of Public Health. 28,611 employed women filled in questionnaires in weeks 17 and 30 in pregnancy. The risk of absence for more than 2 weeks was studied among those who were not absent in week 17 (n = 22,932), and the probability of return to work in week 30 among those who were absent in week 17 (n = 5679). Data were based on self-report. The influence of job adjustment (three categories: not needed, needed but not obtained, needed and obtained) was analysed in additive models in multivariable binomial regression. Associations with other job characteristics and work environment factors were also analysed. The risk of absence for more than 2 weeks was 0.308 and the probability of return to work was 0.137. Compared with women who needed but did not achieve job adjustment, obtained job adjustment was associated with a 0.107 decreased risk of absence (95% confidence interval 0.090 to 0.125) in a model including other job characteristics and work environment factors. Job adjustment was correspondingly associated with a 0.041 (0.023 to 0.059) increased probability of return to work. Absence was associated with adverse work environment, whereas the opposite pattern was found for return to work among those who started off being absent. Job adjustment was associated with reduced absence from work in pregnancy. Results should be interpreted cautiously because of low participation in MoBa and potential information bias from self-reported data.

  18. Socio-emotional regulation in children with intellectual disability and typically developing children, and teachers' perceptions of their social adjustment.

    PubMed

    Baurain, Céline; Nader-Grosbois, Nathalie; Dionne, Carmen

    2013-09-01

    This study examined the extent to which socio-emotional regulation displayed in three dyadic interactive play contexts (neutral, competitive or cooperative) by 45 children with intellectual disability compared with 45 typically developing children (matched on developmental age, ranging from 3 to 6 years) is linked with the teachers' perceptions of their social adjustment. A Coding Grid of Socio-Emotional Regulation by Sequences (Baurain & Nader-Grosbois, 2011b, 2011c) focusing on Emotional Expression, Social Behavior and Behavior toward Social Rules in children was applied. The Social Adjustment for Children Scale (EASE, Hugues, Soares-Boucaud, Hochman, & Frith, 1997) and the Assessment, Evaluation and Intervention Program System (AEPS, Bricker, 2002) were completed by teachers. Regression analyses emphasized, in children with intellectual disability only, a positive significant link between their Behavior toward Social Rules in interactive contexts and the teachers' perceptions of their social adjustment. Children with intellectual disabilities who listen to and follow instructions, who are patient in waiting for their turn, and who moderate their externalized behavior are perceived by their teachers as socially adapted in their daily social relationships. The between-groups dissimilarity in the relational patterns between abilities in socio-emotional regulation and social adjustment supports the "structural difference hypothesis" with regard to the group with intellectual disability, compared with the typically developing group. Hierarchical cluster cases analyses identified distinct subgroups showing variable structural patterns between the three specific categories of abilities in socio-emotional regulation and their levels of social adjustment perceived by teachers. In both groups, several abilities in socio-emotional regulation and teachers' perceptions of social adjustment vary depending on children's developmental age. Chronological age in children with

  19. Hospital charges associated with motorcycle crash factors: a quantile regression analysis.

    PubMed

    Olsen, Cody S; Thomas, Andrea M; Cook, Lawrence J

    2014-08-01

    Previous studies of motorcycle crash (MC) related hospital charges use trauma registries and hospital records, and do not adjust for the number of motorcyclists not requiring medical attention. This may lead to conservative estimates of helmet use effectiveness. MC records were probabilistically linked with emergency department and hospital records to obtain total hospital charges. Missing data were imputed. Multivariable quantile regression estimated reductions in hospital charges associated with helmet use and other crash factors. Motorcycle helmets were associated with reduced median hospital charges of $256 (42% reduction) and reduced 98th percentile of $32,390 (33% reduction). After adjusting for other factors, helmets were associated with reductions in charges in all upper percentiles studied. Quantile regression models described homogenous and heterogeneous associations between other crash factors and charges. Quantile regression comprehensively describes associations between crash factors and hospital charges. Helmet use among motorcyclists is associated with decreased hospital charges. 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.

  20. Comparing Maternal Services Utilization and Expense Reimbursement before and after the Adjustment of the New Rural Cooperative Medical Scheme Policy in Rural China

    PubMed Central

    You, Hua; Gu, Hai; Ning, Weiqing; Zhou, Hua; Dong, Hengjin

    2016-01-01

    Background The New Rural Cooperative Medical Scheme (NCMS) includes a maternal care benefits package that is associated with increasing maternal health services. The local compensation policies have been frequently adjusted in recent years. This study examined the association between the NCMS maternal-services policy adjustment and expense reimbursement in Yuyao, China. Methods Two household surveys were conducted in Yuyao in 2008 and 2011 (before and after the NCMS policy adjustment, respectively). Local women (N = 154) who had delivery history in the past three years were recruited. A questionnaire was used to collect information about delivery history, maternal health services utilization (prenatal care, postnatal care, and the grade of delivery institutions), NCMS participation, and reimbursement status. Logistic regression analyses were used to predict the association between policy adjustment and maternal health utilization and the association between policy adjustment and out-of-pocket proportion. Next, t-tests and covariance analyses adjusting for household income were used to compare the out-of-pocket proportion between 2008 and 2011. Results Results revealed that compensation policy adjustment was associated with an increase in postnatal visits (adjusted OR = 3.32, p = 0.009) and the use of second level or above institutions for delivery (adjusted OR = 2.32, p = 0.03) among participants. In 2008, only 9.1% of pregnant women received reimbursement from the NCMS; however, this rate increased to 36.8% in 2011. After policy adjustment, there were no significant changes in the proportion of out-of-pocket expenses shared in delivery fee (F = 0.24, p = 0.63) and in household income (F = 0.46, p = 0.50). Conclusions Financial compensation increase improved maternal health services utilization; however, this effect was limited. Although the reimbursement rate was raised, the out-of-pocket proportion was not significant changed; therefore, the compensation design

  1. Investigating the utility of a GPA institutional adjustment index.

    PubMed

    Didier, Thomas; Kreiter, Clarence D; Buri, Russell; Solow, Catherine

    2006-05-01

    Grading standards vary widely across undergraduate institutions. If, during the medical school admissions process, GPA is considered without reference to the institution attended, it will disadvantage applicants from undergraduate institutions employing rigorous grading standards. A regression-based GPA institutional equating method using historical MCAT and GPA information is described. Classes selected from eight applicant pools demonstrate the impact of the GPA adjustment. The validity of the adjustment is examined by comparing adjusted and unadjusted GPAs' correlation with USMLE and medical college grades. The adjusted GPA demonstrated significantly improved congruence with MCAT estimates of applicant preparedness. The adjustment changed selection decisions for 21% of those admitted. The adjusted GPA enhanced prediction of USMLE and medical school grades only for students from institutions which required large adjustments. Unlike other indices, the adjustment described uses the same metric as GPA and is based only on an institution's history of preparing medical school applicants. The institutional adjustment is consequential in selection, significantly enhances congruence with a standardized measure of academic preparedness and may enhance the validity of the GPA.

  2. Marital status integration and suicide: A meta-analysis and meta-regression.

    PubMed

    Kyung-Sook, Woo; SangSoo, Shin; Sangjin, Shin; Young-Jeon, Shin

    2018-01-01

    Marital status is an index of the phenomenon of social integration within social structures and has long been identified as an important predictor suicide. However, previous meta-analyses have focused only on a particular marital status, or not sufficiently explored moderators. A meta-analysis of observational studies was conducted to explore the relationships between marital status and suicide and to understand the important moderating factors in this association. Electronic databases were searched to identify studies conducted between January 1, 2000 and June 30, 2016. We performed a meta-analysis, subgroup analysis, and meta-regression of 170 suicide risk estimates from 36 publications. Using random effects model with adjustment for covariates, the study found that the suicide risk for non-married versus married was OR = 1.92 (95% CI: 1.75-2.12). The suicide risk was higher for non-married individuals aged <65 years than for those aged ≥65 years, and higher for men than for women. According to the results of stratified analysis by gender, non-married men exhibited a greater risk of suicide than their married counterparts in all sub-analyses, but women aged 65 years or older showed no significant association between marital status and suicide. The suicide risk in divorced individuals was higher than for non-married individuals in both men and women. The meta-regression showed that gender, age, and sample size affected between-study variation. The results of the study indicated that non-married individuals have an aggregate higher suicide risk than married ones. In addition, gender and age were confirmed as important moderating factors in the relationship between marital status and suicide. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance.

    PubMed

    Nguyen, Tri-Long; Collins, Gary S; Spence, Jessica; Daurès, Jean-Pierre; Devereaux, P J; Landais, Paul; Le Manach, Yannick

    2017-04-28

    Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression. We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds. We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions. If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering.

  4. Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

    PubMed Central

    Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.

    2008-01-01

    Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results. PMID:19054742

  5. Relationship adjustment, depression, and anxiety during pregnancy and the postpartum period.

    PubMed

    Whisman, Mark A; Davila, Joanne; Goodman, Sherryl H

    2011-06-01

    The associations between relationship adjustment and symptoms of depression and anxiety were evaluated in a sample of pregnant married or cohabiting women (N = 113) who were at risk for perinatal depression because of a prior history of major depression. Women completed self-report measures of relationship adjustment, depressive symptoms, and anxiety symptoms monthly during pregnancy and for the first six months following the birth of their child. Multilevel modeling was used to examine concurrent and time-lagged within-subjects effects for relationship adjustment and depressive and anxiety symptoms. Results revealed that (a) relationship adjustment was associated with both depressive symptoms and anxiety symptoms in concurrent analyses; (b) relationship adjustment was predictive of subsequent anxiety symptoms but not subsequent depressive symptoms in lagged analyses; and (c) depressive symptoms were predictive of subsequent relationship adjustment in lagged analyses with symptoms of depression and anxiety examined simultaneously. These results support the continued investigation into the cross-sectional and longitudinal associations between relationship functioning and depressive and anxiety symptoms in women during pregnancy and the postpartum period. 2011 APA, all rights reserved

  6. Adjusting the Adjusted X[superscript 2]/df Ratio Statistic for Dichotomous Item Response Theory Analyses: Does the Model Fit?

    ERIC Educational Resources Information Center

    Tay, Louis; Drasgow, Fritz

    2012-01-01

    Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…

  7. Negative life events and school adjustment among Chinese nursing students: The mediating role of psychological capital.

    PubMed

    Liu, Chunqin; Zhao, Yuanyuan; Tian, Xiaohong; Zou, Guiyuan; Li, Ping

    2015-06-01

    Adjustment difficulties of college students are common and their school adjustment has gained wide concern in recent years. Negative life events and psychological capital (PsyCap) have been associated with school adjustment. However, the potential impact of negative life events on PsyCap, and whether PsyCap mediates the relationship between negative life events and school adjustment among nursing students have not been studied. To investigate the relationship among negative life events, PsyCap, and school adjustment among five-year vocational high school nursing students in China and the mediating role of PsyCap between negative life events and school adjustment. A cross-sectional survey design was conducted. 643 five-year vocational high school nursing students were recruited from three public high vocational colleges in Shandong of China. Adolescent Self-Rating Life Event Checklist (ASLEC), the Psychological Capital Questionnaire for Adolescent Students scale (PCQAS), and the Chinese College Student Adjustment Scale (CCSAS) were used in this study. Hierarchical linear regression analyses were performed to explore the mediating role of PsyCap. Negative life events were negatively associated with the dimensions of school adjustment (interpersonal relationship adaptation, learning adaptation, campus life adaptation, career adaptation, emotional adaptation, self-adaptation, and degree of satisfaction). PsyCap was positively associated with the dimensions of school adjustment and negatively associated with negative life events. PsyCap partially mediated the relationship between negative life events and school adjustment. Negative life events may increase the risk of school maladjustment in individuals with low PsyCap. Interventions designed to increase nursing students' PsyCap might buffer the stress of adverse life events, and thereby, enhance students' positive adjustment to school. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Background stratified Poisson regression analysis of cohort data.

    PubMed

    Richardson, David B; Langholz, Bryan

    2012-03-01

    Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

  9. Attachment style and adjustment to divorce.

    PubMed

    Yárnoz-Yaben, Sagrario

    2010-05-01

    Divorce is becoming increasingly widespread in Europe. In this study, I present an analysis of the role played by attachment style (secure, dismissing, preoccupied and fearful, plus the dimensions of anxiety and avoidance) in the adaptation to divorce. Participants comprised divorced parents (N = 40) from a medium-sized city in the Basque Country. The results reveal a lower proportion of people with secure attachment in the sample group of divorcees. Attachment style and dependence (emotional and instrumental) are closely related. I have also found associations between measures that showed a poor adjustment to divorce and the preoccupied and fearful attachment styles. Adjustment is related to a dismissing attachment style and to the avoidance dimension. Multiple regression analysis confirmed that secure attachment and the avoidance dimension predict adjustment to divorce and positive affectivity while preoccupied attachment and the anxiety dimension predicted negative affectivity. Implications for research and interventions with divorcees are discussed.

  10. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    ERIC Educational Resources Information Center

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  11. Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

    PubMed

    Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

    2018-02-01

    A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © 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.

  12. 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.

  13. Determinants of The Grade A Embryos in Infertile Women; Zero-Inflated Regression Model.

    PubMed

    Almasi-Hashiani, Amir; Ghaheri, Azadeh; Omani Samani, Reza

    2017-10-01

    In assisted reproductive technology, it is important to choose high quality embryos for embryo transfer. The aim of the present study was to determine the grade A embryo count and factors related to it in infertile women. This historical cohort study included 996 infertile women. The main outcome was the number of grade A embryos. Zero-Inflated Poisson (ZIP) regression and Zero-Inflated Negative Binomial (ZINB) regression were used to model the count data as it contained excessive zeros. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. After adjusting for potential confounders, results from the ZINB model show that for each unit increase in the number 2 pronuclear (2PN) zygotes, we get an increase of 1.45 times as incidence rate ratio (95% confidence interval (CI): 1.23-1.69, P=0.001) in the expected grade A embryo count number, and for each increase in the cleavage day we get a decrease 0.35 times (95% CI: 0.20-0.61, P=0.001) in expected grade A embryo count. There is a significant association between both the number of 2PN zygotes and cleavage day with the number of grade A embryos in both ZINB and ZIP regression models. The estimated coefficients are more plausible than values found in earlier studies using less relevant models. Copyright© by Royan Institute. All rights reserved.

  14. Regression Effects in Angoff Ratings: Examples from Credentialing Exams

    ERIC Educational Resources Information Center

    Wyse, Adam E.

    2018-01-01

    This article discusses regression effects that are commonly observed in Angoff ratings where panelists tend to think that hard items are easier than they are and easy items are more difficult than they are in comparison to estimated item difficulties. Analyses of data from two credentialing exams illustrate these regression effects and the…

  15. Self-discrepancies in work-related upper extremity pain: relation to emotions and flexible-goal adjustment.

    PubMed

    Goossens, Mariëlle E; Kindermans, Hanne P; Morley, Stephen J; Roelofs, Jeffrey; Verbunt, Jeanine; Vlaeyen, Johan W

    2010-08-01

    Recurrent pain not only has an impact on disability, but on the long term it may become a threat to one's sense of self. This paper presents a cross-sectional study of patients with work-related upper extremity pain and focuses on: (1) the role of self-discrepancies in this group, (2) the associations between self-discrepancies, pain, emotions and (3) the interaction between self-discrepancies and flexible-goal adjustment. Eighty-nine participants completed standardized self-report measures of pain intensity, pain duration, anxiety, depression and flexible-goal adjustment. A Selves Questionnaire was used to generate self-discrepancies. A series of hierarchical regression analyses showed relationships between actual-ought other, actual-ought self, actual-feared self-discrepancies and depression as well as a significant association between actual-ought other self-discrepancy and anxiety. Furthermore, significant interactions were found between actual-ought other self-discrepancies and flexibility, indicating that less flexible participants with large self-discrepancies score higher on depression. This study showed that self-discrepancies are related to negative emotions and that flexible-goal adjustment served as a moderator in this relationship. The view of self in pain and flexible-goal adjustment should be considered as important variables in the process of chronic pain. Copyright (c) 2009 European Federation of International Association for the Study of Pain Chapters. Published by Elsevier Ltd. All rights reserved.

  16. Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis

    ERIC Educational Resources Information Center

    Kim, Rae Seon

    2011-01-01

    When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…

  17. Bias due to two-stage residual-outcome regression analysis in genetic association studies.

    PubMed

    Demissie, Serkalem; Cupples, L Adrienne

    2011-11-01

    Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

  18. Influence of Parenting Styles on the Adjustment and Academic Achievement of Traditional College Freshmen.

    ERIC Educational Resources Information Center

    Hickman, Gregory P.; Bartholomae, Suzanne; McKenry, Patrick C.

    2000-01-01

    Examines the relationship between parenting styles and academic achievement and adjustment of traditional college freshmen (N=101). Multiple regression models indicate that authoritative parenting style was positively related to student's academic adjustment. Self-esteem was significantly predictive of social, personal-emotional, goal…

  19. Differentiating regressed melanoma from regressed lichenoid keratosis.

    PubMed

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. Soil-adjusted sorption isotherms for arsenic(V) and vanadium(V)

    NASA Astrophysics Data System (ADS)

    Rückamp, Daniel; Utermann, Jens; Florian Stange, Claus

    2017-04-01

    The sorption characteristic of a soil is usually determined by fitting a sorption isotherm model to laboratory data. However, such sorption isotherms are only valid for the studied soil and cannot be transferred to other soils. For this reason, a soil-adjusted sorption isotherm can be calculated by using the data of several soils. Such soil-adjusted sorption isotherms exist for cationic heavy metals, but are lacking for heavy metal oxyanions. Hence, the aim of this study is to establish soil-adjusted sorption isotherms for the oxyanions arsenate (arsenic(V)) and vanadate (vanadium(V)). For the laboratory experiment, 119 soils (samples from top- and subsoils) typical for Germany were chosen. The batch experiments were conducted with six concentrations of arsenic(V) and vanadium(V), respectively. By using the laboratory data, sorption isotherms for each soil were derived. Then, the soil-adjusted sorption isotherms were calculated by non-linear regression of the sorption isotherms with additional soil parameters. The results indicated a correlation between the sorption strength and oxalate-extractable iron, organic carbon, clay, and electrical conductivity for both, arsenic and vanadium. However, organic carbon had a negative regression coefficient. As total organic carbon was correlated with dissolved organic carbon; we attribute this observation to an effect of higher amounts of dissolved organic substances. We conclude that these soil-adjusted sorption isotherms can be used to assess the potential of soils to adsorb arsenic(V) and vanadium(V) without performing time-consuming sorption experiments.

  1. Effects of Relational Authenticity on Adjustment to College

    ERIC Educational Resources Information Center

    Lenz, A. Stephen; Holman, Rachel L.; Lancaster, Chloe; Gotay, Stephanie G.

    2016-01-01

    The authors examined the association between relational health and student adjustment to college. Data were collected from 138 undergraduate students completing their 1st semester at a large university in the mid-southern United States. Regression analysis indicated that higher levels of relational authenticity were a predictor of success during…

  2. Do afterlife beliefs affect psychological adjustment to late-life spousal loss?

    PubMed

    Carr, Deborah; Sharp, Shane

    2014-01-01

    We explore whether beliefs about the existence and nature of an afterlife affect 5 psychological symptoms (anxiety, anger, depression, intrusive thoughts, and yearning) among recently bereaved older spouses. We conduct multivariate regression analyses using data from the Changing Lives of Older Couples (CLOC), a prospective study of spousal loss. The CLOC obtained data from bereaved persons prior to loss and both 6 and 18 months postloss. All analyses are adjusted for health, sociodemographic characteristics, and preloss marital quality. Bleak or uncertain views about the afterlife are associated with multiple aspects of distress postloss. Uncertainty about the existence of an afterlife is associated with elevated intrusive thoughts, a symptom similar to posttraumatic distress. Widowed persons who do not expect to be reunited with loved ones in the afterlife report significantly more depressive symptoms, anger, and intrusive thoughts at both 6 and 18 months postloss. Beliefs in an afterlife may be maladaptive for coping with late-life spousal loss, particularly if one is uncertain about its existence or holds a pessimistic view of what the afterlife entails. Our findings are broadly consistent with recent work suggesting that "continuing bonds" with the decedent may not be adaptive for older bereaved spouses.

  3. The relation between stressful life events and adjustment in elementary school children: the role of social support and social problem-solving skills.

    PubMed

    Dubow, E F; Tisak, J

    1989-12-01

    This study investigated the relation between stressful life events and adjustment in elementary school children, with particular emphasis on the potential main and stress-buffering effects of social support and social problem-solving skills. Third through fifth graders (N = 361) completed social support and social problem-solving measures. Their parents provided ratings of stress in the child's environment and ratings of the child's behavioral adjustment. Teachers provided ratings of the children's behavioral and academic adjustment. Hierarchical multiple regressions revealed significant stress-buffering effects for social support and problem-solving skills on teacher-rated behavior problems, that is, higher levels of social support and problem-solving skills moderated the relation between stressful life events and behavior problems. A similar stress-buffering effect was found for problem-solving skills on grade-point average and parent-rated behavior problems. In terms of children's competent behaviors, analyses supported a main effect model of social support and problem-solving. Possible processes accounting for the main and stress-buffering effects are discussed.

  4. Regression and multivariate models for predicting particulate matter concentration level.

    PubMed

    Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

    2018-01-01

    The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

  5. Association between intake of dairy products and short-term memory with and without adjustment for genetic and family environmental factors: A twin study.

    PubMed

    Ogata, Soshiro; Tanaka, Haruka; Omura, Kayoko; Honda, Chika; Hayakawa, Kazuo

    2016-04-01

    Previous studies have indicated associations between intake of dairy products and better cognitive function and reduced risk of dementia. However, these studies did not adjust for genetic and family environmental factors that may influence food intake, cognitive function, and metabolism of dairy product nutrients. In the present study, we investigated the association between intake of dairy products and short-term memory with and without adjustment for almost all genetic and family environmental factors using a genetically informative sample of twin pairs. A cross-sectional study was conducted among twin pairs aged between 20 and 74. Short-term memory was assessed as primary outcome variable, intake of dairy products was analyzed as the predictive variable, and sex, age, education level, marital status, current smoking status, body mass index, dietary alcohol intake, and medical history of hypertension or diabetes were included as possible covariates. Generalized estimating equations (GEE) were performed by treating twins as individuals and regression analyses were used to identify within-pair differences of a twin pair to adjust for genetic and family environmental factors. Data are reported as standardized coefficients and 95% confidence intervals (CI). Analyses were performed on data from 78 men and 278 women. Among men, high intake of dairy products was significantly associated with better short-term memory after adjustment for the possible covariates (standardized coefficients = 0.22; 95% CI, 0.06-0.38) and almost all genetic and family environmental factors (standardized coefficients = 0.38; 95% CI, 0.07-0.69). Among women, no significant associations were found between intake of dairy products and short-term memory. Subsequent sensitivity analyses were adjusted for small samples and showed similar results. Intake of dairy product may prevent cognitive declines regardless of genetic and family environmental factors in men. Copyright © 2015 Elsevier Ltd

  6. Variable selection and model choice in geoadditive regression models.

    PubMed

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  7. PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

    EPA Science Inventory

    The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

  8. Model building strategy for logistic regression: purposeful selection.

    PubMed

    Zhang, Zhongheng

    2016-03-01

    Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

  9. Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models.

    PubMed

    Seeker, Luise A; Ilska, Joanna J; Psifidi, Androniki; Wilbourn, Rachael V; Underwood, Sarah L; Fairlie, Jennifer; Holland, Rebecca; Froy, Hannah; Bagnall, Ainsley; Whitelaw, Bruce; Coffey, Mike; Nussey, Daniel H; Banos, Georgios

    2018-01-01

    Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL) to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1) characterize the change in bovine relative leukocyte TL (RLTL) across the lifetime in Holstein Friesian dairy cattle, 2) estimate genetic parameters of RLTL over time and 3) investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05-0.08) and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954).

  10. Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models

    PubMed Central

    Ilska, Joanna J.; Psifidi, Androniki; Wilbourn, Rachael V.; Underwood, Sarah L.; Fairlie, Jennifer; Holland, Rebecca; Froy, Hannah; Bagnall, Ainsley; Whitelaw, Bruce; Coffey, Mike; Nussey, Daniel H.; Banos, Georgios

    2018-01-01

    Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL) to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1) characterize the change in bovine relative leukocyte TL (RLTL) across the lifetime in Holstein Friesian dairy cattle, 2) estimate genetic parameters of RLTL over time and 3) investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05–0.08) and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954). PMID:29438415

  11. Threshold regression to accommodate a censored covariate.

    PubMed

    Qian, Jing; Chiou, Sy Han; Maye, Jacqueline E; Atem, Folefac; Johnson, Keith A; Betensky, Rebecca A

    2018-06-22

    In several common study designs, regression modeling is complicated by the presence of censored covariates. Examples of such covariates include maternal age of onset of dementia that may be right censored in an Alzheimer's amyloid imaging study of healthy subjects, metabolite measurements that are subject to limit of detection censoring in a case-control study of cardiovascular disease, and progressive biomarkers whose baseline values are of interest, but are measured post-baseline in longitudinal neuropsychological studies of Alzheimer's disease. We propose threshold regression approaches for linear regression models with a covariate that is subject to random censoring. Threshold regression methods allow for immediate testing of the significance of the effect of a censored covariate. In addition, they provide for unbiased estimation of the regression coefficient of the censored covariate. We derive the asymptotic properties of the resulting estimators under mild regularity conditions. Simulations demonstrate that the proposed estimators have good finite-sample performance, and often offer improved efficiency over existing methods. We also derive a principled method for selection of the threshold. We illustrate the approach in application to an Alzheimer's disease study that investigated brain amyloid levels in older individuals, as measured through positron emission tomography scans, as a function of maternal age of dementia onset, with adjustment for other covariates. We have developed an R package, censCov, for implementation of our method, available at CRAN. © 2018, The International Biometric Society.

  12. An empirical study using permutation-based resampling in meta-regression

    PubMed Central

    2012-01-01

    Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

  13. Least-Squares Data Adjustment with Rank-Deficient Data Covariance Matrices

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

    Williams, J.G.

    2011-07-01

    A derivation of the linear least-squares adjustment formulae is required that avoids the assumption that the covariance matrix of prior parameters can be inverted. Possible proofs are of several kinds, including: (i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. In this paper, the least-squares adjustment equations are derived in both these ways, while explicitly assuming that the covariance matrix of prior parameters is singular. It will be proved that the solutions are unique and that, contrary to statements that have appeared inmore » the literature, the least-squares adjustment problem is not ill-posed. No modification is required to the adjustment formulae that have been used in the past in the case of a singular covariance matrix for the priors. In conclusion: The linear least-squares adjustment formula that has been used in the past is valid in the case of a singular covariance matrix for the covariance matrix of prior parameters. Furthermore, it provides a unique solution. Statements in the literature, to the effect that the problem is ill-posed are wrong. No regularization of the problem is required. This has been proved in the present paper by two methods, while explicitly assuming that the covariance matrix of prior parameters is singular: i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. No modification is needed to the adjustment formulae that have been used in the past. (author)« less

  14. Grandparenting and adolescent adjustment in two-parent biological, lone-parent, and step-families.

    PubMed

    Attar-Schwartz, Shalhevet; Tan, Jo-Pei; Buchanan, Ann; Flouri, Eirini; Griggs, Julia

    2009-02-01

    There is limited research on the links between grandparenting and adolescents' well-being, especially from the perspective of the adolescents. The study examined whether grandparent involvement varied in two-parent biological, lone-parent, and step-families and whether this had a different contribution to the emotional and behavioral adjustment of adolescents across different family structures. The study is based on a sample of 1,515 secondary school students (ages 11-16 years) from England and Wales who completed a structured questionnaire. Findings of hierarchical regression analyses showed that among the whole sample, greater grandparent involvement was associated with fewer emotional problems (p < .01) and with more prosocial behavior (p < .001). In addition, while there were no differences in the level of grandparent involvement across the different family structures, grandparent involvement was more strongly associated with reduced adjustment difficulties among adolescents from lone-parent and step-families than those from two-parent biological families. A possible implication is that the positive role of grandparent involvement in lone-parent and step- families should be more emphasized in family psychology. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

  15. Measuring cancer-specific child adjustment difficulties: Development and validation of the Children's Oncology Child Adjustment Scale (ChOCs).

    PubMed

    Burke, Kylie; McCarthy, Maria; Lowe, Cherie; Sanders, Matthew R; Lloyd, Erin; Bowden, Madeleine; Williams, Lauren

    2017-03-01

    Childhood cancer is associated with child adjustment difficulties including, eating and sleep disturbance, and emotional and other behavioral difficulties. However, there is a lack of validated instruments to measure the specific child adjustment issues associated with pediatric cancer treatments. The aim of this study was to develop and evaluate the reliability and validity of a parent-reported, child adjustment scale. One hundred thirty-two parents from two pediatric oncology centers who had children (aged 2-10 years) diagnosed with cancer completed the newly developed measure and additional measures of child behavior, sleep, diet, and quality of life. Children were more than 4 weeks postdiagnosis and less than 12 months postactive treatment. Factor structure, internal consistency, and construct (convergent) validity analyses were conducted. Principal component analysis revealed five distinct and theoretically coherent factors: Sleep Difficulties, Impact of Child's Illness, Eating Difficulties, Hospital-Related Behavior Difficulties, and General Behavior Difficulties. The final 25-item measure, the Children's Oncology Child Adjustment Scale (ChOCs), demonstrated good internal consistency (α = 0.79-0.91). Validity of the ChOCs was demonstrated by significant correlations between the subscales and measures of corresponding constructs. The ChOCs provides a new measure of child adjustment difficulties designed specifically for pediatric oncology. Preliminary analyses indicate strong theoretical and psychometric properties. Future studies are required to further examine reliability and validity of the scale, including test-retest reliability, discriminant validity, as well as change sensitivity and generalizability across different oncology samples and ages of children. The ChOCs shows promise as a measure of child adjustment relevant for oncology clinical settings and research purposes. © 2016 Wiley Periodicals, Inc.

  16. Meta-analyses of the 5-HTTLPR polymorphisms and post-traumatic stress disorder.

    PubMed

    Navarro-Mateu, Fernando; Escámez, Teresa; Koenen, Karestan C; Alonso, Jordi; Sánchez-Meca, Julio

    2013-01-01

    To conduct a meta-analysis of all published genetic association studies of 5-HTTLPR polymorphisms performed in PTSD cases. Potential studies were identified through PubMed/MEDLINE, EMBASE, Web of Science databases (Web of Knowledge, WoK), PsychINFO, PsychArticles and HuGeNet (Human Genome Epidemiology Network) up until December 2011. Published observational studies reporting genotype or allele frequencies of this genetic factor in PTSD cases and in non-PTSD controls were all considered eligible for inclusion in this systematic review. Two reviewers selected studies for possible inclusion and extracted data independently following a standardized protocol. A biallelic and a triallelic meta-analysis, including the total S and S' frequencies, the dominant (S+/LL and S'+/L'L') and the recessive model (SS/L+ and S'S'/L'+), was performed with a random-effect model to calculate the pooled OR and its corresponding 95% CI. Forest plots and Cochran's Q-Statistic and I(2) index were calculated to check for heterogeneity. Subgroup analyses and meta-regression were carried out to analyze potential moderators. Publication bias and quality of reporting were also analyzed. 13 studies met our inclusion criteria, providing a total sample of 1874 patients with PTSD and 7785 controls in the biallelic meta-analyses and 627 and 3524, respectively, in the triallelic. None of the meta-analyses showed evidence of an association between 5-HTTLPR and PTSD but several characteristics (exposure to the same principal stressor for PTSD cases and controls, adjustment for potential confounding variables, blind assessment, study design, type of PTSD, ethnic distribution and Total Quality Score) influenced the results in subgroup analyses and meta-regression. There was no evidence of potential publication bias. Current evidence does not support a direct effect of 5-HTTLPR polymorphisms on PTSD. Further analyses of gene-environment interactions, epigenetic modulation and new studies with large samples

  17. The importance of extent of choroid plexus cauterization in addition to endoscopic third ventriculostomy for infantile hydrocephalus: a retrospective North American observational study using propensity score-adjusted analysis.

    PubMed

    Fallah, Aria; Weil, Alexander G; Juraschka, Kyle; Ibrahim, George M; Wang, Anthony C; Crevier, Louis; Tseng, Chi-Hong; Kulkarni, Abhaya V; Ragheb, John; Bhatia, Sanjiv

    2017-12-01

    OBJECTIVE Combined endoscopic third ventriculostomy (ETC) and choroid plexus cauterization (CPC)-ETV/CPC- is being investigated to increase the rate of shunt independence in infants with hydrocephalus. The degree of CPC necessary to achieve improved rates of shunt independence is currently unknown. METHODS Using data from a single-center, retrospective, observational cohort study involving patients who underwent ETV/CPC for treatment of infantile hydrocephalus, comparative statistical analyses were performed to detect a difference in need for subsequent CSF diversion procedure in patients undergoing partial CPC (describes unilateral CPC or bilateral CPC that only extended from the foramen of Monro [FM] to the atrium on one side) or subtotal CPC (describes CPC extending from the FM to the posterior temporal horn bilaterally) using a rigid neuroendoscope. Propensity scores for extent of CPC were calculated using age and etiology. Propensity scores were used to perform 1) case-matching comparisons and 2) Cox multivariable regression, adjusting for propensity score in the unmatched cohort. Cox multivariable regression adjusting for age and etiology, but not propensity score was also performed as a third statistical technique. RESULTS Eighty-four patients who underwent ETV/CPC had sufficient data to be included in the analysis. Subtotal CPC was performed in 58 patients (69%) and partial CPC in 26 (31%). The ETV/CPC success rates at 6 and 12 months, respectively, were 49% and 41% for patients undergoing subtotal CPC and 35% and 31% for those undergoing partial CPC. Cox multivariate regression in a 48-patient cohort case-matched by propensity score demonstrated no added effect of increased extent of CPC on ETV/CPC survival (HR 0.868, 95% CI 0.422-1.789, p = 0.702). Cox multivariate regression including all patients, with adjustment for propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.845, 95% CI 0.462-1.548, p = 0.586). Cox multivariate

  18. Genetic analyses of protein yield in dairy cows applying random regression models with time-dependent and temperature x humidity-dependent covariates.

    PubMed

    Brügemann, K; Gernand, E; von Borstel, U U; König, S

    2011-08-01

    Data used in the present study included 1,095,980 first-lactation test-day records for protein yield of 154,880 Holstein cows housed on 196 large-scale dairy farms in Germany. Data were recorded between 2002 and 2009 and merged with meteorological data from public weather stations. The maximum distance between each farm and its corresponding weather station was 50 km. Hourly temperature-humidity indexes (THI) were calculated using the mean of hourly measurements of dry bulb temperature and relative humidity. On the phenotypic scale, an increase in THI was generally associated with a decrease in daily protein yield. For genetic analyses, a random regression model was applied using time-dependent (d in milk, DIM) and THI-dependent covariates. Additive genetic and permanent environmental effects were fitted with this random regression model and Legendre polynomials of order 3 for DIM and THI. In addition, the fixed curve was modeled with Legendre polynomials of order 3. Heterogeneous residuals were fitted by dividing DIM into 5 classes, and by dividing THI into 4 classes, resulting in 20 different classes. Additive genetic variances for daily protein yield decreased with increasing degrees of heat stress and were lowest at the beginning of lactation and at extreme THI. Due to higher additive genetic variances, slightly higher permanent environment variances, and similar residual variances, heritabilities were highest for low THI in combination with DIM at the end of lactation. Genetic correlations among individual values for THI were generally >0.90. These trends from the complex random regression model were verified by applying relatively simple bivariate animal models for protein yield measured in 2 THI environments; that is, defining a THI value of 60 as a threshold. These high correlations indicate the absence of any substantial genotype × environment interaction for protein yield. However, heritabilities and additive genetic variances from the random regression

  19. Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

    PubMed Central

    Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

    2017-01-01

    Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

  20. Regression dilution in the proportional hazards model.

    PubMed

    Hughes, M D

    1993-12-01

    The problem of regression dilution arising from covariate measurement error is investigated for survival data using the proportional hazards model. The naive approach to parameter estimation is considered whereby observed covariate values are used, inappropriately, in the usual analysis instead of the underlying covariate values. A relationship between the estimated parameter in large samples and the true parameter is obtained showing that the bias does not depend on the form of the baseline hazard function when the errors are normally distributed. With high censorship, adjustment of the naive estimate by the factor 1 + lambda, where lambda is the ratio of within-person variability about an underlying mean level to the variability of these levels in the population sampled, removes the bias. As censorship increases, the adjustment required increases and when there is no censorship is markedly higher than 1 + lambda and depends also on the true risk relationship.

  1. Do insurers respond to risk adjustment? A long-term, nationwide analysis from Switzerland.

    PubMed

    von Wyl, Viktor; Beck, Konstantin

    2016-03-01

    Community rating in social health insurance calls for risk adjustment in order to eliminate incentives for risk selection. Swiss risk adjustment is known to be insufficient, and substantial risk selection incentives remain. This study develops five indicators to monitor residual risk selection. Three indicators target activities of conglomerates of insurers (with the same ownership), which steer enrollees into specific carriers based on applicants' risk profiles. As a proxy for their market power, those indicators estimate the amount of premium-, health care cost-, and risk-adjustment transfer variability that is attributable to conglomerates. Two additional indicators, derived from linear regression, describe the amount of residual cost differences between insurers that are not covered by risk adjustment. All indicators measuring conglomerate-based risk selection activities showed increases between 1996 and 2009, paralleling the establishment of new conglomerates. At their maxima in 2009, the indicator values imply that 56% of the net risk adjustment volume, 34% of premium variability, and 51% cost variability in the market were attributable to conglomerates. From 2010 onwards, all indicators decreased, coinciding with a pre-announced risk adjustment reform implemented in 2012. Likewise, the regression-based indicators suggest that the volume and variance of residual cost differences between insurers that are not equaled out by risk adjustment have decreased markedly since 2009 as a result of the latest reform. Our analysis demonstrates that risk-selection, especially by conglomerates, is a real phenomenon in Switzerland. However, insurers seem to have reduced risk selection activities to optimize their losses and gains from the latest risk adjustment reform.

  2. Genetic analyses of stillbirth in relation to litter size using random regression models.

    PubMed

    Chen, C Y; Misztal, I; Tsuruta, S; Herring, W O; Holl, J; Culbertson, M

    2010-12-01

    Estimates of genetic parameters for number of stillborns (NSB) in relation to litter size (LS) were obtained with random regression models (RRM). Data were collected from 4 purebred Duroc nucleus farms between 2004 and 2008. Two data sets with 6,575 litters for the first parity (P1) and 6,259 litters for the second to fifth parity (P2-5) with a total of 8,217 and 5,066 animals in the pedigree were analyzed separately. Number of stillborns was studied as a trait on sow level. Fixed effects were contemporary groups (farm-year-season) and fixed cubic regression coefficients on LS with Legendre polynomials. Models for P2-5 included the fixed effect of parity. Random effects were additive genetic effects for both data sets with permanent environmental effects included for P2-5. Random effects modeled with Legendre polynomials (RRM-L), linear splines (RRM-S), and degree 0 B-splines (RRM-BS) with regressions on LS were used. For P1, the order of polynomial, the number of knots, and the number of intervals used for respective models were quadratic, 3, and 3, respectively. For P2-5, the same parameters were linear, 2, and 2, respectively. Heterogeneous residual variances were considered in the models. For P1, estimates of heritability were 12 to 15%, 5 to 6%, and 6 to 7% in LS 5, 9, and 13, respectively. For P2-5, estimates were 15 to 17%, 4 to 5%, and 4 to 6% in LS 6, 9, and 12, respectively. For P1, average estimates of genetic correlations between LS 5 to 9, 5 to 13, and 9 to 13 were 0.53, -0.29, and 0.65, respectively. For P2-5, same estimates averaged for RRM-L and RRM-S were 0.75, -0.21, and 0.50, respectively. For RRM-BS with 2 intervals, the correlation was 0.66 between LS 5 to 7 and 8 to 13. Parameters obtained by 3 RRM revealed the nonlinear relationship between additive genetic effect of NSB and the environmental deviation of LS. The negative correlations between the 2 extreme LS might possibly indicate different genetic bases on incidence of stillbirth.

  3. Neonatal Sleep-Wake Analyses Predict 18-month Neurodevelopmental Outcomes.

    PubMed

    Shellhaas, Renée A; Burns, Joseph W; Hassan, Fauziya; Carlson, Martha D; Barks, John D E; Chervin, Ronald D

    2017-11-01

    The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p < .05). These prospective, longitudinal data suggest that inefficient neonatal sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction. © Sleep Research Society 2017. Published by Oxford

  4. 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.

  5. 10 CFR 436.22 - Adjusted internal rate of return.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Methodology and Procedures for Life Cycle Cost Analyses § 436.22 Adjusted internal rate of return. The adjusted internal rate of return is the overall rate of return on an energy or water conservation measure... yearly net savings in energy or water and non-fuel or non-water operation and maintenance costs...

  6. Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

    PubMed

    Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

    2015-05-01

    The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. Regression modeling plan for 29 biochemical indicators of diet and nutrition measured in NHANES 2003-2006.

    PubMed

    Sternberg, Maya R; Schleicher, Rosemary L; Pfeiffer, Christine M

    2013-06-01

    The collection of articles in this supplement issue provides insight into the association of various covariates with concentrations of biochemical indicators of diet and nutrition (biomarkers), beyond age, race, and sex, using linear regression. We studied 10 specific sociodemographic and lifestyle covariates in combination with 29 biomarkers from NHANES 2003-2006 for persons aged ≥ 20 y. The covariates were organized into 2 sets or "chunks": sociodemographic (age, sex, race-ethnicity, education, and income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, and physical activity) and fit in hierarchical fashion by using each category or set of related variables to determine how covariates, jointly, are related to biomarker concentrations. In contrast to many regression modeling applications, all variables were retained in a full regression model regardless of significance to preserve the interpretation of the statistical properties of β coefficients, P values, and CIs and to keep the interpretation consistent across a set of biomarkers. The variables were preselected before data analysis, and the data analysis plan was designed at the outset to minimize the reporting of false-positive findings by limiting the amount of preliminary hypothesis testing. Although we generally found that demographic differences seen in biomarkers were over- or underestimated when ignoring other key covariates, the demographic differences generally remained significant after adjusting for sociodemographic and lifestyle variables. These articles are intended to provide a foundation to researchers to help them generate hypotheses for future studies or data analyses and/or develop predictive regression models using the wealth of NHANES data.

  8. A general framework for the use of logistic regression models in meta-analysis.

    PubMed

    Simmonds, Mark C; Higgins, Julian Pt

    2016-12-01

    Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

  9. Risk Adjustment for Medicare Total Knee Arthroplasty Bundled Payments.

    PubMed

    Clement, R Carter; Derman, Peter B; Kheir, Michael M; Soo, Adrianne E; Flynn, David N; Levin, L Scott; Fleisher, Lee

    2016-09-01

    The use of bundled payments is growing because of their potential to align providers and hospitals on the goal of cost reduction. However, such gain sharing could incentivize providers to "cherry-pick" more profitable patients. Risk adjustment can prevent this unintended consequence, yet most bundling programs include minimal adjustment techniques. This study was conducted to determine how bundled payments for total knee arthroplasty (TKA) should be adjusted for risk. The authors collected financial data for all Medicare patients (age≥65 years) undergoing primary unilateral TKA at an academic center over a period of 2 years (n=941). Multivariate regression was performed to assess the effect of patient factors on the costs of acute inpatient care, including unplanned 30-day readmissions. This analysis mirrors a bundling model used in the Medicare Bundled Payments for Care Improvement initiative. Increased age, American Society of Anesthesiologists (ASA) class, and the presence of a Medicare Major Complications/Comorbid Conditions (MCC) modifier (typically representing major complications) were associated with increased costs (regression coefficients, $57 per year; $729 per ASA class beyond I; and $3122 for patients meeting MCC criteria; P=.003, P=.001, and P<.001, respectively). Differences in costs were not associated with body mass index, sex, or race. If the results are generalizable, Medicare bundled payments for TKA encompassing acute inpatient care should be adjusted upward by the stated amounts for older patients, those with elevated ASA class, and patients meeting MCC criteria. This is likely an underestimate for many bundling models, including the Comprehensive Care for Joint Replacement program, incorporating varying degrees of postacute care. Failure to adjust for factors that affect costs may create adverse incentives, creating barriers to care for certain patient populations. [Orthopedics. 2016; 39(5):e911-e916.]. Copyright 2016, SLACK Incorporated.

  10. Sexual satisfaction, sexual compatibility, and relationship adjustment in couples: the role of sexual behaviors, orgasm, and men's discernment of women's intercourse orgasm.

    PubMed

    Klapilová, Kateřina; Brody, Stuart; Krejčová, Lucie; Husárová, Barbara; Binter, Jakub

    2015-03-01

    Research indicated that (i) vaginal orgasm consistency is associated with indices of psychological, intimate relationship, and physiological functioning, and (ii) masturbation is adversely associated with some such measures. The aim of this study was to examine the association of various dyadic and masturbation behavior frequencies and percentage of female orgasms during these activities with: (i) measures of dyadic adjustment; (ii) sexual satisfaction; and (iii) compatibility perceived by both partners. In a sample of 85 Czech long-term couples (aged 20-40; mean relationship length 5.4 years), both partners provided details of recent sexual behaviors and completed sexual satisfaction, Spanier dyadic adjustment, and Hurlbert sexual compatibility measures. Multiple regression analyses were used. The association of sexual behaviors with dyadic adjustment, sexual compatibility, and satisfaction was analyzed. In multivariate analyses, women's dyadic adjustment is independently predicted by greater vaginal orgasm consistency and lower frequency of women's masturbation. For both sexes, sexual compatibility was independently predicted by higher frequency of penile-vaginal intercourse and greater vaginal orgasm consistency. Women's sexual satisfaction score was significantly predicted by greater vaginal orgasm consistency, frequency of partner genital stimulation, and negatively with masturbation. Men's sexual satisfaction score was significantly predicted by greater intercourse frequency and any vaginal orgasm of their female partners. Concordance of partner vaginal orgasm consistency estimates was associated with greater dyadic adjustment. The findings suggest that specifically penile-vaginal intercourse frequency and vaginal orgasm consistency are associated with indices of greater intimate relationship adjustment, satisfaction, and compatibility of both partners, and that women's masturbation is independently inversely associated with measures of dyadic and personal

  11. A computational approach to compare regression modelling strategies in prediction research.

    PubMed

    Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H

    2016-08-25

    It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.

  12. Risk factors for autistic regression: results of an ambispective cohort study.

    PubMed

    Zhang, Ying; Xu, Qiong; Liu, Jing; Li, She-chang; Xu, Xiu

    2012-08-01

    A subgroup of children diagnosed with autism experience developmental regression featured by a loss of previously acquired abilities. The pathogeny of autistic regression is unknown, although many risk factors likely exist. To better characterize autistic regression and investigate the association between autistic regression and potential influencing factors in Chinese autistic children, we conducted an ambispective study with a cohort of 170 autistic subjects. Analyses by multiple logistic regression showed significant correlations between autistic regression and febrile seizures (OR = 3.53, 95% CI = 1.17-10.65, P = .025), as well as with a family history of neuropsychiatric disorders (OR = 3.62, 95% CI = 1.35-9.71, P = .011). This study suggests that febrile seizures and family history of neuropsychiatric disorders are correlated with autistic regression.

  13. Retro-regression--another important multivariate regression improvement.

    PubMed

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  14. Modified Regression Correlation Coefficient for Poisson Regression Model

    NASA Astrophysics Data System (ADS)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  15. Poisson regression models outperform the geometrical model in estimating the peak-to-trough ratio of seasonal variation: a simulation study.

    PubMed

    Christensen, A L; Lundbye-Christensen, S; Dethlefsen, C

    2011-12-01

    Several statistical methods of assessing seasonal variation are available. Brookhart and Rothman [3] proposed a second-order moment-based estimator based on the geometrical model derived by Edwards [1], and reported that this estimator is superior in estimating the peak-to-trough ratio of seasonal variation compared with Edwards' estimator with respect to bias and mean squared error. Alternatively, seasonal variation may be modelled using a Poisson regression model, which provides flexibility in modelling the pattern of seasonal variation and adjustments for covariates. Based on a Monte Carlo simulation study three estimators, one based on the geometrical model, and two based on log-linear Poisson regression models, were evaluated in regards to bias and standard deviation (SD). We evaluated the estimators on data simulated according to schemes varying in seasonal variation and presence of a secular trend. All methods and analyses in this paper are available in the R package Peak2Trough[13]. Applying a Poisson regression model resulted in lower absolute bias and SD for data simulated according to the corresponding model assumptions. Poisson regression models had lower bias and SD for data simulated to deviate from the corresponding model assumptions than the geometrical model. This simulation study encourages the use of Poisson regression models in estimating the peak-to-trough ratio of seasonal variation as opposed to the geometrical model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  16. Parental divorce and adjustment in adulthood: findings from a community sample. The ALSPAC Study Team. Avon Longitudinal Study of Pregnancy and Childhood.

    PubMed

    O'Connor, T G; Thorpe, K; Dunn, J; Golding, J

    1999-07-01

    The current study examines the link between the experience of divorce in childhood and several indices of adjustment in adulthood in a large community sample of women. Results replicated previous research on the long-term correlation between parental divorce and depression and divorce in adulthood. Results further suggested that parental divorce was associated with a wide range of early risk factors, life course patterns, and several indices of adult adjustment. Regression analyses indicated that the long-term correlation between parental divorce and depression in adulthood is explained by quality of parent-child and parental marital relations (in childhood), concurrent levels of stressful life events and social support, and cohabitation. The long-term association between parental divorce and experiencing a divorce in adulthood was partly mediated through quality of parent-child relations, teenage pregnancy, leaving home before 18 years, and educational attainment.

  17. Trace lithium is inversely associated with male suicide after adjustment of climatic factors.

    PubMed

    Shiotsuki, Ippei; Terao, Takeshi; Ishii, Nobuyoshi; Takeuchi, Shouhei; Kuroda, Yoshiki; Kohno, Kentaro; Mizokami, Yoshinori; Hatano, Koji; Tanabe, Sanshi; Kanehisa, Masayuki; Iwata, Noboru; Matusda, Shinya

    2016-01-01

    Previously, we showed the inverse association between lithium in drinking water and male suicide in Kyushu Island. The narrow variation in meteorological factors of Kyushu Island and a considerable amount of evidence regarding the role of the factors on suicide provoked the necessities of adjusting the association by the wide variation in sunshine, temperature, rain fall, and snow fall. To keep the wide variation in meteorological factors, we combined the data of Kyushu (the southernmost city is Itoman, 26°) and Hokkaido (the northernmost city is Wakkanai, 45°). Multiple regression analyses were used to predict suicide SMRs (total, male and female) by lithium levels in drinking water and meteorological factors. After adjustment of meteorological factors, lithium levels were significantly and inversely associated with male suicide SMRs, but not with total or female suicide SMRs, across the 153 cities of Hokkaido and Kyushu Islands. Moreover, annual total sunshine and annual mean temperature were significantly and inversely associated with male suicide SMRs whereas annual total rainfall was significantly and directly associated with male suicide SMRs. The limitations of the present study include the lack of data relevant to lithium levels in food and the proportion of the population who drank tap water and their consumption habits. The present findings suggest that trace lithium is inversely associated with male but not female suicide after adjustment of meteorological factors. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. The mediating role of shame in the relationship between childhood bullying victimization and adult psychosocial adjustment

    PubMed Central

    Strøm, Ida Frugård; Aakvaag, Helene Flood; Birkeland, Marianne Skogbrott; Felix, Erika; Thoresen, Siri

    2018-01-01

    ABSTRACT Background: Psychological distress following experiencing bullying victimization in childhood has been well documented. Less is known about the impact of bullying victimization on psychosocial adjustment problems in young adulthood and about potential pathways, such as shame. Moreover, bullying victimization is often studied in isolation from other forms of victimization. Objective: This study investigated (1) whether childhood experiences of bullying victimization and violence were associated with psychosocial adjustment (distress, impaired functioning, social support barriers) in young adulthood; (2) the unique effect of bullying victimization on psychosocial adjustment; and (3) whether shame mediated the relationship between bullying victimization and these outcomes in young adulthood. Method: The sample included 681 respondents (aged 19–37 years) from a follow-up study (2017) conducted via phone interviews derived from a community telephone survey collected in 2013. Results: The regression analyses showed that both bullying victimization and severe violence were significantly and independently associated with psychological distress, impaired functioning, and increased barriers to social support in young adulthood. Moreover, causal mediation analyses indicated that when childhood physical violence, sexual abuse, and sociodemographic factors were controlled, shame mediated 70% of the association between bullying victimization and psychological distress, 55% of the association between bullying victimization and impaired functioning, and 40% of the association between bullying victimization and social support barriers. Conclusions: Our findings support the growing literature acknowledging bullying victimization as a trauma with severe and long-lasting consequences and indicate that shame may be an important pathway to continue to explore. The unique effect of bullying victimization, over and above the effect of violence, supports the call to integrate

  19. An Empirical Study of Eight Nonparametric Tests in Hierarchical Regression.

    ERIC Educational Resources Information Center

    Harwell, Michael; Serlin, Ronald C.

    When normality does not hold, nonparametric tests represent an important data-analytic alternative to parametric tests. However, the use of nonparametric tests in educational research has been limited by the absence of easily performed tests for complex experimental designs and analyses, such as factorial designs and multiple regression analyses,…

  20. Methods for Adjusting U.S. Geological Survey Rural Regression Peak Discharges in an Urban Setting

    USGS Publications Warehouse

    Moglen, Glenn E.; Shivers, Dorianne E.

    2006-01-01

    A study was conducted of 78 U.S. Geological Survey gaged streams that have been subjected to varying degrees of urbanization over the last three decades. Flood-frequency analysis coupled with nonlinear regression techniques were used to generate a set of equations for converting peak discharge estimates determined from rural regression equations to a set of peak discharge estimates that represent known urbanization. Specifically, urban regression equations for the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year return periods were calibrated as a function of the corresponding rural peak discharge and the percentage of impervious area in a watershed. The results of this study indicate that two sets of equations, one set based on imperviousness and one set based on population density, performed well. Both sets of equations are dependent on rural peak discharges, a measure of development (average percentage of imperviousness or average population density), and a measure of homogeneity of development within a watershed. Average imperviousness was readily determined by using geographic information system methods and commonly available land-cover data. Similarly, average population density was easily determined from census data. Thus, a key advantage to the equations developed in this study is that they do not require field measurements of watershed characteristics as did the U.S. Geological Survey urban equations developed in an earlier investigation. During this study, the U.S. Geological Survey PeakFQ program was used as an integral tool in the calibration of all equations. The scarcity of historical land-use data, however, made exclusive use of flow records necessary for the 30-year period from 1970 to 2000. Such relatively short-duration streamflow time series required a nonstandard treatment of the historical data function of the PeakFQ program in comparison to published guidelines. Thus, the approach used during this investigation does not fully comply with the

  1. Do Afterlife Beliefs Affect Psychological Adjustment to Late-Life Spousal Loss?

    PubMed Central

    2014-01-01

    Objectives. We explore whether beliefs about the existence and nature of an afterlife affect 5 psychological symptoms (anxiety, anger, depression, intrusive thoughts, and yearning) among recently bereaved older spouses. Method. We conduct multivariate regression analyses using data from the Changing Lives of Older Couples (CLOC), a prospective study of spousal loss. The CLOC obtained data from bereaved persons prior to loss and both 6 and 18 months postloss. All analyses are adjusted for health, sociodemographic characteristics, and preloss marital quality. Results. Bleak or uncertain views about the afterlife are associated with multiple aspects of distress postloss. Uncertainty about the existence of an afterlife is associated with elevated intrusive thoughts, a symptom similar to posttraumatic distress. Widowed persons who do not expect to be reunited with loved ones in the afterlife report significantly more depressive symptoms, anger, and intrusive thoughts at both 6 and 18 months postloss. Discussion. Beliefs in an afterlife may be maladaptive for coping with late-life spousal loss, particularly if one is uncertain about its existence or holds a pessimistic view of what the afterlife entails. Our findings are broadly consistent with recent work suggesting that “continuing bonds” with the decedent may not be adaptive for older bereaved spouses. PMID:23811692

  2. Use of Prolonged Travel to Improve Pediatric Risk-Adjustment Models

    PubMed Central

    Lorch, Scott A; Silber, Jeffrey H; Even-Shoshan, Orit; Millman, Andrea

    2009-01-01

    Objective To determine whether travel variables could explain previously reported differences in lengths of stay (LOS), readmission, or death at children's hospitals versus other hospital types. Data Source Hospital discharge data from Pennsylvania between 1996 and 1998. Study Design A population cohort of children aged 1–17 years with one of 19 common pediatric conditions was created (N=51,855). Regression models were constructed to determine difference for LOS, readmission, or death between children's hospitals and other types of hospitals after including five types of additional illness severity variables to a traditional risk-adjustment model. Principal Findings With the traditional risk-adjustment model, children traveling longer to children's or rural hospitals had longer adjusted LOS and higher readmission rates. Inclusion of either a geocoded travel time variable or a nongeocoded travel distance variable provided the largest reduction in adjusted LOS, adjusted readmission rates, and adjusted mortality rates for children's hospitals and rural hospitals compared with other types of hospitals. Conclusions Adding a travel variable to traditional severity adjustment models may improve the assessment of an individual hospital's pediatric care by reducing systematic differences between different types of hospitals. PMID:19207591

  3. Performance of diagnosis-based risk adjustment measures in a population of sick Australians.

    PubMed

    Duckett, S J; Agius, P A

    2002-12-01

    Australia is beginning to explore 'managed competition' as an organising framework for the health care system. This requires setting fair capitation rates, i.e. rates that adjust for the risk profile of covered lives. This paper tests two US-developed risk adjustment approaches using Australian data. Data from the 'co-ordinated care' dataset (which incorporates all service costs of 16,538 participants in a large health service research project conducted in 1996-99) were grouped into homogenous risk categories using risk adjustment 'grouper software'. The grouper products yielded three sets of homogenous categories: Diagnostic Groups and Diagnostic cost Groups. A two-stage analysis of predictive power was used: probability of any service use in the concurrent year, next year and the year after (logistic regression) and, for service users, a regression of logged cost of service use. The independent variables were diagnosis gender, a SES variable and the Age, gender and diagnosis-based risk adjustment measures explain around 40-45% of variation in costs of service use in the current year for untrimmed data (compared with around 15% for age and gender alone). Prediction of subsequent use is much poorer (around 20%). Using more information to assign people to risk categories generally improves prediction. Predictive power of diagnosis-base risk adjusters on this Australian dataset is similar to that found in Low predictive power carries policy risks of cream skimming rather than managing population health and care. Competitive funding models with risk adjustment on prior year experience could reduce system efficiency if implemented with current risk adjustment technology.

  4. Positive and negative meanings are simultaneously ascribed to colorectal cancer: relationship to quality of life and psychosocial adjustment.

    PubMed

    Camacho, Aldo Aguirre; Garland, Sheila N; Martopullo, Celestina; Pelletier, Guy

    2014-08-01

    Experiencing cancer can give rise to existential concerns causing great distress, and consequently drive individuals to make sense of what cancer may mean to their lives. To date, meaning-based research in the context of cancer has largely focused on one possible outcome of this process, the emergence of positive meanings (e.g. post-traumatic growth). However, negative meanings may also be ascribed to cancer, simultaneously with positive meanings. This study focused on the nature of the co-existence of positive and negative meanings in a sample of individuals diagnosed with colorectal cancer to find out whether negative meaning had an impact on quality of life and psychosocial adjustment above and beyond positive meaning. Participants were given questionnaires measuring meaning-made, quality of life, and psychological distress. Semi structured interviews were conducted with a subgroup from the original sample. Hierarchical multiple regression analyses revealed that negative meaning-made (i.e. helplessness) was a significant predictor of poor quality of life and increased levels of depression/anxiety above and beyond positive meaning-made (i.e. life meaningfulness, acceptance, and perceived benefits). Correlational analyses and interview data revealed that negative meaning-made was mainly associated with physical and functional disability, while positive meaning-made was mostly related to emotional and psychological well-being. Meanings of varying valence may simultaneously be ascribed to cancer as it impacts different life dimensions, and they may independently influence quality of life and psychosocial adjustment. The presence of positive meaning was not enough to prevent the detrimental effects of negative meaning on psychosocial adjustment and quality of life among individuals taking part in this study. Future attention to negative meaning is warranted, as it may be at least as important as positive meaning in predicting psychosocial adjustment and quality of

  5. Estimating effects of limiting factors with regression quantiles

    USGS Publications Warehouse

    Cade, B.S.; Terrell, J.W.; Schroeder, R.L.

    1999-01-01

    In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem of minimizing an asymmetric function of absolute errors. Rank-score tests for regression quantiles provide tests of hypotheses and confidence intervals for parameters in linear models with heteroscedastic errors, conditions likely to occur in models of limiting ecological relations. We used selected regression quantiles (e.g., 5th, 10th, ..., 95th) and confidence intervals to test hypotheses that parameters equal zero for estimated changes in average annual acorn biomass due to forest canopy cover of oak (Quercus spp.) and oak species diversity. Regression quantiles also were used to estimate changes in glacier lily (Erythronium grandiflorum) seedling numbers as a function of lily flower numbers, rockiness, and pocket gopher (Thomomys talpoides fossor) activity, data that motivated the query by Thomson et al. for new statistical procedures. Both example applications showed that effects of limiting factors estimated by changes in some upper regression quantile (e

  6. Exploring reasons for the observed inconsistent trial reports on intra-articular injections with hyaluronic acid in the treatment of osteoarthritis: Meta-regression analyses of randomized trials.

    PubMed

    Johansen, Mette; Bahrt, Henriette; Altman, Roy D; Bartels, Else M; Juhl, Carsten B; Bliddal, Henning; Lund, Hans; Christensen, Robin

    2016-08-01

    The aim was to identify factors explaining inconsistent observations concerning the efficacy of intra-articular hyaluronic acid compared to intra-articular sham/control, or non-intervention control, in patients with symptomatic osteoarthritis, based on randomized clinical trials (RCTs). A systematic review and meta-regression analyses of available randomized trials were conducted. The outcome, pain, was assessed according to a pre-specified hierarchy of potentially available outcomes. Hedges׳s standardized mean difference [SMD (95% CI)] served as effect size. REstricted Maximum Likelihood (REML) mixed-effects models were used to combine study results, and heterogeneity was calculated and interpreted as Tau-squared and I-squared, respectively. Overall, 99 studies (14,804 patients) met the inclusion criteria: Of these, only 71 studies (72%), including 85 comparisons (11,216 patients), had adequate data available for inclusion in the primary meta-analysis. Overall, compared with placebo, intra-articular hyaluronic acid reduced pain with an effect size of -0.39 [-0.47 to -0.31; P < 0.001], combining very heterogeneous trial findings (I(2) = 73%). The three most important covariates in reducing heterogeneity were overall risk of bias, blinding of personnel and trial size, reducing heterogeneity with 26%, 26%, and 25%, respectively (Interaction: P ≤ 0.001). Adjusting for publication/selective outcome reporting bias (by imputing "null effects") in 24 of the comparisons with no data available reduced the combined estimate to -0.30 [-0.36 to -0.23; P < 0.001] still in favor of hyaluronic acid. Based on available trial data, intra-articular hyaluronic acid showed a better effect than intra-articular saline on pain reduction in osteoarthritis. Publication bias and the risk of selective outcome reporting suggest only small clinical effect compared to saline. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Intermediate and advanced topics in multilevel logistic regression analysis

    PubMed Central

    Merlo, Juan

    2017-01-01

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517

  8. Independent contrasts and PGLS regression estimators are equivalent.

    PubMed

    Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

    2012-05-01

    We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

  9. The Impact of Financial Sophistication on Adjustable Rate Mortgage Ownership

    ERIC Educational Resources Information Center

    Smith, Hyrum; Finke, Michael S.; Huston, Sandra J.

    2011-01-01

    The influence of a financial sophistication scale on adjustable-rate mortgage (ARM) borrowing is explored. Descriptive statistics and regression analysis using recent data from the Survey of Consumer Finances reveal that ARM borrowing is driven by both the least and most financially sophisticated households but for different reasons. Less…

  10. Integrating Risk Adjustment and Enrollee Premiums in Health Plan Payment

    PubMed Central

    McGuire, Thomas G.; Glazer, Jacob; Newhouse, Joseph P.; Normand, Sharon-Lise; Shi, Julie; Sinaiko, Anna D.; Zuvekas, Samuel

    2013-01-01

    In two important health policy contexts – private plans in Medicare and the new state-run “Exchanges” created as part of the Affordable Care Act (ACA) – plan payments come from two sources: risk-adjusted payments from a Regulator and premiums charged to individual enrollees. This paper derives principles for integrating risk-adjusted payments and premium policy in individual health insurance markets based on fitting total plan payments to health plan costs per person as closely as possible. A least squares regression including both health status and variables used in premiums reveals the weights a Regulator should put on risk adjusters when markets determine premiums. We apply the methods to an Exchange-eligible population drawn from the Medical Expenditure Panel Survey (MEPS). PMID:24308878

  11. Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

    PubMed

    Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

    2012-02-08

    The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

  12. The adjustable intelligent atrium sunshade

    NASA Astrophysics Data System (ADS)

    Ni, Xin; Sun, Jianhua; Wang, Bo

    2017-05-01

    This article is focused on the specific design techniques of the adjustable atrium sunshade, on the basis of the engineering analyses and practices, it is expected to alter the conventional atrium sunshade design concepts; with its uniqueness and technical excellence, this innovative atrium sunshade system exhibits rich emotions and artistry, creates an inspiring and romantic atmosphere at the atrium area of the building.

  13. 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.

  14. Best friend attachment versus peer attachment in the prediction of adolescent psychological adjustment.

    PubMed

    Wilkinson, Ross B

    2010-10-01

    This study examined the utility of the newly developed Adolescent Friendship Attachment Scale (AFAS) for the prediction of adolescent psychological health and school attitude. High school students (266 males, 229 females) were recruited from private and public schools in the Australian Capital Territory with ages of participants ranging from 13 to 19 years. Self-report measures of depression, self-esteem, self-competence and school attitude were administered in addition to the AFAS and a short-form of the Inventory of Parental and Peer Attachment (IPPA). Regression analyses revealed that the AFAS Anxious and Avoidant scales added to the prediction of depression, self-esteem, self-competence, and school attitude beyond the contribution of the IPPA. It is concluded that the AFAS taps aspects of adolescent attachment relationships not assessed by the IPPA and provides a useful contribution to research and practice in the area of adolescent psycho-social adjustment.

  15. Quantum algorithm for linear regression

    NASA Astrophysics Data System (ADS)

    Wang, Guoming

    2017-07-01

    We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

  16. Multiple regression analysis in nomogram development for myopic wavefront laser in situ keratomileusis: Improving astigmatic outcomes.

    PubMed

    Allan, Bruce D; Hassan, Hala; Ieong, Alvin

    2015-05-01

    To describe and evaluate a new multiple regression-derived nomogram for myopic wavefront laser in situ keratomileusis (LASIK). Moorfields Eye Hospital, London, United Kingdom. Prospective comparative case series. Multiple regression modeling was used to derive a simplified formula for adjusting attempted spherical correction in myopic LASIK. An adaptation of Thibos' power vector method was then applied to derive adjustments to attempted cylindrical correction in eyes with 1.0 diopter (D) or more of preoperative cylinder. These elements were combined in a new nomogram (nomogram II). The 3-month refractive results for myopic wavefront LASIK (spherical equivalent ≤11.0 D; cylinder ≤4.5 D) were compared between 299 consecutive eyes treated using the earlier nomogram (nomogram I) in 2009 and 2010 and 414 eyes treated using nomogram II in 2011 and 2012. There was no significant difference in treatment accuracy (variance in the postoperative manifest refraction spherical equivalent error) between nomogram I and nomogram II (P = .73, Bartlett test). Fewer patients treated with nomogram II had more than 0.5 D of residual postoperative astigmatism (P = .0001, Fisher exact test). There was no significant coupling between adjustments to the attempted cylinder and the achieved sphere (P = .18, t test). Discarding marginal influences from a multiple regression-derived nomogram for myopic wavefront LASIK had no clinically significant effect on treatment accuracy. Thibos' power vector method can be used to guide adjustments to the treatment cylinder alongside nomograms designed to optimize postoperative spherical equivalent results in myopic LASIK. mentioned. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  17. An Adjusted Likelihood Ratio Approach Analysing Distribution of Food Products to Assist the Investigation of Foodborne Outbreaks

    PubMed Central

    Norström, Madelaine; Kristoffersen, Anja Bråthen; Görlach, Franziska Sophie; Nygård, Karin; Hopp, Petter

    2015-01-01

    In order to facilitate foodborne outbreak investigations there is a need to improve the methods for identifying the food products that should be sampled for laboratory analysis. The aim of this study was to examine the applicability of a likelihood ratio approach previously developed on simulated data, to real outbreak data. We used human case and food product distribution data from the Norwegian enterohaemorrhagic Escherichia coli outbreak in 2006. The approach was adjusted to include time, space smoothing and to handle missing or misclassified information. The performance of the adjusted likelihood ratio approach on the data originating from the HUS outbreak and control data indicates that the adjusted approach is promising and indicates that the adjusted approach could be a useful tool to assist and facilitate the investigation of food borne outbreaks in the future if good traceability are available and implemented in the distribution chain. However, the approach needs to be further validated on other outbreak data and also including other food products than meat products in order to make a more general conclusion of the applicability of the developed approach. PMID:26237468

  18. Regional Regression Equations to Estimate Flow-Duration Statistics at Ungaged Stream Sites in Connecticut

    USGS Publications Warehouse

    Ahearn, Elizabeth A.

    2010-01-01

    Multiple linear regression equations for determining flow-duration statistics were developed to estimate select flow exceedances ranging from 25- to 99-percent for six 'bioperiods'-Salmonid Spawning (November), Overwinter (December-February), Habitat Forming (March-April), Clupeid Spawning (May), Resident Spawning (June), and Rearing and Growth (July-October)-in Connecticut. Regression equations also were developed to estimate the 25- and 99-percent flow exceedances without reference to a bioperiod. In total, 32 equations were developed. The predictive equations were based on regression analyses relating flow statistics from streamgages to GIS-determined basin and climatic characteristics for the drainage areas of those streamgages. Thirty-nine streamgages (and an additional 6 short-term streamgages and 28 partial-record sites for the non-bioperiod 99-percent exceedance) in Connecticut and adjacent areas of neighboring States were used in the regression analysis. Weighted least squares regression analysis was used to determine the predictive equations; weights were assigned based on record length. The basin characteristics-drainage area, percentage of area with coarse-grained stratified deposits, percentage of area with wetlands, mean monthly precipitation (November), mean seasonal precipitation (December, January, and February), and mean basin elevation-are used as explanatory variables in the equations. Standard errors of estimate of the 32 equations ranged from 10.7 to 156 percent with medians of 19.2 and 55.4 percent to predict the 25- and 99-percent exceedances, respectively. Regression equations to estimate high and median flows (25- to 75-percent exceedances) are better predictors (smaller variability of the residual values around the regression line) than the equations to estimate low flows (less than 75-percent exceedance). The Habitat Forming (March-April) bioperiod had the smallest standard errors of estimate, ranging from 10.7 to 20.9 percent. In

  19. BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

    PubMed Central

    Zhu, Xiang; Stephens, Matthew

    2017-01-01

    Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

  20. Intermediate and advanced topics in multilevel logistic regression analysis.

    PubMed

    Austin, Peter C; Merlo, Juan

    2017-09-10

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  1. Regression discontinuity was a valid design for dichotomous outcomes in three randomized trials.

    PubMed

    van Leeuwen, Nikki; Lingsma, Hester F; Mooijaart, Simon P; Nieboer, Daan; Trompet, Stella; Steyerberg, Ewout W

    2018-06-01

    Regression discontinuity (RD) is a quasi-experimental design that may provide valid estimates of treatment effects in case of continuous outcomes. We aimed to evaluate validity and precision in the RD design for dichotomous outcomes. We performed validation studies in three large randomized controlled trials (RCTs) (Corticosteroid Randomization After Significant Head injury [CRASH], the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries [GUSTO], and PROspective Study of Pravastatin in elderly individuals at risk of vascular disease [PROSPER]). To mimic the RD design, we selected patients above and below a cutoff (e.g., age 75 years) randomized to treatment and control, respectively. Adjusted logistic regression models using restricted cubic splines (RCS) and polynomials and local logistic regression models estimated the odds ratio (OR) for treatment, with 95% confidence intervals (CIs) to indicate precision. In CRASH, treatment increased mortality with OR 1.22 [95% CI 1.06-1.40] in the RCT. The RD estimates were 1.42 (0.94-2.16) and 1.13 (0.90-1.40) with RCS adjustment and local regression, respectively. In GUSTO, treatment reduced mortality (OR 0.83 [0.72-0.95]), with more extreme estimates in the RD analysis (OR 0.57 [0.35; 0.92] and 0.67 [0.51; 0.86]). In PROSPER, similar RCT and RD estimates were found, again with less precision in RD designs. We conclude that the RD design provides similar but substantially less precise treatment effect estimates compared with an RCT, with local regression being the preferred method of analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

    NASA Technical Reports Server (NTRS)

    Boone, Spencer

    2017-01-01

    This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

  3. Integrating risk adjustment and enrollee premiums in health plan payment.

    PubMed

    McGuire, Thomas G; Glazer, Jacob; Newhouse, Joseph P; Normand, Sharon-Lise; Shi, Julie; Sinaiko, Anna D; Zuvekas, Samuel H

    2013-12-01

    In two important health policy contexts - private plans in Medicare and the new state-run "Exchanges" created as part of the Affordable Care Act (ACA) - plan payments come from two sources: risk-adjusted payments from a Regulator and premiums charged to individual enrollees. This paper derives principles for integrating risk-adjusted payments and premium policy in individual health insurance markets based on fitting total plan payments to health plan costs per person as closely as possible. A least squares regression including both health status and variables used in premiums reveals the weights a Regulator should put on risk adjusters when markets determine premiums. We apply the methods to an Exchange-eligible population drawn from the Medical Expenditure Panel Survey (MEPS). Copyright © 2013 Elsevier B.V. All rights reserved.

  4. How Many Subjects Does It Take to Do a Regression Analysis?

    ERIC Educational Resources Information Center

    Green, Samuel B.

    1991-01-01

    An evaluation of the rules-of-thumb used to determine the minimum number of subjects required to conduct multiple regression analyses suggests that researchers who use a rule of thumb rather than power analyses trade simplicity of use for accuracy and specificity of response. Insufficient power is likely to result. (SLD)

  5. Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

    ERIC Educational Resources Information Center

    Wu, Dane W.

    2002-01-01

    The year 2000 US presidential election between Al Gore and George Bush has been the most intriguing and controversial one in American history. The state of Florida was the trigger for the controversy, mainly, due to the use of the misleading "butterfly ballot". Using prediction (or confidence) intervals for least squares regression lines…

  6. Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

    PubMed

    Rose, Sherri

    2018-03-11

    To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

  7. Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with non-cephalic presentation using logistic regression and classification tree analyses.

    PubMed

    Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana

    2017-08-01

    Among women with a fetus with a non-cephalic presentation, external cephalic version (ECV) has been shown to reduce the rate of breech presentation at birth and cesarean birth. Compared with ECV at term, beginning ECV prior to 37 weeks' gestation decreases the number of infants in a non-cephalic presentation at birth. The purpose of this secondary analysis was to investigate factors associated with a successful ECV procedure and to present this in a clinically useful format. Data were collected as part of the Early ECV Pilot and Early ECV2 Trials, which randomized 1776 women with a fetus in breech presentation to either early ECV (34-36 weeks' gestation) or delayed ECV (at or after 37 weeks). The outcome of interest was successful ECV, defined as the fetus being in a cephalic presentation immediately following the procedure, as well as at the time of birth. The importance of several factors in predicting successful ECV was investigated using two statistical methods: logistic regression and classification and regression tree (CART) analyses. Among nulliparas, non-engagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, non-engagement of the presenting part, gestation less than 37 weeks and an easily palpable fetal head were found to be independent predictors of success. These findings were consistent with results of the CART analyses. Regardless of parity, descent of the presenting part was the most discriminating factor in predicting successful ECV and cephalic presentation at birth. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  8. School-Based Racial and Gender Discrimination among African American Adolescents: Exploring Gender Variation in Frequency and Implications for Adjustment.

    PubMed

    Cogburn, Courtney D; Chavous, Tabbye M; Griffin, Tiffany M

    2011-01-03

    The present study examined school-based racial and gender discrimination experiences among African American adolescents in Grade 8 (n = 204 girls; n = 209 boys). A primary goal was exploring gender variation in frequency of both types of discrimination and associations of discrimination with academic and psychological functioning among girls and boys. Girls and boys did not vary in reported racial discrimination frequency, but boys reported more gender discrimination experiences. Multiple regression analyses within gender groups indicated that among girls and boys, racial discrimination and gender discrimination predicted higher depressive symptoms and school importance and racial discrimination predicted self-esteem. Racial and gender discrimination were also negatively associated with grade point average among boys but were not significantly associated in girls' analyses. Significant gender discrimination X racial discrimination interactions resulted in the girls' models predicting psychological outcomes and in boys' models predicting academic achievement. Taken together, findings suggest the importance of considering gender- and race-related experiences in understanding academic and psychological adjustment among African American adolescents.

  9. Bidirectional associations between valued activities and adolescent positive adjustment in a longitudinal study: positive mood as a mediator.

    PubMed

    DesRoches, Andrea; Willoughby, Teena

    2014-02-01

    Although activity involvement has been linked to positive youth development, the value that adolescents place on these activities (i.e., how much they enjoy the activities, find them important, and spend time on them) has received less attention. The purpose of the present study was to examine the bidirectional longitudinal association between engagement in valued activities and adolescent positive adjustment (optimism, purpose in life, and self-esteem), as well as investigate a possible underlying mechanism for this link. High school students (N = 2,270, 48.7% female) from Ontario, Canada completed questionnaires annually in grades 10, 11, and 12. Auto-regressive cross-lagged path analyses were conducted over time, controlling for gender, parental education, and academic grades. Greater engagement in valued activities predicted higher optimism, purpose, and self-esteem over time. Importantly, the results did not support an alternate hypothesis of selection effects, in that adolescents who were better adjusted were not more likely than their peers to engage in valued activities over time. We also found that the longitudinal associations between valued activities and positive adjustment may be due partly to an underlying effect of increased positive mood. Thus, engagement in valued activities appears to be important for adolescent positive adjustment, and may help to foster thriving. Communities, educators, and parents should actively support and encourage adolescents to develop valued activities, and seek to ensure that there are ample opportunities and resources available for them to do so.

  10. Stolon regression

    PubMed Central

    Cherry Vogt, Kimberly S

    2008-01-01

    Many colonial organisms encrust surfaces with feeding and reproductive polyps connected by vascular stolons. Such colonies often show a dichotomy between runner-like forms, with widely spaced polyps and long stolon connections, and sheet-like forms, with closely spaced polyps and short stolon connections. Generative processes, such as rates of polyp initiation relative to rates of stolon elongation, are typically thought to underlie this dichotomy. Regressive processes, such as tissue regression and cell death, may also be relevant. In this context, we have recently characterized the process of stolon regression in a colonial cnidarian, Podocoryna carnea. Stolon regression occurs naturally in these colonies. To characterize this process in detail, high levels of stolon regression were induced in experimental colonies by treatment with reactive oxygen and reactive nitrogen species (ROS and RNS). Either treatment results in stolon regression and is accompanied by high levels of endogenous ROS and RNS as well as morphological indications of cell death in the regressing stolon. The initiating step in regression appears to be a perturbation of normal colony-wide gastrovascular flow. This suggests more general connections between stolon regression and a wide variety of environmental effects. Here we summarize our results and further discuss such connections. PMID:19704785

  11. New regression formula for toric intraocular lens calculations.

    PubMed

    Abulafia, Adi; Koch, Douglas D; Wang, Li; Hill, Warren E; Assia, Ehud I; Franchina, Maria; Barrett, Graham D

    2016-05-01

    To evaluate and compare the accuracy of 2 toric intraocular lens (IOL) calculators with or without a new regression formula. Ein-Tal Eye Center, Tel-Aviv, Israel, and the Lions Eye Institute, Nedlands, Western Australia, Australia. Retrospective case series. A new regression formula (Abulafia-Koch) was developed to calculate the estimated total corneal astigmatism based on standard keratometry measurements. The error in the predicted residual astigmatism was calculated by the Alcon and Holladay toric IOL calculators with and without adjustments by the Abulafia-Koch formula. These results were compared with those of the Barrett toric calculator. Data from 78 eyes were evaluated to validate the Abulafia-Koch formula. The centroid errors in predicted residual astigmatism were against-the-rule with the Alcon (0.55 diopter [D]) and Holladay (0.54 D) toric calculators and decreased to 0.05 D (P < .001 [x-axis], P = .776 [y-axis]) and 0.04 D (P < .001 [x-axis], P = .726 [y-axis]) with adjustments by the Abulafia-Koch formula. The Alcon and the Holladay toric calculators had a higher proportion of eyes within ±0.50 D of the predicted residual astigmatism with the Abulafia-Koch formula (76.9% and 78.2%, respectively) than without it (both 30.8%). There were no significant differences between the results of the Abulafia-Koch-modified Alcon and the Holladay toric calculators and those of the Barrett toric calculator. Adjustment of commercial toric IOL calculators by the Abulafia-Koch formula significantly improved the prediction of postoperative astigmatic outcome. Dr. Abulafia received a speaker's fee from Haag-Streit AG. Dr. Barrett has licensed the Barrett Toric Calculator to Haag-Streit AG. Dr. Koch is a consultant to Alcon Laboratories, Inc., Abbott Medical Optics, Inc., and Revision Optics, Inc. Dr. Hill is a paid consultant to Haag-Streit AG and Alcon Laboratories, Inc. None of the other authors has a financial or proprietary interest in any material or method

  12. Climate variations and salmonellosis transmission in Adelaide, South Australia: a comparison between regression models

    NASA Astrophysics Data System (ADS)

    Zhang, Ying; Bi, Peng; Hiller, Janet

    2008-01-01

    This is the first study to identify appropriate regression models for the association between climate variation and salmonellosis transmission. A comparison between different regression models was conducted using surveillance data in Adelaide, South Australia. By using notified salmonellosis cases and climatic variables from the Adelaide metropolitan area over the period 1990-2003, four regression methods were examined: standard Poisson regression, autoregressive adjusted Poisson regression, multiple linear regression, and a seasonal autoregressive integrated moving average (SARIMA) model. Notified salmonellosis cases in 2004 were used to test the forecasting ability of the four models. Parameter estimation, goodness-of-fit and forecasting ability of the four regression models were compared. Temperatures occurring 2 weeks prior to cases were positively associated with cases of salmonellosis. Rainfall was also inversely related to the number of cases. The comparison of the goodness-of-fit and forecasting ability suggest that the SARIMA model is better than the other three regression models. Temperature and rainfall may be used as climatic predictors of salmonellosis cases in regions with climatic characteristics similar to those of Adelaide. The SARIMA model could, thus, be adopted to quantify the relationship between climate variations and salmonellosis transmission.

  13. A tutorial on the piecewise regression approach applied to bedload transport data

    Treesearch

    Sandra E. Ryan; Laurie S. Porth

    2007-01-01

    This tutorial demonstrates the application of piecewise regression to bedload data to define a shift in phase of transport so that the reader may perform similar analyses on available data. The use of piecewise regression analysis implicitly recognizes different functions fit to bedload data over varying ranges of flow. The transition from primarily low rates of sand...

  14. Regression: A Bibliography.

    ERIC Educational Resources Information Center

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  15. Social support, marital adjustment, and psychological distress among women with primary infertility in Pakistan.

    PubMed

    Qadir, Farah; Khalid, Amna; Medhin, Girmay

    2015-01-01

    This study aimed to identify prevalence rates of psychological distress among Pakistani women seeking help for primary infertility. The associations of social support, marital adjustment, and sociodemographic factors with psychological distress were also examined. A total of 177 women with primary infertility were interviewed from one hospital in Islamabad using a Self-Reporting Questionnaire, the Multidimensional Scale of Perceived Social Support, and the Locke-Wallace Marital Adjustment Test. The data were collected between November 2012 and March 2013. The prevalence of psychological distress was 37.3 percent. The results of the logistic regression suggested that marital adjustment and social support were significantly negatively associated with psychological distress in this sample. These associations were not confounded by any of the demographic variables controlled in the multivariable regression models. The role of perceived social support and adjustment in marriage among women experiencing primary infertility are important factors in understanding their psychological distress. The results of this small-scale effort highlight the need for social and familial awareness to help tackle the psychological distress related to infertility. Future research needs to focus on the way the experience of infertility is conditioned by social structural realities. New ways need to be developed to better take into account the process and nature of the infertility experience.

  16. Where's WALY? : A proof of concept study of the 'wellbeing adjusted life year' using secondary analysis of cross-sectional survey data.

    PubMed

    Johnson, Rebecca; Jenkinson, David; Stinton, Chris; Taylor-Phillips, Sian; Madan, Jason; Stewart-Brown, Sarah; Clarke, Aileen

    2016-09-08

    The Quality-Adjusted Life Year (QALY) is a measure that combines life extension and health improvement in a single score, reflecting preferences around different types of health gain. It can therefore be used to inform decision-making around allocation of health care resources to mutually exclusive options that would produce qualitatively different health benefits. A number of quality-of-life instruments can be used to calculate QALYs. The EQ-5D is one of the most commonly used, and is the preferred option for submissions to NICE ( https://www.nice.org.uk/process/pmg9/ ). However, it has limitations that might make it unsuitable for use in areas such as public and mental health where interventions may aim to improve well-being. One alternative to the QALY is a Wellbeing-Adjusted Life Year. In this study we explore the need for a Wellbeing-Adjusted Life Year measure by examining the extent to which a measure of wellbeing (the Warwick-Edinburgh Mental Well-being Scale) maps onto the EQ-5D-3L. Secondary analyses were conducted on data from the Coventry Household Survey in which 7469 participants completed the EQ-5D-3L, Warwick-Edinburgh Mental Well-being Scale, and a measure of self-rated health. Data were analysed using descriptive statistics, Pearson's and Spearman's correlations, linear regression, and receiver operating characteristic curves. Approximately 75 % of participants scored the maximum on the EQ-5D-3L. Those with maximum EQ-5D-3L scores reported a wide range of levels of mental wellbeing. Both the Warwick-Edinburgh Mental Well-being Scale and the EQ-5D-3L were able to detect differences between those with higher and lower levels of self-reported health. Linear regression indicated that scores on the Warwick-Edinburgh Mental Well-being Scale and the EQ-5D-3L were weakly, positively correlated (with R(2) being 0.104 for the index and 0.141 for the visual analogue scale). The Warwick-Edinburgh Mental Well-being Scale maps onto the EQ-5D-3L to only a

  17. Household water treatment in developing countries: comparing different intervention types using meta-regression.

    PubMed

    Hunter, Paul R

    2009-12-01

    Household water treatment (HWT) is being widely promoted as an appropriate intervention for reducing the burden of waterborne disease in poor communities in developing countries. A recent study has raised concerns about the effectiveness of HWT, in part because of concerns over the lack of blinding and in part because of considerable heterogeneity in the reported effectiveness of randomized controlled trials. This study set out to attempt to investigate the causes of this heterogeneity and so identify factors associated with good health gains. Studies identified in an earlier systematic review and meta-analysis were supplemented with more recently published randomized controlled trials. A total of 28 separate studies of randomized controlled trials of HWT with 39 intervention arms were included in the analysis. Heterogeneity was studied using the "metareg" command in Stata. Initial analyses with single candidate predictors were undertaken and all variables significant at the P < 0.2 level were included in a final regression model. Further analyses were done to estimate the effect of the interventions over time by MonteCarlo modeling using @Risk and the parameter estimates from the final regression model. The overall effect size of all unblinded studies was relative risk = 0.56 (95% confidence intervals 0.51-0.63), but after adjusting for bias due to lack of blinding the effect size was much lower (RR = 0.85, 95% CI = 0.76-0.97). Four main variables were significant predictors of effectiveness of intervention in a multipredictor meta regression model: Log duration of study follow-up (regression coefficient of log effect size = 0.186, standard error (SE) = 0.072), whether or not the study was blinded (coefficient 0.251, SE 0.066) and being conducted in an emergency setting (coefficient -0.351, SE 0.076) were all significant predictors of effect size in the final model. Compared to the ceramic filter all other interventions were much less effective (Biosand 0.247, 0

  18. Education as Experimentation: A Planned Variation Model. Volume IV-E. Supplementary Analyses: Reanalysis of Selected Data Sets. Volume IV-F. Supplementary Analyses: Appendix.

    ERIC Educational Resources Information Center

    Proper, Elizabeth C.; And Others

    This segment of the national evaluation study of the Follow Through Planned Variation Model discusses findings of analyses of achievement test data which have been adjusted to take into consideration the preschool experience of children in three Follow Through cohorts. These analyses serve as a supplement to analyses presented in Volume IV-A of…

  19. Relationship between negative mental adjustment to cancer and distress in thyroid cancer patients.

    PubMed

    Seok, Jeong-Ho; Choi, Won-Jung; Lee, Yong Sang; Park, Cheong Soo; Oh, Young-Ja; Kim, Jong-Sun; Chang, Hang-Seok

    2013-05-01

    Previous studies have reported that over a third of cancer patients experience significant psychological distress with diagnosis and treatment of cancer. Mental adjustment to cancer as well as other biologic and demographic factors may be associated with their distress. We investigated the relationship between mental adjustment and distress in patients with thyroid cancer prior to thyroidectomy. One hundred and fifty-two thyroid cancer patients were included in the final analysis. After global distress levels were screened with a distress thermometer, patients were evaluated concerning mental adjustment to cancer, as well as demographic and cancer-related characteristics. A thyroid function test was also performed. Regression analysis was performed to discern significant factors associated with distress in thyroid cancer patients. Our regression model was significant and explained 38.5% of the total variance in distress of this patient group. Anxious-preoccupation and helpless-hopeless factors on the mental adjustment to cancer scale were significantly associated with distress in thyroid cancer patients. Negative emotional response to cancer diagnosis may be associated with distress in thyroid cancer patients awaiting thyroidectomy. Screening of mental coping strategies at the beginning of cancer treatment may predict psychological distress in cancer patients. Further studies on the efficacy of psychiatric intervention during cancer treatment may be needed for patients showing maladaptive psychological responses to cancer.

  20. Generosity and adjusted premiums in job-based insurance: Hawaii is up, Wyoming is down.

    PubMed

    Gabel, Jon; McDevitt, Roland; Gandolfo, Laura; Pickreign, Jeremy; Hawkins, Samantha; Fahlman, Cheryl

    2006-01-01

    This paper reports national and state findings on the generosity or actuarial value of U.S. employer-based plans and adjusted premiums in 2002. The basis for our calculations is simulated bill paying for a large standardized population. After adjusting for the quality of benefits, we find from regression analysis that adjusted premiums are 18 percent higher in the nation's smallest firms than in firms with 1,000 or more workers. They are 25 percent higher in indemnity plans and 18 percent higher in preferred provider organizations than in health maintenance organizations. The generosity of coverage increased from 1997 to 2002.

  1. Spatial quantile regression using INLA with applications to childhood overweight in Malawi.

    PubMed

    Mtambo, Owen P L; Masangwi, Salule J; Kazembe, Lawrence N M

    2015-04-01

    Analyses of childhood overweight have mainly used mean regression. However, using quantile regression is more appropriate as it provides flexibility to analyse the determinants of overweight corresponding to quantiles of interest. The main objective of this study was to fit a Bayesian additive quantile regression model with structured spatial effects for childhood overweight in Malawi using the 2010 Malawi DHS data. Inference was fully Bayesian using R-INLA package. The significant determinants of childhood overweight ranged from socio-demographic factors such as type of residence to child and maternal factors such as child age and maternal BMI. We observed significant positive structured spatial effects on childhood overweight in some districts of Malawi. We recommended that the childhood malnutrition policy makers should consider timely interventions based on risk factors as identified in this paper including spatial targets of interventions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Advanced statistics: linear regression, part I: simple linear regression.

    PubMed

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  3. Risk adjustment and the fear of markets: the case of Belgium.

    PubMed

    Schokkaert, E; Van de Voorde, C

    2000-02-01

    In Belgium the management and administration of the compulsory and universal health insurance is left to a limited number of non-governmental non-profit sickness funds. Since 1995 these sickness funds are partially financed in a prospective way. The risk adjustment scheme is based on a regression model to explain medical expenditures for different social groups. Medical supply is taken out of the formula to construct risk-adjusted capitation payments. The risk-adjustment formula still leaves scope for risk selection. At the same time, the sickness funds were not given the instruments to exert a real influence on expenditures and the health insurance market has not been opened for new entrants. As a consequence, Belgium runs the danger of ending up in a situation with little incentives for efficiency and considerable profits from cream skimming.

  4. Geodesic least squares regression for scaling studies in magnetic confinement fusion

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

    Verdoolaege, Geert

    In regression analyses for deriving scaling laws that occur in various scientific disciplines, usually standard regression methods have been applied, of which ordinary least squares (OLS) is the most popular. However, concerns have been raised with respect to several assumptions underlying OLS in its application to scaling laws. We here discuss a new regression method that is robust in the presence of significant uncertainty on both the data and the regression model. The method, which we call geodesic least squares regression (GLS), is based on minimization of the Rao geodesic distance on a probabilistic manifold. We demonstrate the superiority ofmore » the method using synthetic data and we present an application to the scaling law for the power threshold for the transition to the high confinement regime in magnetic confinement fusion devices.« less

  5. Gender consistency and flexibility: using dynamics to understand the relationship between gender and adjustment.

    PubMed

    DiDonato, Matthew D; Martin, Carol L; Hessler, Eric E; Amazeen, Polemnia G; Hanish, Laura D; Fabes, Richard A

    2012-04-01

    Controversy surrounds questions regarding the influence of being gender consistent (i.e., having and expressing gendered characteristics that are consistent with one's biological sex) versus being gender flexible (i.e., having and expressing gendered characteristics that vary from masculine to feminine as circumstances arise) on children's adjustment outcomes, such as self-esteem, positive emotion, or behavior problems. Whereas evidence supporting the consistency hypothesis is abundant, little support exists for the flexibility hypothesis. To shed new light on the flexibility hypothesis, we explored children's gendered behavior from a dynamical perspective that highlighted variability and flexibility in addition to employing a conventional approach that emphasized stability and consistency. Conventional mean-level analyses supported the consistency hypothesis by revealing that gender atypical behavior was related to greater maladjustment, and dynamical analyses supported the flexibility hypothesis by showing that flexibility of gendered behavior over time was related to positive adjustment. Integrated analyses showed that gender typical behavior was related to the adjustment of children who were behaviorally inflexible, but not for those who were flexible. These results provided a more comprehensive understanding of the relation between gendered behavior and adjustment in young children and illustrated for the first time the feasibility of applying dynamical analyses to the study of gendered behavior.

  6. Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

    PubMed Central

    Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

    2012-01-01

    While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

  7. Tools to support interpreting multiple regression in the face of multicollinearity.

    PubMed

    Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

    2012-01-01

    While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

  8. Vascular disease, ESRD, and death: interpreting competing risk analyses.

    PubMed

    Grams, Morgan E; Coresh, Josef; Segev, Dorry L; Kucirka, Lauren M; Tighiouart, Hocine; Sarnak, Mark J

    2012-10-01

    Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989-1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20-2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15-2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors.

  9. Small-Sample Adjustments for Tests of Moderators and Model Fit in Robust Variance Estimation in Meta-Regression

    ERIC Educational Resources Information Center

    Tipton, Elizabeth; Pustejovsky, James E.

    2015-01-01

    Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…

  10. The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

    PubMed Central

    Murphy, Kevin; Birn, Rasmus M.; Handwerker, Daniel A.; Jones, Tyler B.; Bandettini, Peter A.

    2009-01-01

    Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step. PMID:18976716

  11. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

    PubMed

    Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

    2009-02-01

    Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

  12. Assessment of Weighted Quantile Sum Regression for Modeling Chemical Mixtures and Cancer Risk

    PubMed Central

    Czarnota, Jenna; Gennings, Chris; Wheeler, David C

    2015-01-01

    In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case–control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome. PMID:26005323

  13. Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk.

    PubMed

    Czarnota, Jenna; Gennings, Chris; Wheeler, David C

    2015-01-01

    In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case-control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome.

  14. Relationship between postural control and fine motor skills in preterm infants at 6 and 12 months adjusted age.

    PubMed

    Wang, Tien-Ni; Howe, Tsu-Hsin; Hinojosa, Jim; Weinberg, Sharon L

    2011-01-01

    We examined the relationship between postural control and fine motor skills of preterm infants at 6 and 12 mo adjusted age. The Alberta Infant Motor Scale was used to measure postural control, and the Peabody Developmental Motor Scales II was used to measure fine motor skills. The data analyzed were taken from 105 medical records from a preterm infant follow-up clinic at an urban academic medical center in south Taiwan. Using multiple regression analyses, we found that the development of postural control is related to the development of fine motor skills, especially in the group of preterm infants with delayed postural control. This finding supports the theoretical assumption of proximal-distal development used by many occupational therapists to guide intervention. Further research is suggested to corroborate findings.

  15. Time course for tail regression during metamorphosis of the ascidian Ciona intestinalis.

    PubMed

    Matsunobu, Shohei; Sasakura, Yasunori

    2015-09-01

    In most ascidians, the tadpole-like swimming larvae dramatically change their body-plans during metamorphosis and develop into sessile adults. The mechanisms of ascidian metamorphosis have been researched and debated for many years. Until now information on the detailed time course of the initiation and completion of each metamorphic event has not been described. One dramatic and important event in ascidian metamorphosis is tail regression, in which ascidian larvae lose their tails to adjust themselves to sessile life. In the present study, we measured the time associated with tail regression in the ascidian Ciona intestinalis. Larvae are thought to acquire competency for each metamorphic event in certain developmental periods. We show that the timing with which the competence for tail regression is acquired is determined by the time since hatching, and this timing is not affected by the timing of post-hatching events such as adhesion. Because larvae need to adhere to substrates with their papillae to induce tail regression, we measured the duration for which larvae need to remain adhered in order to initiate tail regression and the time needed for the tail to regress. Larvae acquire the ability to adhere to substrates before they acquire tail regression competence. We found that when larvae adhered before they acquired tail regression competence, they were able to remember the experience of adhesion until they acquired the ability to undergo tail regression. The time course of the events associated with tail regression provides a valuable reference, upon which the cellular and molecular mechanisms of ascidian metamorphosis can be elucidated. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Standardization and validation of the body weight adjustment regression equations in Olympic weightlifting.

    PubMed

    Kauhanen, Heikki; Komi, Paavo V; Häkkinen, Keijo

    2002-02-01

    The problems in comparing the performances of Olympic weightlifters arise from the fact that the relationship between body weight and weightlifting results is not linear. In the present study, this relationship was examined by using a nonparametric curve fitting technique of robust locally weighted regression (LOWESS) on relatively large data sets of the weightlifting results made in top international competitions. Power function formulas were derived from the fitted LOWESS values to represent the relationship between the 2 variables in a way that directly compares the snatch, clean-and-jerk, and total weightlifting results of a given athlete with those of the world-class weightlifters (golden standards). A residual analysis of several other parametric models derived from the initial results showed that they all experience inconsistencies, yielding either underestimation or overestimation of certain body weights. In addition, the existing handicapping formulas commonly used in normalizing the performances of Olympic weightlifters did not yield satisfactory results when applied to the present data. It was concluded that the devised formulas may provide objective means for the evaluation of the performances of male weightlifters, regardless of their body weights, ages, or performance levels.

  17. New Parents’ Psychological Adjustment and Trajectories of Early Parental Involvement

    PubMed Central

    Jia, Rongfang; Kotila, Letitia E.; Schoppe-Sullivan, Sarah J.; Kamp Dush, Claire M.

    2016-01-01

    Trajectories of parental involvement time (engagement and child care) across 3, 6, and 9 months postpartum and associations with parents’ own and their partners’ psychological adjustment (dysphoria, anxiety, and empathic personal distress) were examined using a sample of dual-earner couples experiencing first-time parenthood (N = 182 couples). Using time diary measures that captured intensive parenting moments, hierarchical linear modeling analyses revealed that patterns of associations between psychological adjustment and parental involvement time depended on the parenting domain, aspect of psychological adjustment, and parent gender. Psychological adjustment difficulties tended to bias the 2-parent system toward a gendered pattern of “mother step in” and “father step out,” as father involvement tended to decrease, and mother involvement either remained unchanged or increased, in response to their own and their partners’ psychological adjustment difficulties. In contrast, few significant effects were found in models using parental involvement to predict psychological adjustment. PMID:27397935

  18. Spatial regression analysis on 32 years of total column ozone data

    NASA Astrophysics Data System (ADS)

    Knibbe, J. S.; van der A, R. J.; de Laat, A. T. J.

    2014-08-01

    Multiple-regression analyses have been performed on 32 years of total ozone column data that was spatially gridded with a 1 × 1.5° resolution. The total ozone data consist of the MSR (Multi Sensor Reanalysis; 1979-2008) and 2 years of assimilated SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) ozone data (2009-2010). The two-dimensionality in this data set allows us to perform the regressions locally and investigate spatial patterns of regression coefficients and their explanatory power. Seasonal dependencies of ozone on regressors are included in the analysis. A new physically oriented model is developed to parameterize stratospheric ozone. Ozone variations on nonseasonal timescales are parameterized by explanatory variables describing the solar cycle, stratospheric aerosols, the quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO) and stratospheric alternative halogens which are parameterized by the effective equivalent stratospheric chlorine (EESC). For several explanatory variables, seasonally adjusted versions of these explanatory variables are constructed to account for the difference in their effect on ozone throughout the year. To account for seasonal variation in ozone, explanatory variables describing the polar vortex, geopotential height, potential vorticity and average day length are included. Results of this regression model are compared to that of a similar analysis based on a more commonly applied statistically oriented model. The physically oriented model provides spatial patterns in the regression results for each explanatory variable. The EESC has a significant depleting effect on ozone at mid- and high latitudes, the solar cycle affects ozone positively mostly in the Southern Hemisphere, stratospheric aerosols affect ozone negatively at high northern latitudes, the effect of QBO is positive and negative in the tropics and mid- to high latitudes, respectively, and ENSO affects ozone negatively

  19. Accounting for standard errors of vision-specific latent trait in regression models.

    PubMed

    Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L

    2014-07-11

    To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits

  20. Smokers' increased risk for disability pension: social confounding or health-mediated effects? Gender-specific analyses of the Hordaland Health Study cohort.

    PubMed

    Haukenes, Inger; Riise, Trond; Haug, Kjell; Farbu, Erlend; Maeland, John Gunnar

    2013-09-01

    Studies indicate that cigarette smokers have an increased risk for disability pension, presumably mediated by adverse health effects. However, smoking is also related to socioeconomic status. The current study examined the association between smoking and subsequent disability pension, and whether the association is explained by social confounding and/or health-related mediation. A subsample of 7934 men and 8488 women, aged 40-46, from the Hordaland Health Study, Norway (1997-1999), provided baseline information on smoking status, self-reported health measures and socioeconomic status. Outcome was register-based disability pension from 12 months after baseline to end of 2004. Gender stratified Cox regression analyses were used adjusted for socioeconomic status, physical activity, self-reported health and musculoskeletal pain sites. A total of 155 (2%) men and 333 (3.9%) women were granted disability pension during follow-up. The unadjusted disability risk associated with heavy smoking versus non-smoking was 1.88 (95% CI 1.23 to 2.89) among men and 3.06 (95% CI 2.23 to 4.20) among women. In multivariate analyses, adjusting for socioeconomic status, HRs were 1.33 (95% CI 0.84 to 2.11) among men and 2.22 (95% CI 1.58 to 3.13) among women. Final adjustment for physical activity, self-reported health and musculoskeletal pain further reduced the effect of heavy smoking in women (HR=1.53, 95% CI 1.09 to 2.16). Socioeconomic status confounded the smoking-related risk for disability pension; for female heavy smokers, however, a significant increased risk persisted after adjustment. Women may be particularly vulnerable to heavy smoking and to its sociomedical consequences, such as disability pension.

  1. Land use regression modeling of ultrafine particles, ozone, nitrogen oxides and markers of particulate matter pollution in Augsburg, Germany.

    PubMed

    Wolf, Kathrin; Cyrys, Josef; Harciníková, Tatiana; Gu, Jianwei; Kusch, Thomas; Hampel, Regina; Schneider, Alexandra; Peters, Annette

    2017-02-01

    Important health relevance has been suggested for ultrafine particles (UFP) and ozone, but studies on long-term effects are scarce, mainly due to the lack of appropriate spatial exposure models. We designed a measurement campaign to develop land use regression (LUR) models to predict the spatial variability focusing on particle number concentration (PNC) as indicator for UFP, ozone and several other air pollutants in the Augsburg region, Southern Germany. Three bi-weekly measurements of PNC, ozone, particulate matter (PM 10 , PM 2.5 ), soot (PM 2.5 abs) and nitrogen oxides (NO x , NO 2 ) were performed at 20 sites in 2014/15. Annual average concentration were calculated and temporally adjusted by measurements from a continuous background station. As geographic predictors we offered several traffic and land use variables, altitude, population and building density. Models were validated using leave-one-out cross-validation. Adjusted model explained variance (R 2 ) was high for PNC and ozone (0.89 and 0.88). Cross-validation adjusted R 2 was slightly lower (0.82 and 0.81) but still indicated a very good fit. LUR models for other pollutants performed well with adjusted R 2 between 0.68 (PM coarse ) and 0.94 (NO 2 ). Contrary to previous studies, ozone showed a moderate correlation with NO 2 (Pearson's r=-0.26). PNC was moderately correlated with ozone and PM 2.5 , but highly correlated with NO x (r=0.91). For PNC and NO x , LUR models comprised similar predictors and future epidemiological analyses evaluating health effects need to consider these similarities. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Examining the Components of Children's Peer Liking as Antecedents of School Adjustment

    ERIC Educational Resources Information Center

    Betts, Lucy R.; Rotenberg, Ken J.; Trueman, Mark; Stiller, James

    2012-01-01

    Children's social interactions with their peers influence their psychosocial adjustment; consequently, the relationship between class-wide peer liking, same-gender peer liking, and school adjustment was explored in two age groups. Peer liking was analysed using the social relations model (SRM). In Study 1, 205 children (103 female and 102 male,…

  3. Estimating the exceedance probability of rain rate by logistic regression

    NASA Technical Reports Server (NTRS)

    Chiu, Long S.; Kedem, Benjamin

    1990-01-01

    Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

  4. Evaluating differential effects using regression interactions and regression mixture models

    PubMed Central

    Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

    2015-01-01

    Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903

  5. Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

    PubMed

    Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

    2016-05-01

    Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

  6. Recurrent Dreams and Psychosocial Adjustment in Preteenaged Children

    PubMed Central

    Gauchat, Aline; Zadra, Antonio; Tremblay, Richard E.; Zelazo, Philip David; Séguin, Jean R.

    2014-01-01

    Research indicates that recurrent dreams in adults are associated with impoverished psychological well-being. Whether similar associations exist in children remains unknown. The authors hypothesized that children reporting recurrent dreams would show poorer psychosocial adjustment than children without recurrent dreams. One hundred sixty-eight 11-year-old children self-reported on their recurrent dreams and on measures of psychosocial adjustment. Although 35% of children reported having experienced a recurrent dream during the past year, our hypothesis was only partially supported. Multivariate analyses revealed a marginally significant interaction between gender and recurrent dream presence and a significant main effect of gender. Univariate analyses revealed that boys reporting recurrent dreams reported significantly higher scores on reactive aggression than those who did not (d = 0.58). This suggests that by age 11 years, the presence of recurrent dreams may already reflect underlying emotional difficulties in boys but not necessarily in girls. Challenges in addressing this developmental question are discussed. PMID:24976740

  7. Continuous Covariate Imbalance and Conditional Power for Clinical Trial Interim Analyses

    PubMed Central

    Ciolino, Jody D.; Martin, Renee' H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

    2014-01-01

    Oftentimes valid statistical analyses for clinical trials involve adjustment for known influential covariates, regardless of imbalance observed in these covariates at baseline across treatment groups. Thus, it must be the case that valid interim analyses also properly adjust for these covariates. There are situations, however, in which covariate adjustment is not possible, not planned, or simply carries less merit as it makes inferences less generalizable and less intuitive. In this case, covariate imbalance between treatment groups can have a substantial effect on both interim and final primary outcome analyses. This paper illustrates the effect of influential continuous baseline covariate imbalance on unadjusted conditional power (CP), and thus, on trial decisions based on futility stopping bounds. The robustness of the relationship is illustrated for normal, skewed, and bimodal continuous baseline covariates that are related to a normally distributed primary outcome. Results suggest that unadjusted CP calculations in the presence of influential covariate imbalance require careful interpretation and evaluation. PMID:24607294

  8. A review on the relationship between marital adjustment and maternal attachment.

    PubMed

    Mutlu, Birsen; Erkut, Zeynep; Yıldırım, Zeynem; Gündoğdu, Nurgül

    2018-03-01

    To determine the relationship between marital adjustment of mothers who have babies between 1-4 months old and their maternal attachment; as well as the relationship of maternal attachment and marital adjustment with sociodemographic characteristics. The research is descriptive and correlational. Its sample consists of 113 mothers. Maternal Attachment Index (MAI) and Marital Adjustment Scale (MAS) are used as data collection tools. We found that, for mothers who participated in this research, the average level of maternal attachment is 92.17 ± 8.49, and the average level of marital adjustment is 43.06 ± 7.90. We discovered that the maternal attachment level is higher for mothers who have completed high school and university, those who breastfeed their babies exclusively and whose spouses help care for the baby. We also discovered that the Marital Adjustment Score is higher among mothers who are employed, get married by companionship (not arranged), continue attending pregnancy classes and whose duration of marriage is between 1-5 years and 10-15 years. There is weak positive relationship (r=0.38; p=0.00) between marital adjustment and maternal attachment; and the regression analysis that is run to explain this relationship is statistically significant (F=26.131; p<0.05). In our study, the level of maternal attachment was high, while the level of marital adjustment was liminal. There are many factors affecting sociodemographic characteristics, pregnancy and baby care. The level of marital adjustment for mothers increases the maternal attachment.

  9. Mental health selection and income support dynamics: multiple spell discrete-time survival analyses of welfare receipt.

    PubMed

    Kiely, Kim M; Butterworth, Peter

    2014-04-01

    The higher occurrence of common psychiatric disorders among welfare recipients has been attributed to health selection, social causation and underlying vulnerability. The aims of this study were to test for the selection effects of mental health problems on entry and re-entry to working-age welfare payments in respect to single parenthood, unemployment and disability. Nationally representative longitudinal data were drawn from the Household Income and Labour Dynamics in Australia survey. Multiple spell discrete-time survival analyses were conducted using multinomial logistic regression models to test if pre-existing mental health problems predicted transitions to welfare. Analyses were stratified by sex and multivariate adjusted for mental health problems, father's occupation, socioeconomic position, marital status, employment history, smoking status and alcohol consumption, physical function and financial hardship. All covariates were modelled as either lagged effects or when a respondent was first observed to be at risk of income support. Mental health problems were associated with increased risk of entry and re-entry to disability, unemployment and single parenting payments for women, and disability and unemployment payments for men. These associations were attenuated but remained significant after adjusting for contemporaneous risk factors. Although we do not control for reciprocal causation, our findings are consistent with a health selection hypothesis and indicate that mental illness may be a contributing factor to later receipt of different types of welfare payments. We argue that mental health warrants consideration in the design and targeting of social and economic policies.

  10. Belgium: risk adjustment and financial responsibility in a centralised system.

    PubMed

    Schokkaert, Erik; Van de Voorde, Carine

    2003-07-01

    Since 1995 Belgian sickness funds are partially financed through a risk adjustment system and are held partially financially responsible for the difference between their actual and their risk-adjusted expenditures. However, they did not get the necessary instruments for exerting a real influence on expenditures and the health insurance market has not been opened for new entrants. At the same time the sickness funds have powerful tools for risk selection, because they also dominate the market for supplementary health insurance. The present risk-adjustment system is based on the results of a regression analysis with aggregate data. The main proclaimed purpose of this system is to guarantee a fair treatment to all the sickness funds. Until now the danger of risk selection has not been taken seriously. Consumer mobility has remained rather low. However, since the degree of financial responsibility is programmed to increase in the near future, the potential profits from cream skimming will increase.

  11. Long-term sickness absence due to adjustment disorder.

    PubMed

    Catalina-Romero, C; Pastrana-Jiménez, J I; Tenas-López, M J; Martínez-Muñoz, P; Ruiz-Moraga, M; Fernández-Labandera, C; Calvo-Bonacho, E

    2012-07-01

    Although adjustment disorder is frequently reported in clinical settings, scientific evidence is scarce regarding its impact on sickness absence and the variables associated with sickness absence duration. To report sickness absence duration and to identify predictors of long-term sickness absence in patients with adjustment disorder. This observational, prospective study included subjects with non-work-related sickness absence (>15 days) after a diagnosis of adjustment disorder. A stepwise logistic regression analysis was conducted to identify the best predictors of long-term sickness absence (≥ 6 months). There were 1182 subjects in the final analysis. The median duration of sickness absence due to adjustment disorder was 91 days. Twenty-two per cent of the subjects reported long-term sickness absence. After multivariate analysis, comorbidity (OR = 2.23, 95% CI 1.43-3.49), age (25-34 years old versus <25 years old: OR = 2.78, 95% CI 1.27-6.07; 35-44 years old versus <25 years old: OR = 3.70, 95% CI 1.71-7.99; 45-54 years old versus <25 years old: OR = 3.58, 95% CI 1.60-8.02; ≥ 55 years old versus <25 years old: OR = 6.35, 95% CI 2.64-15.31) and occupational level (blue collar versus white collar: OR = 1.52, 95% CI 1.10-2.09) remained significantly associated with long-term sickness absence. Comorbidity was the strongest predictor. It is possible to predict long-term sickness absence due to adjustment disorder on the basis of demographic, work-related and clinical information available during the basic assessment of the patient.

  12. Quasi-static shape adjustment of a 15 meter diameter space antenna

    NASA Technical Reports Server (NTRS)

    Belvin, W. Keith; Herstrom, Catherine L.; Edighoffer, Harold H.

    1987-01-01

    A 15 meter diameter Hoop-Column antenna has been analyzed and tested to study shape adjustment of the reflector surface. The Hoop-Column antenna concept employs pretensioned cables and mesh to produce a paraboloidal reflector surface. Fabrication errors and thermal distortions may significantly reduce surface accuracy and consequently degrade electromagnetic performance. Thus, the ability to adjust the surface shape is desirable. The shape adjustment algorithm consisted of finite element and least squares error analyses to minimize the surface distortions. Experimental results verified the analysis. Application of the procedure resulted in a reduction of surface error by 38 percent. Quasi-static shape adjustment has the potential for on-orbit compensation for a variety of surface shape distortions.

  13. Family Profiles of Cohesion and Parenting Practices and Latino Youth Adjustment.

    PubMed

    Bámaca-Colbert, Mayra Y; Gonzales-Backen, Melinda; Henry, Carolyn S; Kim, Peter S Y; Roblyer, Martha Zapata; Plunkett, Scott W; Sands, Tovah

    2017-08-10

    Using a sample of 279 (52% female) Latino youth in 9th grade (M = 14.57, SD = .56), we examined profiles of family cohesion and parenting practices and their relation to youth adjustment. The results of latent profile analyses revealed four family profiles: Engaged, Supportive, Intrusive, and Disengaged. Latino youth in the Supportive family profile showed most positive adjustment (highest self-esteem and lowest depressive symptoms), followed by youth in the Engaged family profile. Youth in the Intrusive and Disengaged profiles showed the lowest levels of positive adjustment. The findings contribute to the current literature on family dynamics, family profiles, and youth psychological adjustment within specific ethnic groups. © 2017 Family Process Institute.

  14. Prediction by regression and intrarange data scatter in surface-process studies

    USGS Publications Warehouse

    Toy, T.J.; Osterkamp, W.R.; Renard, K.G.

    1993-01-01

    Modeling is a major component of contemporary earth science, and regression analysis occupies a central position in the parameterization, calibration, and validation of geomorphic and hydrologic models. Although this methodology can be used in many ways, we are primarily concerned with the prediction of values for one variable from another variable. Examination of the literature reveals considerable inconsistency in the presentation of the results of regression analysis and the occurrence of patterns in the scatter of data points about the regression line. Both circumstances confound utilization and evaluation of the models. Statisticians are well aware of various problems associated with the use of regression analysis and offer improved practices; often, however, their guidelines are not followed. After a review of the aforementioned circumstances and until standard criteria for model evaluation become established, we recommend, as a minimum, inclusion of scatter diagrams, the standard error of the estimate, and sample size in reporting the results of regression analyses for most surface-process studies. ?? 1993 Springer-Verlag.

  15. Coffee intake, cardiovascular disease and all-cause mortality: observational and Mendelian randomization analyses in 95 000-223 000 individuals.

    PubMed

    Nordestgaard, Ask Tybjærg; Nordestgaard, Børge Grønne

    2016-12-01

    Coffee has been associated with modestly lower risk of cardiovascular disease and all-cause mortality in meta-analyses; however, it is unclear whether these are causal associations. We tested first whether coffee intake is associated with cardiovascular disease and all-cause mortality observationally; second, whether genetic variations previously associated with caffeine intake are associated with coffee intake; and third, whether the genetic variations are associated with cardiovascular disease and all-cause mortality. First, we used multivariable adjusted Cox proportional hazard regression models evaluated with restricted cubic splines to examine observational associations in 95 366 White Danes. Second, we estimated mean coffee intake according to five genetic variations near the AHR (rs4410790; rs6968865) and CYP1A1/2 genes (rs2470893; rs2472297; rs2472299). Third, we used sex- and age adjusted Cox proportional hazard regression models to examine genetic associations with cardiovascular disease and all-cause mortality in 112 509 Danes. Finally, we used sex and age-adjusted logistic regression models to examine genetic associations with ischaemic heart disease including the Cardiogram and C4D consortia in a total of up to 223 414 individuals. We applied similar analyses to ApoE genotypes associated with plasma cholesterol levels, as a positive control. In observational analyses, we observed U-shaped associations between coffee intake and cardiovascular disease and all-cause mortality; lowest risks were observed in individuals with medium coffee intake. Caffeine intake allele score (rs4410790 + rs2470893) was associated with a 42% higher coffee intake. Hazard ratios per caffeine intake allele were 1.02 (95% confidence interval: 1.00-1.03) for ischaemic heart disease, 1.02 (0.99-1.02) for ischaemic stroke, 1.02 (1.00-1.03) for ischaemic vascular disease, 1.02 (0.99-1.06) for cardiovascular mortality and 1.01 (0.99-1.03) for all-cause mortality. Including

  16. Geomorphic analyses from space imagery

    NASA Technical Reports Server (NTRS)

    Morisawa, M.

    1985-01-01

    One of the most obvious applications of space imagery to geomorphological analyses is in the study of drainage patterns and channel networks. LANDSAT, high altitude photography and other types of remote sensing imagery are excellent for depicting stream networks on a regional scale because of their broad coverage in a single image. They offer a valuable tool for comparing and analyzing drainage patterns and channel networks all over the world. Three aspects considered in this geomorphological study are: (1) the origin, evolution and rates of development of drainage systems; (2) the topological studies of network and channel arrangements; and (3) the adjustment of streams to tectonic events and geologic structure (i.e., the mode and rate of adjustment).

  17. 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.

  18. Vascular Disease, ESRD, and Death: Interpreting Competing Risk Analyses

    PubMed Central

    Coresh, Josef; Segev, Dorry L.; Kucirka, Lauren M.; Tighiouart, Hocine; Sarnak, Mark J.

    2012-01-01

    Summary Background and objectives Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. Design, setting, participants, & measurements This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989–1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. Results The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20–2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15–2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. Conclusions When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors. PMID:22859747

  19. Balancing Score Adjusted Targeted Minimum Loss-based Estimation

    PubMed Central

    Lendle, Samuel David; Fireman, Bruce; van der Laan, Mark J.

    2015-01-01

    Adjusting for a balancing score is sufficient for bias reduction when estimating causal effects including the average treatment effect and effect among the treated. Estimators that adjust for the propensity score in a nonparametric way, such as matching on an estimate of the propensity score, can be consistent when the estimated propensity score is not consistent for the true propensity score but converges to some other balancing score. We call this property the balancing score property, and discuss a class of estimators that have this property. We introduce a targeted minimum loss-based estimator (TMLE) for a treatment-specific mean with the balancing score property that is additionally locally efficient and doubly robust. We investigate the new estimator’s performance relative to other estimators, including another TMLE, a propensity score matching estimator, an inverse probability of treatment weighted estimator, and a regression-based estimator in simulation studies. PMID:26561539

  20. School-Based Racial and Gender Discrimination among African American Adolescents: Exploring Gender Variation in Frequency and Implications for Adjustment

    PubMed Central

    Chavous, Tabbye M.; Griffin, Tiffany M.

    2012-01-01

    The present study examined school-based racial and gender discrimination experiences among African American adolescents in Grade 8 (n = 204 girls; n = 209 boys). A primary goal was exploring gender variation in frequency of both types of discrimination and associations of discrimination with academic and psychological functioning among girls and boys. Girls and boys did not vary in reported racial discrimination frequency, but boys reported more gender discrimination experiences. Multiple regression analyses within gender groups indicated that among girls and boys, racial discrimination and gender discrimination predicted higher depressive symptoms and school importance and racial discrimination predicted self-esteem. Racial and gender discrimination were also negatively associated with grade point average among boys but were not significantly associated in girls’ analyses. Significant gender discrimination X racial discrimination interactions resulted in the girls’ models predicting psychological outcomes and in boys’ models predicting academic achievement. Taken together, findings suggest the importance of considering gender- and race-related experiences in understanding academic and psychological adjustment among African American adolescents. PMID:22837794

  1. A gigawatt level repetitive rate adjustable magnetic pulse compressor.

    PubMed

    Li, Song; Gao, Jing-Ming; Yang, Han-Wu; Qian, Bao-Liang; Li, Ze-Xin

    2015-08-01

    In this paper, a gigawatt level repetitive rate adjustable magnetic pulse compressor is investigated both numerically and experimentally. The device has advantages of high power level, high repetitive rate achievability, and long lifetime reliability. Importantly, dominate parameters including the saturation time, the peak voltage, and even the compression ratio can be potentially adjusted continuously and reliably, which significantly expands the applicable area of the device and generators based on it. Specifically, a two-stage adjustable magnetic pulse compressor, utilized for charging the pulse forming network of a high power pulse generator, is designed with different compression ratios of 25 and 18 through an optimized design process. Equivalent circuit analysis shows that the modification of compression ratio can be achieved by just changing the turn number of the winding. At the same time, increasing inductance of the grounded inductor will decrease the peak voltage and delay the charging process. Based on these analyses, an adjustable compressor was built and studied experimentally in both the single shot mode and repetitive rate mode. Pulses with peak voltage of 60 kV and energy per pulse of 360 J were obtained in the experiment. The rise times of the pulses were compressed from 25 μs to 1 μs and from 18 μs to 1 μs, respectively, at repetitive rate of 20 Hz with good repeatability. Experimental results show reasonable agreement with analyses.

  2. Gene regulatory network inference from multifactorial perturbation data using both regression and correlation analyses.

    PubMed

    Xiong, Jie; Zhou, Tong

    2012-01-01

    An important problem in systems biology is to reconstruct gene regulatory networks (GRNs) from experimental data and other a priori information. The DREAM project offers some types of experimental data, such as knockout data, knockdown data, time series data, etc. Among them, multifactorial perturbation data are easier and less expensive to obtain than other types of experimental data and are thus more common in practice. In this article, a new algorithm is presented for the inference of GRNs using the DREAM4 multifactorial perturbation data. The GRN inference problem among [Formula: see text] genes is decomposed into [Formula: see text] different regression problems. In each of the regression problems, the expression level of a target gene is predicted solely from the expression level of a potential regulation gene. For different potential regulation genes, different weights for a specific target gene are constructed by using the sum of squared residuals and the Pearson correlation coefficient. Then these weights are normalized to reflect effort differences of regulating distinct genes. By appropriately choosing the parameters of the power law, we constructe a 0-1 integer programming problem. By solving this problem, direct regulation genes for an arbitrary gene can be estimated. And, the normalized weight of a gene is modified, on the basis of the estimation results about the existence of direct regulations to it. These normalized and modified weights are used in queuing the possibility of the existence of a corresponding direct regulation. Computation results with the DREAM4 In Silico Size 100 Multifactorial subchallenge show that estimation performances of the suggested algorithm can even outperform the best team. Using the real data provided by the DREAM5 Network Inference Challenge, estimation performances can be ranked third. Furthermore, the high precision of the obtained most reliable predictions shows the suggested algorithm may be helpful in guiding

  3. Differential Adjustment Among Rural Adolescents Exposed to Family Violence

    PubMed Central

    Sianko, Natallia; Hedge, Jasmine M.; McDonell, James R.

    2016-01-01

    This study examines differences in psychological adjustment in a sample of rural adolescents who have been exposed to family violence. Self-report questionnaires were administered to 580 adolescents and their primary caregivers. The results revealed that over two thirds of the study participants (68.8%) had been exposed to violence in their families. As hypothesized, cluster analysis identified several profiles among adolescents, distinguished by their psychological and emotional functioning: well adjusted (46.2%), moderately adjusted (44.3%), and struggling (9.5%). Discriminant function analysis confirmed the groupings and revealed that family functioning was among the most influential factors explaining adjustment differences. Multivariate analyses of variance (MANOVAs) further showed that adolescents from each of the three adjustment profiles reported significantly different levels of family social support, parental involvement, and perceived neighborhood safety. Overall, the results confirm heterogeneity of adolescent adaptation in the aftermath of family violence and provide insights into family and neighborhood factors that account for variability in adolescents’ reactions to violence. Implications for future research and practical interventions are discussed. PMID:27106255

  4. Differential Adjustment Among Rural Adolescents Exposed to Family Violence.

    PubMed

    Sianko, Natallia; Hedge, Jasmine M; McDonell, James R

    2016-04-22

    This study examines differences in psychological adjustment in a sample of rural adolescents who have been exposed to family violence. Self-report questionnaires were administered to 580 adolescents and their primary caregivers. The results revealed that over two thirds of the study participants (68.8%) had been exposed to violence in their families. As hypothesized, cluster analysis identified several profiles among adolescents, distinguished by their psychological and emotional functioning: well adjusted (46.2%), moderately adjusted (44.3%), and struggling (9.5%). Discriminant function analysis confirmed the groupings and revealed that family functioning was among the most influential factors explaining adjustment differences. Multivariate analyses of variance (MANOVAs) further showed that adolescents from each of the three adjustment profiles reported significantly different levels of family social support, parental involvement, and perceived neighborhood safety. Overall, the results confirm heterogeneity of adolescent adaptation in the aftermath of family violence and provide insights into family and neighborhood factors that account for variability in adolescents' reactions to violence. Implications for future research and practical interventions are discussed. © The Author(s) 2016.

  5. Cumulative Socioeconomic Status Risk, Allostatic Load, and Adjustment: A Prospective Latent Profile Analysis With Contextual and Genetic Protective Factors

    PubMed Central

    Brody, Gene H.; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M.; Evans, Gary W.; Beach, Steven R. H.; Windle, Michael; Simons, Ronald L.; Gerrard, Meg; Gibbons, Frederick X.; Philibert, Robert A.

    2012-01-01

    The health disparities literature identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative SES risk. The current study was designed to test hypotheses about the developmental precursors to this pattern. Hypotheses were tested with a representative sample of 443 African American youths living in the rural South. Cumulative SES risk and protective processes were assessed at 11-13 years; psychological adjustment was assessed at ages 14-18 years; genotyping at the 5-HTTLPR was conducted at age 16 years; and allostatic load (AL) was assessed at age 19 years. A Latent Profile Analysis identified 5 profiles that evinced distinct patterns of SES risk, AL, and psychological adjustment, with 2 relatively large profiles designated as focal profiles: a physical health vulnerability profile characterized by high SES risk/high AL/low adjustment problems, and a resilient profile characterized by high SES risk/low AL/low adjustment problems. The physical health vulnerability profile mirrored the pattern found in the adult health disparities literature. Multinomial logistic regression analyses indicated that carrying an s allele at the 5-HTTLPR and receiving less peer support distinguished the physical health vulnerability profile from the resilient profile. Protective parenting and planful self-regulation distinguished both focal profiles from the other 3 profiles. The results suggest the public health importance of preventive interventions that enhance coping and reduce the effects of stress across childhood and adolescence. PMID:22709130

  6. Cumulative socioeconomic status risk, allostatic load, and adjustment: a prospective latent profile analysis with contextual and genetic protective factors.

    PubMed

    Brody, Gene H; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M; Evans, Gary W; Beach, Steven R H; Windle, Michael; Simons, Ronald L; Gerrard, Meg; Gibbons, Frederick X; Philibert, Robert A

    2013-05-01

    The health disparities literature has identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative socioeconomic status (SES) risk. The current study was designed to test hypotheses about the developmental precursors to this pattern. Hypotheses were tested with a representative sample of 443 African American youths living in the rural South. Cumulative SES risk and protective processes were assessed at ages 11-13 years; psychological adjustment was assessed at ages 14-18 years; genotyping at the 5-HTTLPR was conducted at age 16 years; and allostatic load (AL) was assessed at age 19 years. A latent profile analysis identified 5 profiles that evinced distinct patterns of SES risk, AL, and psychological adjustment, with 2 relatively large profiles designated as focal profiles: a physical health vulnerability profile characterized by high SES risk/high AL/low adjustment problems, and a resilient profile characterized by high SES risk/low AL/low adjustment problems. The physical health vulnerability profile mirrored the pattern found in the adult health disparities literature. Multinomial logistic regression analyses indicated that carrying an s allele at the 5-HTTLPR and receiving less peer support distinguished the physical health vulnerability profile from the resilient profile. Protective parenting and planful self-regulation distinguished both focal profiles from the other 3 profiles. The results suggest the public health importance of preventive interventions that enhance coping and reduce the effects of stress across childhood and adolescence.

  7. Body mass index adjustments to increase the validity of body fatness assessment in UK Black African and South Asian children.

    PubMed

    Hudda, M T; Nightingale, C M; Donin, A S; Fewtrell, M S; Haroun, D; Lum, S; Williams, J E; Owen, C G; Rudnicka, A R; Wells, J C K; Cook, D G; Whincup, P H

    2017-07-01

    Body mass index (BMI) (weight per height 2 ) is the most widely used marker of childhood obesity and total body fatness (BF). However, its validity is limited, especially in children of South Asian and Black African origins. We aimed to quantify BMI adjustments needed for UK children of Black African and South Asian origins so that adjusted BMI related to BF in the same way as for White European children. We used data from four recent UK studies that made deuterium dilution BF measurements in UK children of White European, South Asian and Black African origins. A height-standardized fat mass index (FMI) was derived to represent BF. Linear regression models were then fitted, separately for boys and girls, to quantify ethnic differences in BMI-FMI relationships and to provide ethnic-specific BMI adjustments. We restricted analyses to 4-12 year olds, to whom a single consistent FMI (fat mass per height 5 ) could be applied. BMI consistently underestimated BF in South Asians, requiring positive BMI adjustments of +1.12 kg m - 2 (95% confidence interval (CI): 0.83, 1.41 kg m - 2 ; P<0.0001) for boys and +1.07 kg m - 2 (95% CI: 0.74, 1.39 kg m - 2 ; P<0.0001) for girls of all age groups and FMI levels. BMI overestimated BF in Black Africans, requiring negative BMI adjustments for Black African children. However, these were complex because there were statistically significant interactions between Black African ethnicity and FMI (P=0.004 boys; P=0.003 girls) and also between FMI and age group (P<0.0001 for boys and girls). BMI adjustments therefore varied by age group and FMI level (and indirectly BMI); the largest adjustments were in younger children with higher unadjusted BMI and the smallest in older children with lower unadjusted BMI. BMI underestimated BF in South Asians and overestimated BF in Black Africans. Ethnic-specific adjustments, increasing BMI in South Asians and reducing BMI in Black Africans, can improve the accuracy of BF assessment in

  8. The perspective of prostate cancer patients and patients' partners on the psychological burden of androgen deprivation and the dyadic adjustment of prostate cancer couples.

    PubMed

    Hamilton, Lisa Dawn; Van Dam, Dexter; Wassersug, Richard J

    2016-07-01

    Prostate cancer and its treatments, particularly androgen deprivation therapy (ADT), affect both patients and partners. This study assessed how prostate cancer treatment type, patient mood, and sexual function related to dyadic adjustment from patient and partner perspectives. Men with prostate cancer (n = 206) and partners of men with prostate cancer (n = 66) completed an online survey assessing the patients' mood (profile of mood states short form), their dyadic adjustment (dyadic adjustment scale), and sexual function (expanded prostate cancer index composite). Analyses of covariance found that men on ADT reported better dyadic adjustment compared with men not on ADT. Erectile dysfunction was high for all patients, but a multivariate analysis of variance found that those on ADT experienced greater bother at loss of sexual function than patients not on ADT, suggesting that loss of libido when on ADT does not mitigate the psychological distress associated with loss of erections. In a multiple linear regression, patients' mood predicted their dyadic adjustment, such that worse mood was related to worse dyadic adjustment. However, more bother with patients' overall sexual function predicted lower relationship scores for the patients, while the patients' lack of sexual desire predicted lower dyadic adjustment for partners. Both patients and partners are impacted by the prostate cancer treatment effects on patients' psychological and sexual function. Our data help clarify the way that prostate cancer treatments can affect relationships and that loss of libido on ADT does not attenuate distress about erectile dysfunction. Understanding these changes may help patients and partners maintain a co-supportive relationship. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  9. Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

    PubMed

    Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

    2017-03-05

    The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized

  10. A risk-adjusted financial model to estimate the cost of a video-assisted thoracoscopic surgery lobectomy programme.

    PubMed

    Brunelli, Alessandro; Tentzeris, Vasileios; Sandri, Alberto; McKenna, Alexandra; Liew, Shan Liung; Milton, Richard; Chaudhuri, Nilanjan; Kefaloyannis, Emmanuel; Papagiannopoulos, Kostas

    2016-05-01

    To develop a clinically risk-adjusted financial model to estimate the cost associated with a video-assisted thoracoscopic surgery (VATS) lobectomy programme. Prospectively collected data of 236 VATS lobectomy patients (August 2012-December 2013) were analysed retrospectively. Fixed and variable intraoperative and postoperative costs were retrieved from the Hospital Accounting Department. Baseline and surgical variables were tested for a possible association with total cost using a multivariable linear regression and bootstrap analyses. Costs were calculated in GBP and expressed in Euros (EUR:GBP exchange rate 1.4). The average total cost of a VATS lobectomy was €11 368 (range €6992-€62 535). Average intraoperative (including surgical and anaesthetic time, overhead, disposable materials) and postoperative costs [including ward stay, high dependency unit (HDU) or intensive care unit (ICU) and variable costs associated with management of complications] were €8226 (range €5656-€13 296) and €3029 (range €529-€51 970), respectively. The following variables remained reliably associated with total costs after linear regression analysis and bootstrap: carbon monoxide lung diffusion capacity (DLCO) <60% predicted value (P = 0.02, bootstrap 63%) and chronic obstructive pulmonary disease (COPD; P = 0.035, bootstrap 57%). The following model was developed to estimate the total costs: 10 523 + 1894 × COPD + 2376 × DLCO < 60%. The comparison between predicted and observed costs was repeated in 1000 bootstrapped samples to verify the stability of the model. The two values were not different (P > 0.05) in 86% of the samples. A hypothetical patient with COPD and DLCO less than 60% would cost €4270 more than a patient without COPD and with higher DLCO values (€14 793 vs €10 523). Risk-adjusting financial data can help estimate the total cost associated with VATS lobectomy based on clinical factors. This model can be used to audit the internal financial

  11. A comparative study of adjustable and non-adjustable sutures in primary horizontal muscle surgery in children

    PubMed Central

    Kamal, A M; Abozeid, D; Seif, Y; Hassan, M

    2016-01-01

    Purpose To compare the results of using adjustable and non-adjustable sutures in primary horizontal strabismus surgeries in children. Methods This randomized control trial included 60 cases of primary horizontal deviation. The adjustable suture (AS) group included 30 patients, and the non-adjustable suture (NAS) group included 30 patients. The follow-up period was at least 6 months. A successful motor outcome was defined as orthophoria or a horizontal tropia of 8 PD or less at both near and far distances. The success rate and ocular drift were recorded and analysed. Results The mean age in the AS group was 3.48±2.37 years at the time of surgery. The mean age in the NAS group was 3.55±2.64 years at the time of surgery. The success rate at the end of 6 months was 86.67% in the AS group and 73.33% in the NAS group (P=0.197). In exotropic patients, there was a mean undercorrection drift of 2.86 PD in the AS group and a mean undercorrection drift of 2.17 PD in the NAS group. In esotropic patients, there was a mean undercorrection drift of 0.26 PD in the AS group and a mean undercorrection drift of 1.83 PD in the NAS group. Conclusion There was no significant difference between the groups. However, the success rate was clinically higher in the AS group than in the NAS group. PMID:27419838

  12. Nonlinear Theory of The Geostrophic Adjustment

    NASA Astrophysics Data System (ADS)

    Zeitlin, V.

    Nonlinear geostrophic adjustment and splitting of the fast and slow dynamical vari- ables are analysed in the framework of multi-layer and continuously stratified prim- itive equations by means of the multi-scale perturbation theory in the Rossby num- ber applied to localized initial disturbances. Two basic dynamical regimes: the quasi- geostrophic (QG) and the frontal geostrophic (FG) with small and large deviations of the isopycnal surfaces, respectively, are considered and differences in corresponding adjustment scenarios are displayed. Decoupling of the fast component of the flow is proven up to the third order in Rossby number and long-time corrections to the stan- dard balanced QG and FG models are found. Peculiarities of splitting in the FG regime due to the quasi-inertial oscillations are displayed and a Schrodinger-like modulation equations for the envelope of these latter are derived.

  13. State infant mortality: an ecologic study to determine modifiable risks and adjusted infant mortality rates.

    PubMed

    Paul, David A; Mackley, Amy; Locke, Robert G; Stefano, John L; Kroelinger, Charlan

    2009-05-01

    To determine factors contributing to state infant mortality rates (IMR) and develop an adjusted IMR in the United States for 2001 and 2002. Ecologic study of factors contributing to state IMR. State IMR for 2001 and 2002 were obtained from the United States linked death and birth certificate data from the National Center for Health Statistics. Factors investigated using multivariable linear regression included state racial demographics, ethnicity, state population, median income, education, teen birth rate, proportion of obesity, smoking during pregnancy, diabetes, hypertension, cesarean delivery, prenatal care, health insurance, self-report of mental illness, and number of in-vitro fertilization procedures. Final risk adjusted IMR's were standardized and states were compared with the United States adjusted rates. Models for IMR in individual states in 2001 (r2 = 0.66, P < 0.01) and 2002 (r2 = 0.81, P < 0.01) were tested. African-American race, teen birth rate, and smoking during pregnancy remained independently associated with state infant mortality rates for 2001 and 2002. Ninety five percent confidence intervals (CI) were calculated around the regression lines to model the expected IMR. After adjustment, some states maintained a consistent IMR; for instance, Vermont and New Hampshire remained low, while Delaware and Louisiana remained high. However, other states such as Mississippi, which have traditionally high infant mortality rates, remained within the expected 95% CI for IMR after adjustment indicating confounding affected the initial unadjusted rates. Non-modifiable demographic variables, including the percentage of non-Hispanic African-American and Hispanic populations of the state are major factors contributing to individual variation in state IMR. Race and ethnicity may confound or modify the IMR in states that shifted inside or outside the 95% CI following adjustment. Other factors including smoking during pregnancy and teen birth rate, which are

  14. Association between regression and self injury among children with autism.

    PubMed

    Lance, Eboni I; York, Janet M; Lee, Li-Ching; Zimmerman, Andrew W

    2014-02-01

    Self injurious behaviors (SIBs) are challenging clinical problems in individuals with autism spectrum disorders (ASDs). This study is one of the first and largest to utilize inpatient data to examine the associations between autism, developmental regression, and SIBs. Medical records of 125 neurobehavioral hospitalized patients with diagnoses of ASDs and SIBs between 4 and 17 years of age were reviewed. Data were collected from medical records on the type and frequency of SIBs and a history of language, social, or behavioral regression during development. The children with a history of any type of developmental regression (social, behavioral, or language) were more likely to have a diagnosis of autistic disorder than other ASD diagnoses. There were no significant differences in the occurrence of self injurious or other problem behaviors (such as aggression or disruption) between children with and without regression. Regression may influence the diagnostic considerations in ASDs but does not seem to influence the clinical phenotype with regard to behavioral issues. Additional data analyses explored the frequencies and subtypes of SIBs and other medical diagnoses in ASDs, with intellectual disability and disruptive behavior disorder found most commonly. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. A method for fitting regression splines with varying polynomial order in the linear mixed model.

    PubMed

    Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

    2006-02-15

    The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

  16. On the Importance of Age-Adjustment Methods in Ecological Studies of Social Determinants of Mortality

    PubMed Central

    Milyo, Jeffrey; Mellor, Jennifer M

    2003-01-01

    Objective To illustrate the potential sensitivity of ecological associations between mortality and certain socioeconomic factors to different methods of age-adjustment. Data Sources Secondary analysis employing state-level data from several publicly available sources. Crude and age-adjusted mortality rates for 1990 are obtained from the U.S. Centers for Disease Control. The Gini coefficient for family income and percent of persons below the federal poverty line are from the U.S. Bureau of Labor Statistics. Putnam's (2000) Social Capital Index was downloaded from ; the Social Mistrust Index was calculated from responses to the General Social Survey, following the method described in Kawachi et al. (1997). All other covariates are obtained from the U.S. Census Bureau. Study Design We use least squares regression to estimate the effect of several state-level socioeconomic factors on mortality rates. We examine whether these statistical associations are sensitive to the use of alternative methods of accounting for the different age composition of state populations. Following several previous studies, we present results for the case when only mortality rates are age-adjusted. We contrast these results with those obtained from regressions of crude mortality on age variables. Principal Findings Different age-adjustment methods can cause a change in the sign or statistical significance of the association between mortality and various socioeconomic factors. When age variables are included as regressors, we find no significant association between mortality and either income inequality, minority racial concentration, or social capital. Conclusions Ecological associations between certain socioeconomic factors and mortality may be extremely sensitive to different age-adjustment methods. PMID:14727797

  17. A methodological approach to identify external factors for indicator-based risk adjustment illustrated by a cataract surgery register

    PubMed Central

    2014-01-01

    Background Risk adjustment is crucial for comparison of outcome in medical care. Knowledge of the external factors that impact measured outcome but that cannot be influenced by the physician is a prerequisite for this adjustment. To date, a universal and reproducible method for identification of the relevant external factors has not been published. The selection of external factors in current quality assurance programmes is mainly based on expert opinion. We propose and demonstrate a methodology for identification of external factors requiring risk adjustment of outcome indicators and we apply it to a cataract surgery register. Methods Defined test criteria to determine the relevance for risk adjustment are “clinical relevance” and “statistical significance”. Clinical relevance of the association is presumed when observed success rates of the indicator in the presence and absence of the external factor exceed a pre-specified range of 10%. Statistical significance of the association between the external factor and outcome indicators is assessed by univariate stratification and multivariate logistic regression adjustment. The cataract surgery register was set up as part of a German multi-centre register trial for out-patient cataract surgery in three high-volume surgical sites. A total of 14,924 patient follow-ups have been documented since 2005. Eight external factors potentially relevant for risk adjustment were related to the outcome indicators “refractive accuracy” and “visual rehabilitation” 2–5 weeks after surgery. Results The clinical relevance criterion confirmed 2 (“refractive accuracy”) and 5 (“visual rehabilitation”) external factors. The significance criterion was verified in two ways. Univariate and multivariate analyses revealed almost identical external factors: 4 were related to “refractive accuracy” and 7 (6) to “visual rehabilitation”. Two (“refractive accuracy”) and 5 (“visual rehabilitation”) factors

  18. Indirect medical education and disproportionate share adjustments to Medicare inpatient payment rates.

    PubMed

    Nguyen, Nguyen Xuan; Sheingold, Steven H

    2011-11-04

    The indirect medical education (IME) and disproportionate share hospital (DSH) adjustments to Medicare's prospective payment rates for inpatient services are generally intended to compensate hospitals for patient care costs related to teaching activities and care of low income populations. These adjustments were originally established based on the statistical relationships between IME and DSH and hospital costs. Due to a variety of policy considerations, the legislated levels of these adjustments may have deviated over time from these "empirically justified levels," or simply, "empirical levels." In this paper, we estimate the empirical levels of IME and DSH using 2006 hospital data and 2009 Medicare final payment rules. Our analyses suggest that the empirical level for IME would be much smaller than under current law-about one-third to one-half. Our analyses also support the DSH adjustment prescribed by the Affordable Care Act of 2010 (ACA)--about one-quarter of the pre-ACA level. For IME, the estimates imply an increase in costs of 1.88% for each 10% increase in teaching intensity. For DSH, the estimates imply that costs would rise by 0.52% for each 10% increase in the low-income patient share for large urban hospitals. Public Domain.

  19. Transcriptome-wide analyses indicate mitochondrial responses to particulate air pollution exposure.

    PubMed

    Winckelmans, Ellen; Nawrot, Tim S; Tsamou, Maria; Den Hond, Elly; Baeyens, Willy; Kleinjans, Jos; Lefebvre, Wouter; Van Larebeke, Nicolas; Peusens, Martien; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Vanpoucke, Charlotte; de Kok, Theo M; Vrijens, Karen

    2017-08-18

    Due to their lack of repair capacity mitochondria are critical targets for environmental toxicants. We studied genes and pathways reflecting mitochondrial responses to short- and medium-term PM 10 exposure. Whole genome gene expression was measured in peripheral blood of 98 adults (49% women). We performed linear regression analyses stratified by sex and adjusted for individual and temporal characteristics to investigate alterations in gene expression induced by short-term (week before blood sampling) and medium-term (month before blood sampling) PM 10 exposure. Overrepresentation analyses (ConsensusPathDB) were performed to identify enriched mitochondrial associated pathways and gene ontology sets. Thirteen Human MitoCarta genes were measured by means of quantitative real-time polymerase chain reaction (qPCR) along with mitochondrial DNA (mtDNA) content in an independent validation cohort (n = 169, 55.6% women). Overrepresentation analyses revealed significant pathways (p-value <0.05) related to mitochondrial genome maintenance and apoptosis for short-term exposure and to the electron transport chain (ETC) for medium-term exposure in women. For men, medium-term PM 10 exposure was associated with the Tri Carbonic Acid cycle. In an independent study population, we validated several ETC genes, including UQCRH and COX7C (q-value <0.05), and some genes crucial for the maintenance of the mitochondrial genome, including LONP1 (q-value: 0.07) and POLG (q-value: 0.04) in women. In this exploratory study, we identified mitochondrial genes and pathways associated with particulate air pollution indicating upregulation of energy producing pathways as a potential mechanism to compensate for PM-induced mitochondrial damage.

  20. The Unified Levelling Network of Sarawak and its Adjustment

    NASA Astrophysics Data System (ADS)

    Som, Z. A. M.; Yazid, A. M.; Ming, T. K.; Yazid, N. M.

    2016-09-01

    The height reference network of Sarawak has seen major improvement in over the past two decades. The most significant improvement was the establishment of extended precise leveling network of which is now able to connect all three major datum points at Pulau Lakei, Original and Bintulu. Datum by following the major accessible routes across Sarawak. This means the leveling network in Sarawak has now been inter-connected and unified. By having such a unified network leads to the possibility of having a common single least squares adjustment been performed for the first time. The least squares adjustment of this unified levelling network was attempted in order to compute the height of all Bench Marks established in the entire levelling network. The adjustment was done by using MoreFix levelling adjustment package developed at FGHT UTM. The computational procedure adopted is linear parametric adjustment by minimum constraint. Since Sarawak has three separate datums therefore three separate adjustments were implemented by utilizing datum at Pulau Lakei, Original Miri and Bintulu Datum respectively. Results of the MoreFix unified adjustment agreed very well with adjustment repeated using Starnet. Further the results were compared with solution given by Jupem and they are in good agreement as well. The difference in height analysed were within 10mm for the case of minimum constraint at Pulau Lakei datum and with much better agreement in the case of Original Miri Datum.

  1. Regression Verification Using Impact Summaries

    NASA Technical Reports Server (NTRS)

    Backes, John; Person, Suzette J.; Rungta, Neha; Thachuk, Oksana

    2013-01-01

    versions [19]. These techniques compare two programs with a large degree of syntactic similarity to prove that portions of one program version are equivalent to the other. Regression verification can be used for guaranteeing backward compatibility, and for showing behavioral equivalence in programs with syntactic differences, e.g., when a program is refactored to improve its performance, maintainability, or readability. Existing regression verification techniques leverage similarities between program versions by using abstraction and decomposition techniques to improve scalability of the analysis [10, 12, 19]. The abstractions and decomposition in the these techniques, e.g., summaries of unchanged code [12] or semantically equivalent methods [19], compute an over-approximation of the program behaviors. The equivalence checking results of these techniques are sound but not complete-they may characterize programs as not functionally equivalent when, in fact, they are equivalent. In this work we describe a novel approach that leverages the impact of the differences between two programs for scaling regression verification. We partition program behaviors of each version into (a) behaviors impacted by the changes and (b) behaviors not impacted (unimpacted) by the changes. Only the impacted program behaviors are used during equivalence checking. We then prove that checking equivalence of the impacted program behaviors is equivalent to checking equivalence of all program behaviors for a given depth bound. In this work we use symbolic execution to generate the program behaviors and leverage control- and data-dependence information to facilitate the partitioning of program behaviors. The impacted program behaviors are termed as impact summaries. The dependence analyses that facilitate the generation of the impact summaries, we believe, could be used in conjunction with other abstraction and decomposition based approaches, [10, 12], as a complementary reduction technique. An

  2. Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

    PubMed

    Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

    2017-01-01

    The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

  3. Adjustment Disorders as a Stress-Related Disorder: A Longitudinal Study of the Associations among Stress, Resources, and Mental Health

    PubMed Central

    Kocalevent, Rüya-Daniela; Mierke, Annett; Danzer, Gerhard; Klapp, Burghard F.

    2014-01-01

    Objective Adjustment disorders are re-conceptualized in the DSM-5 as a stress-related disorder; however, besides the impact of an identifiable stressor, the specification of a stress concept, remains unclear. This study is the first to examine an existing stress-model from the general population, in patients diagnosed with adjustment disorders, using a longitudinal design. Methods The study sample consisted of 108 patients consecutively admitted for adjustment disorders. Associations of stress perception, emotional distress, resources, and mental health were measured at three time points: the outpatients’ presentation, admission for inpatient treatment, and discharge from the hospital. To evaluate a longitudinal stress model of ADs, we examined whether stress at admission predicted mental health at each of the three time points using multiple linear regressions and structural equation modeling. A series of repeated-measures one-way analyses of variance (rANOVAs) was performed to assess change over time. Results Significant within-participant changes from baseline were observed between hospital admission and discharge with regard to mental health, stress perception, and emotional distress (p<0.001). Stress perception explained nearly half of the total variance (44%) of mental health at baseline; the adjusted R2 increased (0.48), taking emotional distress (i.e., depressive symptoms) into account. The best predictor of mental health at discharge was the level of emotional distress (i.e., anxiety level) at baseline (β = −0.23, R2 corr = 0.56, p<0.001). With a CFI of 0.86 and an NFI of 0.86, the fit indices did not allow for acceptance of the stress-model (Cmin/df = 15.26; RMSEA = 0.21). Conclusions Stress perception is an important predictor in adjustment disorders, and mental health-related treatment goals are dependent on and significantly impacted by stress perception and emotional distress. PMID:24825165

  4. Advanced statistics: linear regression, part II: multiple linear regression.

    PubMed

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  5. Effortful control and school adjustment: The moderating role of classroom chaos.

    PubMed

    Berger, Rebecca H; Valiente, Carlos; Eisenberg, Nancy; Hernandez, Maciel M; Thompson, Marilyn; Spinrad, Tracy; VanSchyndel, Sarah; Silva, Kassondra; Southworth, Jody

    2017-11-01

    Guided by the person by environment framework, the primary goal of this study was to determine whether classroom chaos moderated the relation between effortful control and kindergarteners' school adjustment. Classroom observers reported on children's ( N = 301) effortful control in the fall. In the spring, teachers reported on classroom chaos and school adjustment outcomes (teacher-student relationship closeness and conflict, and school liking and avoidance). Cross-level interactions between effortful control and classroom chaos predicting school adjustment outcomes were assessed. A consistent pattern of interactions between effortful control and classroom chaos indicated that the relations between effortful control and the school adjustment outcomes were strongest in high chaos classrooms. Post-hoc analyses indicated that classroom chaos was associated with poor school adjustment when effortful control was low, suggesting that the combination of high chaos and low effortful control was associated with the poorest school outcomes.

  6. Regression equations for calculation of z scores for echocardiographic measurements of left heart structures in healthy Han Chinese children.

    PubMed

    Wang, Shan-Shan; Hong, Wen-Jing; Zhang, Yu-Qi; Chen, Shu-Bao; Huang, Guo-Ying; Zhang, Hong-Yan; Chen, Li-Jun; Wu, Lan-Ping; Shen, Rong; Liu, Yi-Qing; Zhu, Jun-Xue

    2018-06-01

    Clinical decision making in children with heart disease relies on detailed measurements of cardiac structures using two-dimensional and M-mode echocardiography. However, no echocardiographic reference values are available for the Chinese children. We aimed to establish z-score regression equations for left heart structures in a population-based cohort of healthy Chinese Han children. Echocardiography was performed in 545 children with a normal heart. The dimensions of the aortic valve annulus (AVA), aortic sinuses of Valsalva (ASV), sinotubular junction (STJ), ascending aorta (AAO), left atrium (LA), mitral valve annulus (MVA), interventricular septal end-diastolic thickness (IVSd), interventricular septal end-systolic thickness (IVSs), left ventricular end-diastolic diameter (LVIDd), left ventricular end-systolic diameter (LVIDs), left ventricular posterior wall end-diastolic thickness (LVPWd), left ventricular posterior wall end-systolic thickness (LVPWs) were measured. Regression analyses were conducted to relate the measurements of left heart structures to body surface area (BSA). Left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were calculated. Several models were used, and the adjusted R2 values were compared for each model. AVA, ASV, STJ, AAO, LA, MVA, IVSd, IVSs, LVIDd, LVIDs, LVPWd, and LVPWs had a cubic relationship with BSA. LVEF and LVFS fell within a narrow range. Our results provide reference values for z scores and regression equations for left heart structures in Han Chinese children. These data may help make a quick and accurate judgment of the routine clinical measurement of left heart structures in children with heart disease. © 2018 Wiley Periodicals, Inc.

  7. A Comparison between the Use of Beta Weights and Structure Coefficients in Interpreting Regression Results

    ERIC Educational Resources Information Center

    Tong, Fuhui

    2006-01-01

    Background: An extensive body of researches has favored the use of regression over other parametric analyses that are based on OVA. In case of noteworthy regression results, researchers tend to explore magnitude of beta weights for the respective predictors. Purpose: The purpose of this paper is to examine both beta weights and structure…

  8. Age, Acculturation, Cultural Adjustment, and Mental Health Symptoms of Chinese, Korean, and Japanese Immigrant Youths.

    ERIC Educational Resources Information Center

    Yeh, Christine J.

    2003-01-01

    This study of Japanese, Chinese, and Korean immigrant junior high and high school students investigated the association between age, acculturation, cultural adjustment difficulties, and general mental health concerns. Analyses determined that age, acculturation, and cultural adjustment difficulties had significant predictive effects on mental…

  9. A SURVEY OF DEATH ADJUSTMENT IN THE INDIAN SUBCONTINENT.

    PubMed

    Hossain, Mohammad Samir; Irfan, Muhammad; Balhara, Yatan Pal Singh; Giasuddin, Noor Ahmed; Sultana, Syeda Naheed

    2015-01-01

    The Death Adjustment Hypothesis (DAH) postulates two key themes. Its first part postulates that death should not be considered the end of existence and the second part emphasizes that the belief in immortal pattern of human existence can only be adopted in a morally rich life with the attitude towards morality and materialism balanced mutually. We wanted to explore Death Adjustment in the Indian subcontinent and the differences among, Indians, Pakistanis and Bangladeshis. We also wanted to find the relationship between death adjustment (i.e., adaptation to death), materialistic thoughts and death adjustment thoughts. This was a cross-sectional study, conducted from May 2010 to June 2013. Using a purposive sampling strategy, a sample of 296 participants from the Indian subcontinent [Pakistan (n=100), Bangladesh (n=98) and India (n=98)] was selected. Multidimensional Fear of Death Scale (MFODS) was used to measure death adjustment. The rest of the variables were measured using lists of respective thoughts, described in elaborated DAH. Analyses were carried out using SPSSv13. The mean death adjustment score for Pakistani, Indian and Bangaldeshi population were 115.26 +/- 26.4, 125.87 +/- 24.3 and 114.91 +/- 21.2, respectively. Death adjustment was better with older age (r=0.20) and with lower scores on materialistic thoughts (r = -0.26). However, this was a weak relation. The three nationalities were compared with each other by using Analysis of variance. Death adjustment thoughts and death adjustment were significantly different when Indians were compared with Bangladeshis (p=0.00) and Pakistanis (p=0.006) but comparison between Bangladeshis and Pakistanis showed no significant difference. Subjects with lesser materialistic thoughts showed better death adjustment. There are differences between Muslims and non-Muslims in adjusting to death.

  10. Weighing Evidence "Steampunk" Style via the Meta-Analyser.

    PubMed

    Bowden, Jack; Jackson, Chris

    2016-10-01

    The funnel plot is a graphical visualization of summary data estimates from a meta-analysis, and is a useful tool for detecting departures from the standard modeling assumptions. Although perhaps not widely appreciated, a simple extension of the funnel plot can help to facilitate an intuitive interpretation of the mathematics underlying a meta-analysis at a more fundamental level, by equating it to determining the center of mass of a physical system. We used this analogy to explain the concepts of weighing evidence and of biased evidence to a young audience at the Cambridge Science Festival, without recourse to precise definitions or statistical formulas and with a little help from Sherlock Holmes! Following on from the science fair, we have developed an interactive web-application (named the Meta-Analyser) to bring these ideas to a wider audience. We envisage that our application will be a useful tool for researchers when interpreting their data. First, to facilitate a simple understanding of fixed and random effects modeling approaches; second, to assess the importance of outliers; and third, to show the impact of adjusting for small study bias. This final aim is realized by introducing a novel graphical interpretation of the well-known method of Egger regression.

  11. Adjustment of QT dispersion assessed from 12 lead electrocardiograms for different numbers of analysed electrocardiographic leads: comparison of stability of different methods.

    PubMed Central

    Hnatkova, K; Malik, M; Kautzner, J; Gang, Y; Camm, A J

    1994-01-01

    OBJECTIVE--Normal electrocardiographic recordings were analysed to establish the influence of measurement of different numbers of electrocardiographic leads on the results of different formulas expressing QT dispersion and the effects of adjustment of QT dispersion obtained from a subset of an electrocardiogram to approximate to the true QT dispersion obtained from a complete electrocardiogram. SUBJECTS AND METHODS--Resting 12 lead electrocardiograms of 27 healthy people were investigated. In each lead, the QT interval was measured with a digitising board and QT dispersion was evaluated by three formulas: (A) the difference between the longest and the shortest QT interval among all leads; (B) the difference between the second longest and the second shortest QT interval; (C) SD of QT intervals in different leads. For each formula, the "true" dispersion was assessed from all measurable leads and then different combinations of leads were omitted. The mean relative differences between the QT dispersion with a given number of omitted leads and the "true" QT dispersion (mean relative errors) and the coefficients of variance of the results of QT dispersion obtained when omitting combinations of leads were compared for the different formulas. The procedure was repeated with an adjustment of each formula dividing its results by the square root of the number of measured leads. The same approach was used for the measurement of QT dispersion from the chest leads including a fourth formula (D) the SD of interlead differences weighted according to the distances between leads. For different formulas, the mean relative errors caused by omitting individual electrocardiographic leads were also assessed and the importance of individual leads for correct measurement of QT dispersion was investigated. RESULTS--The study found important differences between different formulas for assessment of QT dispersion with respect to compensation for missing measurements of QT interval. The

  12. Light-adjustable lens.

    PubMed Central

    Schwartz, Daniel M

    2003-01-01

    PURPOSE: First, to determine whether a silicone light-adjustable intraocular lens (IOL) can be fabricated and adjusted precisely with a light delivery device (LDD). Second, to determine the biocompatibility of an adjustable IOL and whether the lens can be adjusted precisely in vivo. METHODS: After fabrication of a light-adjustable silicone formulation, IOLs were made and tested in vitro for cytotoxicity, leaching, precision of adjustment, optical quality after adjustment, and mechanical properties. Light-adjustable IOLs were then tested in vivo for biocompatibility and precision of adjustment in a rabbit model. In collaboration with Zeiss-Meditec, a digital LDD was developed and tested to correct for higher-order aberrations in light-adjustable IOLs. RESULTS: The results establish that a biocompatible silicone IOL can be fabricated and adjusted using safe levels of light. There was no evidence of cytotoxicity or leaching. Testing of mechanical properties revealed no significant differences from commercial controls. Implantation of light-adjustable lenses in rabbits demonstrated- excellent biocompatibility after 6 months, comparable to a commercially available IOL. In vivo spherical (hyperopic and myopic) adjustment in rabbits was achieved using an analog light delivery system. The digital light delivery system was tested and achieved correction of higher-order aberrations. CONCLUSION: A silicone light-adjustable IOL and LDD have been developed to enable postoperative, noninvasive adjustment of lens power. The ability to correct higher-order aberrations in these materials has broad potential applicability for optimization of vision in patients undergoing cataract and refractive surgery. PMID:14971588

  13. Accounting for estimated IQ in neuropsychological test performance with regression-based techniques.

    PubMed

    Testa, S Marc; Winicki, Jessica M; Pearlson, Godfrey D; Gordon, Barry; Schretlen, David J

    2009-11-01

    Regression-based normative techniques account for variability in test performance associated with multiple predictor variables and generate expected scores based on algebraic equations. Using this approach, we show that estimated IQ, based on oral word reading, accounts for 1-9% of the variability beyond that explained by individual differences in age, sex, race, and years of education for most cognitive measures. These results confirm that adding estimated "premorbid" IQ to demographic predictors in multiple regression models can incrementally improve the accuracy with which regression-based norms (RBNs) benchmark expected neuropsychological test performance in healthy adults. It remains to be seen whether the incremental variance in test performance explained by estimated "premorbid" IQ translates to improved diagnostic accuracy in patient samples. We describe these methods, and illustrate the step-by-step application of RBNs with two cases. We also discuss the rationale, assumptions, and caveats of this approach. More broadly, we note that adjusting test scores for age and other characteristics might actually decrease the accuracy with which test performance predicts absolute criteria, such as the ability to drive or live independently.

  14. Regression Discontinuity for Causal Effect Estimation in Epidemiology.

    PubMed

    Oldenburg, Catherine E; Moscoe, Ellen; Bärnighausen, Till

    Regression discontinuity analyses can generate estimates of the causal effects of an exposure when a continuously measured variable is used to assign the exposure to individuals based on a threshold rule. Individuals just above the threshold are expected to be similar in their distribution of measured and unmeasured baseline covariates to individuals just below the threshold, resulting in exchangeability. At the threshold exchangeability is guaranteed if there is random variation in the continuous assignment variable, e.g., due to random measurement error. Under exchangeability, causal effects can be identified at the threshold. The regression discontinuity intention-to-treat (RD-ITT) effect on an outcome can be estimated as the difference in the outcome between individuals just above (or below) versus just below (or above) the threshold. This effect is analogous to the ITT effect in a randomized controlled trial. Instrumental variable methods can be used to estimate the effect of exposure itself utilizing the threshold as the instrument. We review the recent epidemiologic literature reporting regression discontinuity studies and find that while regression discontinuity designs are beginning to be utilized in a variety of applications in epidemiology, they are still relatively rare, and analytic and reporting practices vary. Regression discontinuity has the potential to greatly contribute to the evidence base in epidemiology, in particular on the real-life and long-term effects and side-effects of medical treatments that are provided based on threshold rules - such as treatments for low birth weight, hypertension or diabetes.

  15. Ecologic regression analysis and the study of the influence of air quality on mortality.

    PubMed Central

    Selvin, S; Merrill, D; Wong, L; Sacks, S T

    1984-01-01

    This presentation focuses entirely on the use and evaluation of regression analysis applied to ecologic data as a method to study the effects of ambient air pollution on mortality rates. Using extensive national data on mortality, air quality and socio-economic status regression analyses are used to study the influence of air quality on mortality. The analytic methods and data are selected in such a way that direct comparisons can be made with other ecologic regression studies of mortality and air quality. Analyses are performed by use of two types of geographic areas, age-specific mortality of both males and females and three pollutants (total suspended particulates, sulfur dioxide and nitrogen dioxide). The overall results indicate no persuasive evidence exists of a link between air quality and general mortality levels. Additionally, a lack of consistency between the present results and previous published work is noted. Overall, it is concluded that linear regression analysis applied to nationally collected ecologic data cannot be used to usefully infer a causal relationship between air quality and mortality which is in direct contradiction to other major published studies. PMID:6734568

  16. Logistic Regression Likelihood Ratio Test Analysis for Detecting Signals of Adverse Events in Post-market Safety Surveillance.

    PubMed

    Nam, Kijoeng; Henderson, Nicholas C; Rohan, Patricia; Woo, Emily Jane; Russek-Cohen, Estelle

    2017-01-01

    The Vaccine Adverse Event Reporting System (VAERS) and other product surveillance systems compile reports of product-associated adverse events (AEs), and these reports may include a wide range of information including age, gender, and concomitant vaccines. Controlling for possible confounding variables such as these is an important task when utilizing surveillance systems to monitor post-market product safety. A common method for handling possible confounders is to compare observed product-AE combinations with adjusted baseline frequencies where the adjustments are made by stratifying on observable characteristics. Though approaches such as these have proven to be useful, in this article we propose a more flexible logistic regression approach which allows for covariates of all types rather than relying solely on stratification. Indeed, a main advantage of our approach is that the general regression framework provides flexibility to incorporate additional information such as demographic factors and concomitant vaccines. As part of our covariate-adjusted method, we outline a procedure for signal detection that accounts for multiple comparisons and controls the overall Type 1 error rate. To demonstrate the effectiveness of our approach, we illustrate our method with an example involving febrile convulsion, and we further evaluate its performance in a series of simulation studies.

  17. The Role of Natural Support Systems in the Post-deployment Adjustment of Active Duty Military Personnel.

    PubMed

    Welsh, Janet A; Olson, Jonathan; Perkins, Daniel F; Travis, Wendy J; Ormsby, LaJuana

    2015-09-01

    This study examined the relations among three different types of naturally occurring social support (from romantic partners, friends and neighbors, and unit leaders) and three indices of service member well-being (self reports of depressive symptoms, satisfaction with military life, and perceptions of unit readiness) for service members who did and did not report negative experiences associated with military deployment. Data were drawn from the 2011 Community Assessment completed anonymously by more than 63,000 USAF personnel. Regression analyses revealed that higher levels of social support was associated with better outcomes regardless of negative deployment experiences. Evidence of moderation was also noted, with all forms of social support moderating the impact of negative deployment experiences on depressive symptoms and support from unit leaders moderating the impact of negative deployment experience on satisfaction with military life. No moderation was found for perceptions of unit readiness. Subgroup analyses revealed slightly different patterns for male and female service members, with support providing fewer moderation effects for women. These findings may have value for military leaders and mental health professionals working to harness the power of naturally occurring relationships to maximize the positive adjustment of service members and their families. Implications for practices related to re-integration of post-deployment military personnel are discussed.

  18. The effects of physiological adjustments on the perceptual and acoustical characteristics of simulated laryngeal vocal tremor

    PubMed Central

    Lester, Rosemary A.; Story, Brad H.

    2015-01-01

    The purpose of this study was to determine if adjustments to the voice source [i.e., fundamental frequency (F0), degree of vocal fold adduction] or vocal tract filter (i.e., vocal tract shape for vowels) reduce the perception of simulated laryngeal vocal tremor and to determine if listener perception could be explained by characteristics of the acoustical modulations. This research was carried out using a computational model of speech production that allowed for precise control and manipulation of the glottal and vocal tract configurations. Forty-two healthy adults participated in a perceptual study involving pair-comparisons of the magnitude of “shakiness” with simulated samples of laryngeal vocal tremor. Results revealed that listeners perceived a higher magnitude of voice modulation when simulated samples had a higher mean F0, greater degree of vocal fold adduction, and vocal tract shape for /i/ vs /ɑ/. However, the effect of F0 was significant only when glottal noise was not present in the acoustic signal. Acoustical analyses were performed with the simulated samples to determine the features that affected listeners' judgments. Based on regression analyses, listeners' judgments were predicted to some extent by modulation information present in both low and high frequency bands. PMID:26328711

  19. The role of premorbid adjustment in schizophrenia: Focus on cognitive remediation outcome.

    PubMed

    Buonocore, Mariachiara; Bosinelli, Francesca; Bechi, Margherita; Spangaro, Marco; Piantanida, Marco; Cocchi, Federica; Bianchi, Laura; Guglielmino, Carmelo; Mastromatteo, Antonella Rita; Cavallaro, Roberto; Bosia, Marta

    2018-02-19

    Premorbid adjustment has been associated with several outcomes in schizophrenia and has been proposed as an index of cognitive reserve. This study aims to comprehensively analyse the relation between premorbid adjustment and clinical, neurocognitive, socio-cognitive and functional assessments, as well as to investigate the effect of premorbid adjustment on cognitive improvements after a cognitive remediation therapy protocol. Seventy-nine clinically stabilised outpatients with schizophrenia underwent a combined intervention consisting of cognitive remediation therapy added to standard rehabilitation therapy. All patients were assessed at baseline for psychopathology, premorbid adjustment, intellectual level, cognition and functioning. Cognitive evaluations were also repeated after the intervention. At baseline, significant correlations were observed between premorbid adjustment and working memory. The global cognitive improvement after treatment was significantly predicted by age and premorbid adjustment. This study confirms the association between premorbid adjustment and cognitive impairment and is the first to highlight the possible role of premorbid adjustment on the capacity to recover from cognitive deficits through a cognitive remediation therapy protocol. The data suggest that cognitive remediation may be particularly effective for people in the early course and that the assessment of premorbid adjustment could be of value to design individualised interventions.

  20. Risk-adjusted hospital outcomes for children's surgery.

    PubMed

    Saito, Jacqueline M; Chen, Li Ern; Hall, Bruce L; Kraemer, Kari; Barnhart, Douglas C; Byrd, Claudia; Cohen, Mark E; Fei, Chunyuan; Heiss, Kurt F; Huffman, Kristopher; Ko, Clifford Y; Latus, Melissa; Meara, John G; Oldham, Keith T; Raval, Mehul V; Richards, Karen E; Shah, Rahul K; Sutton, Laura C; Vinocur, Charles D; Moss, R Lawrence

    2013-09-01

    BACKGROUND The American College of Surgeons National Surgical Quality Improvement Program-Pediatric was initiated in 2008 to drive quality improvement in children's surgery. Low mortality and morbidity in previous analyses limited differentiation of hospital performance. Participating institutions included children's units within general hospitals and free-standing children's hospitals. Cases selected by Current Procedural Terminology codes encompassed procedures within pediatric general, otolaryngologic, orthopedic, urologic, plastic, neurologic, thoracic, and gynecologic surgery. Trained personnel abstracted demographic, surgical profile, preoperative, intraoperative, and postoperative variables. Incorporating procedure-specific risk, hierarchical models for 30-day mortality and morbidities were developed with significant predictors identified by stepwise logistic regression. Reliability was estimated to assess the balance of information versus error within models. In 2011, 46 281 patients from 43 hospitals were accrued; 1467 codes were aggregated into 226 groupings. Overall mortality was 0.3%, composite morbidity 5.8%, and surgical site infection (SSI) 1.8%. Hierarchical models revealed outlier hospitals with above or below expected performance for composite morbidity in the entire cohort, pediatric abdominal subgroup, and spine subgroup; SSI in the entire cohort and pediatric abdominal subgroup; and urinary tract infection in the entire cohort. Based on reliability estimates, mortality discriminates performance poorly due to very low event rate; however, reliable model construction for composite morbidity and SSI that differentiate institutions is feasible. The National Surgical Quality Improvement Program-Pediatric expansion has yielded risk-adjusted models to differentiate hospital performance in composite and specific morbidities. However, mortality has low utility as a children's surgery performance indicator. Programmatic improvements have resulted in

  1. Application of artificial neural network to fMRI regression analysis.

    PubMed

    Misaki, Masaya; Miyauchi, Satoru

    2006-01-15

    We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

  2. Public health vulnerability to wintertime weather: time-series regression and episode analyses of national mortality and morbidity databases to inform the Cold Weather Plan for England.

    PubMed

    Hajat, S; Chalabi, Z; Wilkinson, P; Erens, B; Jones, L; Mays, N

    2016-08-01

    To inform development of Public Health England's Cold Weather Plan (CWP) by characterizing pre-existing relationships between wintertime weather and mortality and morbidity outcomes, and identification of groups most at risk. Time-series regression analysis and episode analysis of daily mortality, emergency hospital admissions, and accident and emergency visits for each region of England. Seasonally-adjusted Poisson regression models estimating the percent change in daily health events per 1 °C fall in temperature or during individual episodes of extreme weather. Adverse cold effects were observed in all regions, with the North East, North West and London having the greatest risk of cold-related mortality. Nationally, there was a 3.44% (95% CI: 3.01, 3.87) increase in all-cause deaths and 0.78% (95% CI: 0.53, 1.04) increase in all-cause emergency admissions for every 1 °C drop in temperature below identified thresholds. The very elderly and people with COPD were most at risk from low temperatures. A&E visits for fractures were elevated during heavy snowfall periods, with adults (16-64 years) being the most sensitive age-group. Since even moderately cold days are associated with adverse health effects, by far the greatest health burdens of cold weather fell outside of the alert periods currently used in the CWP. Our findings indicate that levels 0 ('year round planning') and 1 ('winter preparedness and action') are crucial components of the CWP in comparison to the alerts. Those most vulnerable during winter may vary depending on the type of weather conditions being experienced. Recommendations are made for the CWP. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  3. Unmitigated agency, social support, and psychological adjustment in men with cancer.

    PubMed

    Hoyt, Michael A; Stanton, Annette L

    2011-04-01

    Unmitigated agency (UA), a gender-linked characteristic, has been associated with poorer cancer adjustment. Support from one's social network typically predicts adjustment but may be poorly matched to UA. The influence of UA on the utility of social support on adjustment over time is examined. Men with cancer (N=55) were assessed initially and 6 months later on three indicators of adjustment. Multilevel modeling analyses varied by adjustment indicator. UA was associated with increased cancer-related psychosocial symptoms but not depressive symptoms or cancer-related thought intrusion. Social support predicted fewer depressive symptoms and less cancer-related thought intrusion. However, a cross-level interaction revealed that the utility of social support on cancer-related thought intrusion was weaker for men with greater levels of UA. Men with cancer likely respond differently to changes in social support depending on their endorsement of UA. © 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.

  4. Structural vascular disease in Africans: Performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: The SABPA study.

    PubMed

    Botha, J; de Ridder, J H; Potgieter, J C; Steyn, H S; Malan, L

    2013-10-01

    A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fasting bloods (glucose, high density lipoprotein (HDL) and triglycerides) were obtained in a well-controlled setting. The RPWC male model (LR ROC AUC: 0.71, NN ROC AUC: 0.71) was practically equal to the JSC model (LR ROC AUC: 0.71, NN ROC AUC: 0.69) to predict structural vascular -disease. Similarly, the female RPWC model (LR ROC AUC: 0.84, NN ROC AUC: 0.82) and JSC model (LR ROC AUC: 0.82, NN ROC AUC: 0.81) equally predicted CIMT as surrogate marker for structural vascular disease. Odds ratios supported validity where prediction of CIMT revealed -clinical -significance, well over 1, for both the JSC and RPWC models in African males and females (OR 3.75-13.98). In conclusion, the proposed RPWC model was substantially validated utilizing linear and non-linear analyses. We therefore propose ethnic-specific WC cut points (African males, ≥90 cm; -females, ≥98 cm) to predict a surrogate marker for structural vascular disease. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

  5. Adult attachment, hostile conflict, and relationship adjustment among couples facing multiple sclerosis.

    PubMed

    Crangle, Cassandra J; Hart, Tae L

    2017-11-01

    Couples facing multiple sclerosis (MS) report significantly elevated rates of relationship distress, yet the effects of attachment have never been examined in this population. We examined whether hostile conflict mediated the dyadic effects of attachment on relationship adjustment in couples facing MS and whether these associations were moderated by gender or role. We also explored whether dyadic adjustment mediated the relationship between attachment and hostile conflict. The study was cross-sectional and included 103 couples in which one partner had been diagnosed with MS. Participants completed the Experiences in Close Relationships-Revised, Dyadic Adjustment Scale, and Aversive Interactions Scale, as well as demographic variables. We used the actor-partner interdependence model for data analysis. There were significant actor and partner effects of greater anxious attachment and worse dyadic adjustment. Actor and partner effects of anxious attachment were significantly mediated by greater hostile conflict. Gender significantly moderated the effects between avoidant attachment and dyadic adjustment. The actor effect was significant for males and females; the partner effect was only significant for females. The actor effect for females but not males was significantly mediated by greater hostile conflict. Role was not a significant moderator. Exploratory analyses also showed that dyadic adjustment mediated the relationship between anxious and avoidant attachment and hostile conflict. Findings highlight the important effects of attachment on relationship adjustment in MS couples. Both hostile conflict and dyadic adjustment appear to be mechanisms through which insecure attachment has a detrimental effect. Statement of contribution What is already known on this subject? Despite higher-than-normal rates of marital distress and separation/divorce, the effects of attachment on relationship adjustment among couples facing multiple sclerosis have never been examined

  6. Perceived social support and psychosocial adjustment in patients with coronary heart disease.

    PubMed

    Karataş, Tuğba; Bostanoğlu, Hatice

    2017-08-01

    This study was performed to assess perceived social support and psychosocial adjustment in patients with coronary heart disease. Participants were 250 patients referred to the cardiology outpatient clinic of a university hospital in Ankara, Turkey, between December 2013 and March 2014. Data were collected using a participant information form, the Multidimensional Scale of Perceived Social Support, and the Psychosocial Adjustment to Illness Scale-Self-Report. Data were analysed using frequencies, percentages, mean scores, and Pearson's correlation coefficient. Patients' mean perceived social support scores were relatively low and patients' mean scores for psychosocial adjustment considered to be poor. Subgroups in the psychosocial adjustment and social support scales were significantly associated. This study's results indicate that patients' social support is linked to their psychosocial adjustment to coronary heart disease. As psychosocial adjustment is inhibited in patients who lack sufficient social support, sources of social support of patients should be identified and facilitated. © 2017 John Wiley & Sons Australia, Ltd.

  7. Risk Adjustment and Primary Health Care in Chile

    PubMed Central

    Vargas, Veronica; Wasem, Juergen

    2006-01-01

    Aim To offer a capitation formula with greater capacity for guiding resource spending on population with poorer health and lower socioeconomic status in the context of financing and equity in primary health care. Methods We collected two years of data on a sample of 10 000 individuals from a region in Chile, Valdivia and Temuco and evaluated three models to estimate utilization and expenditures per capita. The first model included age and sex; the second one included age, sex, and the presence of two key diagnoses; and the third model included age, sex, and the presence of seven key diagnoses. Regression results were evaluated by R2 and predictive ratios to select the best specifications. Results Per-capita expenditures by age and sex confirmed international trends, where children under five, women, and the elderly were the main users of primary health care services. Women sought health advice twice as much as men. Clear differences by socioeconomic status were observed for the indigent population aged ≥65 years who under-utilized primary health care services. From the three models, major improvement in the predictive power occurred from the demographic (adjusted R2, 9%) to the demographic plus two diagnoses model (adjusted R2, 27%). Improvements were modest when five other diagnoses were added (adjusted R2, 28%). Conclusion The current formula that uses municipality’s financial power and geographic location of health centers to adjust capitation payments provides little incentive to appropriate care for the indigent and people with chronic conditions. A capitation payment that adjusts for age, sex, and the presence of diabetes and hypertension will better guide resource allocation to those with poorer health and lower socioeconomic status. PMID:16758525

  8. Lipid Adjustment for Chemical Exposures: Accounting for Concomitant Variables

    PubMed Central

    Li, Daniel; Longnecker, Matthew P.; Dunson, David B.

    2013-01-01

    Background Some environmental chemical exposures are lipophilic and need to be adjusted by serum lipid levels before data analyses. There are currently various strategies that attempt to account for this problem, but all have their drawbacks. To address such concerns, we propose a new method that uses Box-Cox transformations and a simple Bayesian hierarchical model to adjust for lipophilic chemical exposures. Methods We compared our Box-Cox method to existing methods. We ran simulation studies in which increasing levels of lipid-adjusted chemical exposure did and did not increase the odds of having a disease, and we looked at both single-exposure and multiple-exposures cases. We also analyzed an epidemiology dataset that examined the effects of various chemical exposures on the risk of birth defects. Results Compared with existing methods, our Box-Cox method produced unbiased estimates, good coverage, similar power, and lower type-I error rates. This was the case in both single- and multiple-exposure simulation studies. Results from analysis of the birth-defect data differed from results using existing methods. Conclusion Our Box-Cox method is a novel and intuitive way to account for the lipophilic nature of certain chemical exposures. It addresses some of the problems with existing methods, is easily extendable to multiple exposures, and can be used in any analyses that involve concomitant variables. PMID:24051893

  9. Low Reporting Quality of the Meta-Analyses in Diagnostic Pathology.

    PubMed

    Liu, Xulei; Kinzler, Michael; Yuan, Jiangfan; He, Guozhong; Zhang, Lanjing

    2017-03-01

    - Little is known regarding the reporting quality of meta-analyses in diagnostic pathology. - To compare reporting quality of meta-analyses in diagnostic pathology and medicine and to examine factors associated with reporting quality of diagnostic pathology meta-analyses. - Meta-analyses were identified in 12 major diagnostic pathology journals without specifying years and 4 major medicine journals in 2006 and 2011 using PubMed. Reporting quality of meta-analyses was evaluated using the 27-item checklist of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement published in 2009. A higher PRISMA score indicates higher reporting quality. - Forty-one diagnostic pathology meta-analyses and 118 medicine meta-analyses were included. Overall, reporting quality of meta-analyses in diagnostic pathology was lower than that in medicine (median [interquartile range] = 22 [15, 25] versus 27 [23, 28], P < .001). Compared with medicine meta-analyses, diagnostic pathology meta-analyses less likely reported 23 of the 27 items (85.2%) on the PRISMA checklist, but more likely reported the data items. Higher reporting quality of diagnostic pathology meta-analyses was associated with recent publication years (later than 2009 versus 2009 or earlier, P = .002) and non-North American first authors (versus North American, P = .001), but not journal publisher's location (P = .11). Interestingly, reporting quality was not associated with adjusted citation ratio for meta-analyses in either diagnostic pathology or medicine (P = .40 and P = .09, respectively). - Meta-analyses in diagnostic pathology had lower reporting quality than those in medicine. Reporting quality of diagnostic pathology meta-analyses is linked to publication year and first author's location, but not to journal publisher's location or article's adjusted citation ratios. More research and education on meta-analysis methodology may improve the reporting quality of diagnostic pathology meta-analyses.

  10. Association among depressive disorder, adjustment disorder, sleep disturbance, and suicidal ideation in Taiwanese adolescent.

    PubMed

    Chung, Ming-Shun; Chiu, Hsien-Jane; Sun, Wen-Jung; Lin, Chieh-Nan; Kuo, Chien-Cheng; Huang, Wei-Che; Chen, Ying-Sheue; Cheng, Hui-Ping; Chou, Pesus

    2014-09-01

    The aim of this study is to investigate the association among depressive disorder, adjustment disorder, sleep disturbance, and suicidal ideation in Taiwanese adolescent. We recruited 607 students (grades 5-9) to fill out the investigation of basic data and sleep disturbance. Psychiatrists then used the Mini International Neuropsychiatric Interview-Kid to interview these students to assess their suicidal ideation and psychiatric diagnosis. Multiple logistic regression with forward conditionals was used to find the risk factors for multivariate analysis. Female, age, depressive disorder, adjustment disorder, and poor sleep all contributed to adolescent suicidal ideation in univariate analysis. However, poor sleep became non-significant under the control of depressive disorder and adjustment disorder. We found that both depressive disorder and adjustment disorder play important roles in sleep and adolescent suicidal ideation. After controlling both depressive disorder and adjustment disorder, sleep disturbance was no longer a risk of adolescent suicidal ideation. We also confirm the indirect influence of sleep on suicidal ideation in adolescent. © 2013 Wiley Publishing Asia Pty Ltd.

  11. Use of risk-adjusted CUSUM charts to monitor 30-day mortality in Danish hospitals.

    PubMed

    Rasmussen, Thomas Bøjer; Ulrichsen, Sinna Pilgaard; Nørgaard, Mette

    2018-01-01

    Monitoring hospital outcomes and clinical processes as a measure of clinical performance is an integral part of modern health care. The risk-adjusted cumulative sum (CUSUM) chart is a frequently used sequential analysis technique that can be implemented to monitor a wide range of different types of outcomes. The aim of this study was to describe how risk-adjusted CUSUM charts based on population-based nationwide medical registers were used to monitor 30-day mortality in Danish hospitals and to give an example on how alarms of increased hospital mortality from the charts can guide further in-depth analyses. We used routinely collected administrative data from the Danish National Patient Registry and the Danish Civil Registration System to create risk-adjusted CUSUM charts. We monitored 30-day mortality after hospital admission with one of 77 selected diagnoses in 24 hospital units in Denmark in 2015. The charts were set to detect a 50% increase in 30-day mortality, and control limits were determined by simulations. Among 1,085,576 hospital admissions, 441,352 admissions had one of the 77 selected diagnoses as their primary diagnosis and were included in the risk-adjusted CUSUM charts. The charts yielded a total of eight alarms of increased mortality. The median of the hospitals' estimated average time to detect a 50% increase in 30-day mortality was 50 days (interquartile interval, 43;54). In the selected example of an alarm, descriptive analyses indicated performance problems with 30-day mortality following hip fracture surgery and diagnosis of chronic obstructive pulmonary disease. The presented implementation of risk-adjusted CUSUM charts can detect significant increases in 30-day mortality within 2 months, on average, in most Danish hospitals. Together with descriptive analyses, it was possible to use an alarm from a risk-adjusted CUSUM chart to identify potential performance problems.

  12. Separation in Logistic Regression: Causes, Consequences, and Control.

    PubMed

    Mansournia, Mohammad Ali; Geroldinger, Angelika; Greenland, Sander; Heinze, Georg

    2018-04-01

    Separation is encountered in regression models with a discrete outcome (such as logistic regression) where the covariates perfectly predict the outcome. It is most frequent under the same conditions that lead to small-sample and sparse-data bias, such as presence of a rare outcome, rare exposures, highly correlated covariates, or covariates with strong effects. In theory, separation will produce infinite estimates for some coefficients. In practice, however, separation may be unnoticed or mishandled because of software limits in recognizing and handling the problem and in notifying the user. We discuss causes of separation in logistic regression and describe how common software packages deal with it. We then describe methods that remove separation, focusing on the same penalized-likelihood techniques used to address more general sparse-data problems. These methods improve accuracy, avoid software problems, and allow interpretation as Bayesian analyses with weakly informative priors. We discuss likelihood penalties, including some that can be implemented easily with any software package, and their relative advantages and disadvantages. We provide an illustration of ideas and methods using data from a case-control study of contraceptive practices and urinary tract infection.

  13. Temporal Synchronization Analysis for Improving Regression Modeling of Fecal Indicator Bacteria Levels

    EPA Science Inventory

    Multiple linear regression models are often used to predict levels of fecal indicator bacteria (FIB) in recreational swimming waters based on independent variables (IVs) such as meteorologic, hydrodynamic, and water-quality measures. The IVs used for these analyses are traditiona...

  14. Hospital Variation in Risk-Adjusted Pediatric Sepsis Mortality.

    PubMed

    Ames, Stefanie G; Davis, Billie S; Angus, Derek C; Carcillo, Joseph A; Kahn, Jeremy M

    2018-05-01

    With continued attention to pediatric sepsis at both the clinical and policy levels, it is important to understand the quality of hospitals in terms of their pediatric sepsis mortality. We sought to develop a method to evaluate hospital pediatric sepsis performance using 30-day risk-adjusted mortality and to assess hospital variation in risk-adjusted sepsis mortality in a large state-wide sample. Retrospective cohort study using administrative claims data. Acute care hospitals in the state of Pennsylvania from 2011 to 2013. Patients between the ages of 0-19 years admitted to a hospital with sepsis defined using validated International Classification of Diseases, Ninth revision, Clinical Modification, diagnosis and procedure codes. None. During the study period, there were 9,013 pediatric sepsis encounters in 153 hospitals. After excluding repeat visits and hospitals with annual patient volumes too small to reliably assess hospital performance, there were 6,468 unique encounters in 24 hospitals. The overall unadjusted mortality rate was 6.5% (range across all hospitals: 1.5-11.9%). The median number of pediatric sepsis cases per hospital was 67 (range across all hospitals: 30-1,858). A hierarchical logistic regression model for 30-day risk-adjusted mortality controlling for patient age, gender, emergency department admission, infection source, presence of organ dysfunction at admission, and presence of chronic complex conditions showed good discrimination (C-statistic = 0.80) and calibration (slope and intercept of calibration plot: 0.95 and -0.01, respectively). The hospital-specific risk-adjusted mortality rates calculated from this model varied minimally, ranging from 6.0% to 7.4%. Although a risk-adjustment model for 30-day pediatric sepsis mortality had good performance characteristics, the use of risk-adjusted mortality rates as a hospital quality measure in pediatric sepsis is not useful due to the low volume of cases at most hospitals. Novel metrics to

  15. Functional mixture regression.

    PubMed

    Yao, Fang; Fu, Yuejiao; Lee, Thomas C M

    2011-04-01

    In functional linear models (FLMs), the relationship between the scalar response and the functional predictor process is often assumed to be identical for all subjects. Motivated by both practical and methodological considerations, we relax this assumption and propose a new class of functional regression models that allow the regression structure to vary for different groups of subjects. By projecting the predictor process onto its eigenspace, the new functional regression model is simplified to a framework that is similar to classical mixture regression models. This leads to the proposed approach named as functional mixture regression (FMR). The estimation of FMR can be readily carried out using existing software implemented for functional principal component analysis and mixture regression. The practical necessity and performance of FMR are illustrated through applications to a longevity analysis of female medflies and a human growth study. Theoretical investigations concerning the consistent estimation and prediction properties of FMR along with simulation experiments illustrating its empirical properties are presented in the supplementary material available at Biostatistics online. Corresponding results demonstrate that the proposed approach could potentially achieve substantial gains over traditional FLMs.

  16. Sensitivity analysis for mistakenly adjusting for mediators in estimating total effect in observational studies.

    PubMed

    Wang, Tingting; Li, Hongkai; Su, Ping; Yu, Yuanyuan; Sun, Xiaoru; Liu, Yi; Yuan, Zhongshang; Xue, Fuzhong

    2017-11-20

    In observational studies, epidemiologists often attempt to estimate the total effect of an exposure on an outcome of interest. However, when the underlying diagram is unknown and limited knowledge is available, dissecting bias performances is essential to estimating the total effect of an exposure on an outcome when mistakenly adjusting for mediators under logistic regression. Through simulation, we focused on six causal diagrams concerning different roles of mediators. Sensitivity analysis was conducted to assess the bias performances of varying across exposure-mediator effects and mediator-outcome effects when adjusting for the mediator. Based on the causal relationships in the real world, we compared the biases of varying across the effects of exposure-mediator with those of varying across the effects of mediator-outcome when adjusting for the mediator. The magnitude of the bias was defined by the difference between the estimated effect (using logistic regression) and the total effect of the exposure on the outcome. In four scenarios (a single mediator, two series mediators, two independent parallel mediators or two correlated parallel mediators), the biases of varying across the effects of exposure-mediator were greater than those of varying across the effects of mediator-outcome when adjusting for the mediator. In contrast, in two other scenarios (a single mediator or two independent parallel mediators in the presence of unobserved confounders), the biases of varying across the effects of exposure-mediator were less than those of varying across the effects of mediator-outcome when adjusting for the mediator. The biases were more sensitive to the variation of effects of exposure-mediator than the effects of mediator-outcome when adjusting for the mediator in the absence of unobserved confounders, while the biases were more sensitive to the variation of effects of mediator-outcome than those of exposure-mediator in the presence of an unobserved confounder.

  17. Can statistic adjustment of OR minimize the potential confounding bias for meta-analysis of case-control study? A secondary data analysis.

    PubMed

    Liu, Tianyi; Nie, Xiaolu; Wu, Zehao; Zhang, Ying; Feng, Guoshuang; Cai, Siyu; Lv, Yaqi; Peng, Xiaoxia

    2017-12-29

    Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis. We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders. Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding. The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind

  18. Kidney function changes with aging in adults: comparison between cross-sectional and longitudinal data analyses in renal function assessment.

    PubMed

    Chung, Sang M; Lee, David J; Hand, Austin; Young, Philip; Vaidyanathan, Jayabharathi; Sahajwalla, Chandrahas

    2015-12-01

    The study evaluated whether the renal function decline rate per year with age in adults varies based on two primary statistical analyses: cross-section (CS), using one observation per subject, and longitudinal (LT), using multiple observations per subject over time. A total of 16628 records (3946 subjects; age range 30-92 years) of creatinine clearance and relevant demographic data were used. On average, four samples per subject were collected for up to 2364 days (mean: 793 days). A simple linear regression and random coefficient models were selected for CS and LT analyses, respectively. The renal function decline rates per year were 1.33 and 0.95 ml/min/year for CS and LT analyses, respectively, and were slower when the repeated individual measurements were considered. The study confirms that rates are different based on statistical analyses, and that a statistically robust longitudinal model with a proper sampling design provides reliable individual as well as population estimates of the renal function decline rates per year with age in adults. In conclusion, our findings indicated that one should be cautious in interpreting the renal function decline rate with aging information because its estimation was highly dependent on the statistical analyses. From our analyses, a population longitudinal analysis (e.g. random coefficient model) is recommended if individualization is critical, such as a dose adjustment based on renal function during a chronic therapy. Copyright © 2015 John Wiley & Sons, Ltd.

  19. Optimization of fixture layouts of glass laser optics using multiple kernel regression.

    PubMed

    Su, Jianhua; Cao, Enhua; Qiao, Hong

    2014-05-10

    We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.

  20. Use of probabilistic weights to enhance linear regression myoelectric control

    NASA Astrophysics Data System (ADS)

    Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

    2015-12-01

    Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  1. Who uses height-adjustable desks? - Sociodemographic, health-related, and psycho-social variables of regular users.

    PubMed

    Wallmann-Sperlich, Birgit; Bipp, Tanja; Bucksch, Jens; Froboese, Ingo

    2017-03-06

    Sit-to-stand height-adjustable desks (HAD) may promote workplace standing, as long as workers use them on a regular basis. The aim of this study was to investigate (i) how common HAD in German desk-based workers are, and how frequently HADs are used, (ii) to identify sociodemographic, health-related, and psycho-social variables of workday sitting including having a HAD, and (iii) to analyse sociodemographic, health-related, and psycho-social variables of users and non-users of HADs. A cross-sectional sample of 680 participants (51.9% men; 41.0 ± 13.1 years) in a desk-based occupation was interviewed by telephone about their occupational sitting and standing proportions, having and usage of a HAD, and answered questions concerning psycho-social variables of occupational sitting. The proportion of workday sitting was calculated for participants having an HAD (n = 108) and not-having an HAD (n = 573), as well as for regular users of HAD (n = 54), and irregular/non-users of HAD (n = 54). Linear regressions were conducted to calculate associations between socio-demographic, health-related, psychosocial variables and having/not having an HAD, and the proportion of workday sitting. Logistic regressions were executed to examine the association of mentioned variables and participants' usage of HADs. Sixteen percent report that they have an HAD, and 50% of these report regular use of HAD. Having an HAD is not a correlate of the proportion of workday sitting. Further analysis restricted to participants having available a HAD highlights that only the 'perceived advantages of sitting less' was significantly associated with HAD use in the fully adjusted model (OR 1.75 [1.09; 2.81], p < 0.05). The present findings indicate that accompanying behavioral action while providing an HAD is promising to increase the regular usage of HAD. Hence, future research needs to address the specificity of behavioral actions in order to enhance regular HAD use, and needs

  2. 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.

  3. Vertebral artery injury associated with blunt cervical spine trauma: a multivariate regression analysis.

    PubMed

    Lebl, Darren R; Bono, Christopher M; Velmahos, George; Metkar, Umesh; Nguyen, Joseph; Harris, Mitchel B

    2013-07-15

    Retrospective analysis of prospective registry data. To determine the patient characteristics, risk factors, and fracture patterns associated with vertebral artery injury (VAI) in patients with blunt cervical spine injury. VAI associated with cervical spine trauma has the potential for catastrophical clinical sequelae. The patterns of cervical spine injury and patient characteristics associated with VAI remain to be determined. A retrospective review of prospectively collected data from the American College of Surgeons trauma registries at 3 level-1 trauma centers identified all patients with a cervical spine injury on multidetector computed tomographic scan during a 3-year period (January 1, 2007, to January 1, 2010). Fracture pattern and patient characteristics were recorded. Logistic multivariate regression analysis of independent predictors for VAI and subgroup analysis of neurological events related to VAI was performed. Twenty-one percent of 1204 patients with cervical injuries (n = 253) underwent screening for VAI by multidetector computed tomography angiogram. VAI was diagnosed in 17% (42 of 253), unilateral in 15% (38 of 253), and bilateral in 1.6% (4 of 253) and was associated with a lower Glasgow coma scale (P < 0.001), a higher injury severity score (P < 0.01), and a higher mortality (P < 0.001). VAI was associated with ankylosing spondylitis/diffuse idiopathic skeletal hyperosteosis (crude odds ratio [OR] = 8.04; 95% confidence interval [CI], 1.30-49.68; P = 0.034), and occipitocervical dissociation (P < 0.001) by univariate analysis and fracture displacement into the transverse foramen 1 mm or more (adjusted OR = 3.29; 95% CI, 1.15-9.41; P = 0.026), and basilar skull fracture (adjusted OR = 4.25; 95% CI, 1.25-14.47; P= 0.021), by multivariate regression model. Subgroup analyses of neurological events secondary to VAI occurred in 14% (6 of 42) and the stroke-related mortality rate was 4.8% (2 of 42). Neurological events were associated with male sex (P

  4. Regression of left ventricular hypertrophy and microalbuminuria changes during antihypertensive treatment.

    PubMed

    Rodilla, Enrique; Pascual, Jose Maria; Costa, Jose Antonio; Martin, Joaquin; Gonzalez, Carmen; Redon, Josep

    2013-08-01

    The objective of the present study was to assess the regression of left ventricular hypertrophy (LVH) during antihypertensive treatment, and its relationship with the changes in microalbuminuria. One hundred and sixty-eight previously untreated patients with echocardiographic LVH, 46 (27%) with microalbuminuria, were followed during a median period of 13 months (range 6-23 months) and treated with lifestyle changes and antihypertensive drugs. Twenty-four-hour ambulatory blood pressure monitoring, echocardiography and urinary albumin excretion were assessed at the beginning and at the end of the study period. Left ventricular mass index (LVMI) was reduced from 137 [interquartile interval (IQI), 129-154] to 121 (IQI, 104-137) g/m (P < 0.001). Eighty-nine patients (53%) had a reduction in LVMI of at least 17.8 g/m, and an LVH regression rate of 43.8 per 100 patient-years [95% confidence interval (CI) 35.2-53.9]. The main factor related to LVH regression was the reduction in SBP24 h [multivariate odds ratio (ORm) 4.49; 95% CI 1.73-11.63; P = 0.005, highest tertile compared with lower tertiles]. Male sex (ORm 0.39; 95% CI 0.17-0.90; P = 0.04) and baseline glomerular filtration rate less than 90 ml/min per 1.73 m (ORm 0.39; 95% CI 0.17-0.90; P = 0.03) were associated with a lower probability of LVH regression. Patients with microalbuminuria regression (urinary albumin excretion reduction >50%) had the same odds of achieving regression of LVH as patients with normoalbuminuria (ORm 1.1; 95% CI 0.38-3.25; P = 0.85). However, those with microalbuminuria at baseline, who did not regress, had less probability of achieving LVH regression than the normoalbuminuric patients (OR 0.26; 95% CI 0.07-0.90; P = 0.03) even when adjusted for age, sex, initial LVMI, GFR, blood pressure and angiotensin-converting enzyme inhibitor (ACE-I) or angiotensin receptor blocker (ARB) treatment during the follow-up. Patients who do not have a significant reduction in

  5. Long-term Adjustment After Surviving Open Heart Surgery: The Effect of Using Prayer for Coping Replicated in a Prospective Design.

    PubMed

    Ai, A L; Ladd, K L; Peterson, C; Cook, C A; Shearer, M; Koenig, H G

    2010-12-01

    despite the growing evidence for effects of religious factors on cardiac health in general populations, findings are not always consistent in sicker and older populations. We previously demonstrated that short-term negative outcomes (depression and anxiety) among older adults following open heart surgery are partially alleviated when patients employ prayer as part of their coping strategy. The present study examines multifaceted effects of religious factors on long-term postoperative adjustment, extending our previous findings concerning prayer and coping with cardiac disease. analyses capitalized on a preoperative survey and medical variables from the Society of Thoracic Surgeons' National Database of patients undergoing open heart surgery. The current participants completed a mailed survey 30 months after surgery. Two hierarchical regressions were performed to evaluate the extent to which religious factors predicted depression and anxiety, after controlling for key demographics, medical indices, and mental health. predicting lower levels of depression at the follow-up were preoperative use of prayer for coping, optimism, and hope. Predicting lower levels of anxiety at the follow-up were subjective religiousness, marital status, and hope. Predicting poorer adjustment were reverence in religious contexts, preoperative mental health symptoms, and medical comorbidity. Including optimism and hope in the model did not eliminate effects of religious factors. Several other religious factors had no long-term influences. MPLICATIONS: the influence of religious factors on the long-term postoperative adjustment is independent and complex, with mediating factors yet to be determined. Future research should investigate mechanisms underlying religion-health relations.

  6. Associations between faith, distress and mental adjustment--a Danish survivorship study.

    PubMed

    Johannessen-Henry, Christine Tind; Deltour, Isabelle; Bidstrup, Pernille Envold; Dalton, Susanne O; Johansen, Christoffer

    2013-02-01

    Several studies have suggested that religion and spirituality are important for overcoming psychological distress and adjusting mentally to cancer, but these studies did not differentiate between spiritual well-being and specific aspects of faith. We examined the extent to which spiritual well-being, the faith dimension of spiritual well-being and aspects of performed faith are associated with distress and mental adjustment among cancer patients. In a cross-sectional design, 1043 survivors of various cancers filled in a questionnaire on spiritual well-being (FACIT-Sp-12), specific aspects of faith ('belief in a god', 'belief in a god with whom I can talk' and 'experiences of god or a higher power'), religious community and church attendance (DUREL), distress (POMS-SF), adjustment to cancer (Mini-MAC) and sociodemographic factors. Linear regression models were used to analyze the associations between exposure (spiritual well-being and specific faith aspects) and outcome (distress and adjustment to cancer) with adjustment for age, gender, cancer diagnosis and physical and social well-being. Higher spiritual well-being was associated with less total distress (β = -0.79, CI -0.92; -0.66) and increased adjustment to cancer (fighting spirit, anxious preoccupation, helplessness-hopelessness). Specific aspects of faith were associated with high confusion-bewilderment and tension-anxiety, but also lower score on vigor-activity, and with higher anxious-preoccupation, both higher and lower cognitive avoidance, but also more fighting spirit. As hypothesized, spiritual well-being were associated with less distress and better mental adjustment. However, specific aspects of faith were both positively and negatively associated with distress and mental adjustment. The results illustrate the complexity of associations between spiritual well-being and specific aspects of faith with psychological function among cancer survivors.

  7. Maternal personal resources and children's socioemotional and behavioral adjustment.

    PubMed

    Al-Yagon, Michal

    2008-09-01

    The study examined the role of three maternal personal resources [sense of coherence (SOC), attachment style, and social/emotional feelings of loneliness] in explaining children's socioemotional adjustment (self-rated loneliness and SOC, and mother-rated child behavior) and children's (self-rated) secure attachment. The sample included 58 mother-child dyads (27 boys and 31 girls) aged 8-11 years. Preliminary analyses indicated significant group differences between mothers with high or low scores on the two subscales of the attachment scale (i.e., avoidance and anxiety), on their SOC, and their social/emotional loneliness. Findings revealed that maternal SOC significantly contributed to all child socioemotional adjustment measures and attachment scores. In addition, the current findings demonstrated the role of maternal anxious attachment in explaining children's externalizing behaviors. Discussion focused on the unique value of maternal characteristics for understanding social and emotional adjustment among school-age children.

  8. Ancestry-Adjusted Vitamin D Metabolite Concentrations in Association With Cytochrome P450 3A Polymorphisms.

    PubMed

    Wilson, Robin Taylor; Masters, Loren D; Barnholtz-Sloan, Jill S; Salzberg, Anna C; Hartman, Terryl J

    2018-04-01

    We investigated the association between genetic polymorphisms in cytochrome P450 (CYP2R1, CYP24A1, and the CYP3A family) with nonsummer plasma concentrations of vitamin D metabolites (25-hydroxyvitamin D3 (25(OH)D3) and proportion 24,25-dihydroxyvitamin D3 (24,25(OH)2D3)) among healthy individuals of sub-Saharan African and European ancestry, matched on age (within 5 years; n = 188 in each ancestral group), in central suburban Pennsylvania (2006-2009). Vitamin D metabolites were measured using high-performance liquid chromatography with tandem mass spectrometry. Paired multiple regression and adjusted least-squares mean analyses were used to test for associations between genotype and log-transformed metabolite concentrations, adjusted for age, sex, proportion of West-African genetic ancestry, body mass index, oral contraceptive (OC) use, tanning bed use, vitamin D intake, days from summer solstice, time of day of blood draw, and isoforms of the vitamin D receptor (VDR) and vitamin D binding protein. Polymorphisms in CYP2R1, CYP3A43, vitamin D binding protein, and genetic ancestry proportion remained associated with plasma 25(OH)D3 after adjustment. Only CYP3A43 and VDR polymorphisms were associated with proportion 24,25(OH)2D3. Magnitudes of association with 25(OH)D3 were similar for CYP3A43, tanning bed use, and OC use. Significant least-squares mean interactions (CYP2R1/OC use (P = 0.030) and CYP3A43/VDR (P = 0.013)) were identified. A CYP3A43 genotype, previously implicated in cancer, is strongly associated with biomarkers of vitamin D metabolism. Interactive associations should be further investigated.

  9. Body mass index adjustments to increase the validity of body fatness assessment in UK Black African and South Asian children

    PubMed Central

    Hudda, M T; Nightingale, C M; Donin, A S; Fewtrell, M S; Haroun, D; Lum, S; Williams, J E; Owen, C G; Rudnicka, A R; Wells, J C K; Cook, D G; Whincup, P H

    2017-01-01

    Background/Objectives: Body mass index (BMI) (weight per height2) is the most widely used marker of childhood obesity and total body fatness (BF). However, its validity is limited, especially in children of South Asian and Black African origins. We aimed to quantify BMI adjustments needed for UK children of Black African and South Asian origins so that adjusted BMI related to BF in the same way as for White European children. Methods: We used data from four recent UK studies that made deuterium dilution BF measurements in UK children of White European, South Asian and Black African origins. A height-standardized fat mass index (FMI) was derived to represent BF. Linear regression models were then fitted, separately for boys and girls, to quantify ethnic differences in BMI–FMI relationships and to provide ethnic-specific BMI adjustments. Results: We restricted analyses to 4–12 year olds, to whom a single consistent FMI (fat mass per height5) could be applied. BMI consistently underestimated BF in South Asians, requiring positive BMI adjustments of +1.12 kg m−2 (95% confidence interval (CI): 0.83, 1.41 kg m−2; P<0.0001) for boys and +1.07 kg m−2 (95% CI: 0.74, 1.39 kg m−2; P<0.0001) for girls of all age groups and FMI levels. BMI overestimated BF in Black Africans, requiring negative BMI adjustments for Black African children. However, these were complex because there were statistically significant interactions between Black African ethnicity and FMI (P=0.004 boys; P=0.003 girls) and also between FMI and age group (P<0.0001 for boys and girls). BMI adjustments therefore varied by age group and FMI level (and indirectly BMI); the largest adjustments were in younger children with higher unadjusted BMI and the smallest in older children with lower unadjusted BMI. Conclusions: BMI underestimated BF in South Asians and overestimated BF in Black Africans. Ethnic-specific adjustments, increasing BMI in South Asians and reducing BMI in Black

  10. Genome-wide regression and prediction with the BGLR statistical package.

    PubMed

    Pérez, Paulino; de los Campos, Gustavo

    2014-10-01

    Many modern genomic data analyses require implementing regressions where the number of parameters (p, e.g., the number of marker effects) exceeds sample size (n). Implementing these large-p-with-small-n regressions poses several statistical and computational challenges, some of which can be confronted using Bayesian methods. This approach allows integrating various parametric and nonparametric shrinkage and variable selection procedures in a unified and consistent manner. The BGLR R-package implements a large collection of Bayesian regression models, including parametric variable selection and shrinkage methods and semiparametric procedures (Bayesian reproducing kernel Hilbert spaces regressions, RKHS). The software was originally developed for genomic applications; however, the methods implemented are useful for many nongenomic applications as well. The response can be continuous (censored or not) or categorical (either binary or ordinal). The algorithm is based on a Gibbs sampler with scalar updates and the implementation takes advantage of efficient compiled C and Fortran routines. In this article we describe the methods implemented in BGLR, present examples of the use of the package, and discuss practical issues emerging in real-data analysis. Copyright © 2014 by the Genetics Society of America.

  11. Quantile regression for the statistical analysis of immunological data with many non-detects.

    PubMed

    Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

    2012-07-07

    Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

  12. Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

    ERIC Educational Resources Information Center

    Shafiq, M. Najeeb

    2013-01-01

    Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

  13. Longitudinal Psychosocial Adjustment of Women to Human Papillomavirus Infection.

    PubMed

    Hsu, Yu-Yun; Wang, Wei-Ming; Fetzer, Susan Jane; Cheng, Ya-Min; Hsu, Keng-Fu

    2018-05-29

    The aim of this study was to examine the psychosocial adjustment trajectory, focusing on psychological distress, sexual relationships and health care information, as well as factors which have an impact on adjustment on receiving a positive diagnosis of human papillomavirus infection. Human papillomavirus is a common sexually transmitted infection in females. To date, knowledge of the longitudinal psychosocial response to the diagnosis of human papillomavirus is limited. A prospective longitudinal design was conducted with a convenience sample. Women aged 20-65 years old were followed at one, 6 and 12 months after a diagnosis of HPV. Participants completed measures of initial emotional distress and followed-up psychosocial adjustment. A mixed-effects model was applied to analyze the longitudinal changes in psychosocial adjustment. Seventy human papillomavirus positive women participated in the study with nearly 20% of the women reporting emotional distress during their first visit. Mixed-effects model analyses showed that a trajectory of psychosocial adjustment in health care orientation, sexual relationship and psychosocial distress occur from one to 6 months after HPV diagnosis. However, a declining trend from 6-12 months was significant in health care orientation. Initial emotional distress was associated with changes in psychological adjustment. Psychosocial adjustment to human papillomavirus was worse at one month compared with 6 and 12 months after diagnosis. Healthcare providers should offer health information and psychosocial support to women according to their disease progression. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  14. Smooth individual level covariates adjustment in disease mapping.

    PubMed

    Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise

    2018-05-01

    Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Measuring Sojourner Adjustment among American students studying abroad

    PubMed Central

    Pedersen, Eric R.; Neighbors, Clayton; Larimer, Mary E.; Lee, Christine M.

    2011-01-01

    The literature on “Sojourner Adjustment,” a term expanding on the acculturation concept to apply to groups residing temporarily in foreign environments, suggests that engagement, participation, and temporary integration into the host culture may contribute to less psychological and sociocultural difficulty while abroad. The present study was designed to establish a brief multi-component measure of Sojourner Adjustment (the Sojourner Adjustment Measure; SAM) to be used in work with populations residing temporarily in foreign environments (e.g., international students, foreign aid workers). Using exploratory and confirmatory factor analyses on a sample of 248 American study abroad college students, we established a 24-item measure of Sojourner Adjustment composed of four positive factors (social interaction with host nationals, cultural understanding and participation, language development and use, host culture identification) and two negative factors (social interaction with co-nationals, homesickness/feeling out of place). Preliminary convergent validity was examined through correlations with established measures of acculturation. Further research with the SAM is encouraged to explore the relevance of this measure with other groups of sojourners (e.g., foreign aid workers, international businessmen, military personnel) and to determine how SAM factors relate to psychological well-being, health behaviors, and risk behaviors abroad among these diverse groups. PMID:22125351

  16. Weighing Evidence “Steampunk” Style via the Meta-Analyser

    PubMed Central

    Bowden, Jack; Jackson, Chris

    2016-01-01

    ABSTRACT The funnel plot is a graphical visualization of summary data estimates from a meta-analysis, and is a useful tool for detecting departures from the standard modeling assumptions. Although perhaps not widely appreciated, a simple extension of the funnel plot can help to facilitate an intuitive interpretation of the mathematics underlying a meta-analysis at a more fundamental level, by equating it to determining the center of mass of a physical system. We used this analogy to explain the concepts of weighing evidence and of biased evidence to a young audience at the Cambridge Science Festival, without recourse to precise definitions or statistical formulas and with a little help from Sherlock Holmes! Following on from the science fair, we have developed an interactive web-application (named the Meta-Analyser) to bring these ideas to a wider audience. We envisage that our application will be a useful tool for researchers when interpreting their data. First, to facilitate a simple understanding of fixed and random effects modeling approaches; second, to assess the importance of outliers; and third, to show the impact of adjusting for small study bias. This final aim is realized by introducing a novel graphical interpretation of the well-known method of Egger regression. PMID:28003684

  17. Reconstruction of missing daily streamflow data using dynamic regression models

    NASA Astrophysics Data System (ADS)

    Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault

    2015-12-01

    River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.

  18. Results from a preliminary study to develop the quality adjustments for quality adjusted life year values for Trinidad and Tobago.

    PubMed

    Bailey, H

    2013-07-01

    No country can afford to provide all necessary healthcare for its citizens, so prioritization among interventions must feature in all health systems. Resources in health should be allocated among interventions/facilities/patients in such a way as to be in line with the objectives of the health system. To achieve this, resource allocation decisions must be informed by the relative contributions that prospective interventions will make to societal health and to costs. Internationally, the EQ-5D based quality adjusted life year (QALY) now dominates this kind of analysis. This paper reports on a pilot study to develop an EQ-5D-3L value set for Trinidad and Tobago based on a protocol that avoids some of the issues that are associated with other approaches to developing such value sets such as the complex elicitation tasks that respondents must carry out, and the large respondent samples required for collecting multiple valuation subset values using blocked designs. An orthogonal discrete choice experiment design was used to elicit a set of choices from a sample of respondents. The choice data were analysed using mixed multinomial logistic regression to produce an internally valid model that predicts well. This paper marks an important milestone in the development of health resource allocation in the Caribbean. It sets out the importance of incorporating the impact of health interventions to inform health resource allocation decisions, describes the elicitation and analysis methods used in the pilot and provides an illustration of the use of the EQ-5D value set.

  19. Mental Health Risk Adjustment with Clinical Categories and Machine Learning.

    PubMed

    Shrestha, Akritee; Bergquist, Savannah; Montz, Ellen; Rose, Sherri

    2017-12-15

    To propose nonparametric ensemble machine learning for mental health and substance use disorders (MHSUD) spending risk adjustment formulas, including considering Clinical Classification Software (CCS) categories as diagnostic covariates over the commonly used Hierarchical Condition Category (HCC) system. 2012-2013 Truven MarketScan database. We implement 21 algorithms to predict MHSUD spending, as well as a weighted combination of these algorithms called super learning. The algorithm collection included seven unique algorithms that were supplied with three differing sets of MHSUD-related predictors alongside demographic covariates: HCC, CCS, and HCC + CCS diagnostic variables. Performance was evaluated based on cross-validated R 2 and predictive ratios. Results show that super learning had the best performance based on both metrics. The top single algorithm was random forests, which improved on ordinary least squares regression by 10 percent with respect to relative efficiency. CCS categories-based formulas were generally more predictive of MHSUD spending compared to HCC-based formulas. Literature supports the potential benefit of implementing a separate MHSUD spending risk adjustment formula. Our results suggest there is an incentive to explore machine learning for MHSUD-specific risk adjustment, as well as considering CCS categories over HCCs. © Health Research and Educational Trust.

  20. Logistic Regression in the Identification of Hazards in Construction

    NASA Astrophysics Data System (ADS)

    Drozd, Wojciech

    2017-10-01

    The construction site and its elements create circumstances that are conducive to the formation of risks to safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This article attempts to analyse the characteristics related to the construction site, in order to indicate their importance in defining the circumstances of accidents at work. The study includes sites inspected in 2014 - 2016 by the employees of the District Labour Inspectorate in Krakow (Poland). The analysed set of detailed (disaggregated) data includes both quantitative and qualitative characteristics. The substantive task focused on classification modelling in the identification of hazards in construction and identifying those of the analysed characteristics that are important in an accident. In terms of methodology, resource data analysis using statistical classifiers, in the form of logistic regression, was the method used.

  1. Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12

    USGS Publications Warehouse

    Galloway, Joel M.

    2014-01-01

    The Red River of the North (hereafter referred to as “Red River”) Basin is an important hydrologic region where water is a valuable resource for the region’s economy. Continuous water-quality monitors have been operated by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks at the Red River at Fargo, North Dakota, from 2003 through 2012 and at Grand Forks, N.Dak., from 2007 through 2012. The purpose of the monitoring was to provide a better understanding of the water-quality dynamics of the Red River and provide a way to track changes in water quality. Regression equations were developed that can be used to estimate concentrations and loads for dissolved solids, sulfate, chloride, nitrate plus nitrite, total phosphorus, and suspended sediment using explanatory variables such as streamflow, specific conductance, and turbidity. Specific conductance was determined to be a significant explanatory variable for estimating dissolved solids concentrations at the Red River at Fargo and Grand Forks. The regression equations provided good relations between dissolved solid concentrations and specific conductance for the Red River at Fargo and at Grand Forks, with adjusted coefficients of determination of 0.99 and 0.98, respectively. Specific conductance, log-transformed streamflow, and a seasonal component were statistically significant explanatory variables for estimating sulfate in the Red River at Fargo and Grand Forks. Regression equations provided good relations between sulfate concentrations and the explanatory variables, with adjusted coefficients of determination of 0.94 and 0.89, respectively. For the Red River at Fargo and Grand Forks, specific conductance, streamflow, and a seasonal component were statistically significant explanatory variables for estimating chloride. For the Red River at Grand Forks, a time

  2. Teacher characteristics, social classroom relationships, and children's social, emotional, and behavioral classroom adjustment in special education.

    PubMed

    Breeman, L D; Wubbels, T; van Lier, P A C; Verhulst, F C; van der Ende, J; Maras, A; Hopman, J A B; Tick, N T

    2015-02-01

    The goal of this study was to explore relations between teacher characteristics (i.e., competence and wellbeing); social classroom relationships (i.e., teacher-child and peer interactions); and children's social, emotional, and behavioral classroom adjustment. These relations were explored at both the individual and classroom levels among 414 children with emotional and behavioral disorders placed in special education. Two models were specified. In the first model, children's classroom adjustment was regressed on social relationships and teacher characteristics. In the second model, reversed links were examined by regressing teacher characteristics on social relationships and children's adjustment. Results of model 1 showed that, at the individual level, better social and emotional adjustment of children was predicted by higher levels of teacher-child closeness and better behavioral adjustment was predicted by both positive teacher-child and peer interactions. At the classroom level, positive social relationships were predicted by higher levels of teacher competence, which in turn were associated with lower classroom levels of social problems. Higher levels of teacher wellbeing were directly associated with classroom adaptive and maladaptive child outcomes. Results of model 2 showed that, at the individual and classroom levels, only the emotional and behavioral problems of children predicted social classroom relationships. At the classroom level, teacher competence was best predicted by positive teacher-child relationships and teacher wellbeing was best predicted by classroom levels of prosocial behavior. We discuss the importance of positive teacher-child and peer interactions for children placed in special education and suggest ways of improving classroom processes by targeting teacher competence. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  3. A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

    PubMed

    Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

    2017-06-01

    Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

  4. Correcting bias in self-rated quality of life: an application of anchoring vignettes and ordinal regression models to better understand QoL differences across commuting modes.

    PubMed

    Crane, Melanie; Rissel, Chris; Greaves, Stephen; Gebel, Klaus

    2016-02-01

    Likert scales are frequently used in public health research, but are subject to scale perception bias. This study sought to explore scale perception bias in quality-of-life (QoL) self-assessment and assess its relationships with commuting mode in the Sydney Travel and Health Study. Multilevel ordinal logistic regression analysis was used to analyse the association between two global QoL items about overall QoL and health satisfaction, with usual travel mode to work or study. Anchoring vignettes were applied using parametric and simpler nonparametric methods to detect and adjust for differences in reporting behaviour across age, sex, education, and income groups. The anchoring vignettes exposed differences in scale responses across demographic groups. After adjusting for these biases, public transport users (OR = 0.37, 95 % CI 0.21-0.65), walkers (OR = 0.44, 95 % CI 0.24-0.82), and motor vehicle users (OR = 0.47, 95 % CI 0.25-0.86) were all found to have lower odds of reporting high QoL compared with bicycle commuters. Similarly, the odds of reporting high health satisfaction were found to be proportionally lower amongst all competing travel modes: motor vehicle users (OR = 0.31, 95 % CI 0.18-0.56), public transport users (OR = 0.34, 95 % CI 0.20-0.57), and walkers (OR = 0.35, 95 % CI 0.20-0.64) when compared with cyclists. Fewer differences were observed in the unadjusted models. Application of the vignettes by the two approaches removed scaling biases, thereby improving the accuracy of the analyses of the associations between travel mode and quality of life. The adjusted results revealed higher quality of life in bicycle commuters compared with all other travel mode users.

  5. Risk adjustment alternatives in paying for behavioral health care under Medicaid.

    PubMed Central

    Ettner, S L; Frank, R G; McGuire, T G; Hermann, R C

    2001-01-01

    OBJECTIVE: To compare the performance of various risk adjustment models in behavioral health applications such as setting mental health and substance abuse (MH/SA) capitation payments or overall capitation payments for populations including MH/SA users. DATA SOURCES/STUDY DESIGN: The 1991-93 administrative data from the Michigan Medicaid program were used. We compared mean absolute prediction error for several risk adjustment models and simulated the profits and losses that behavioral health care carve outs and integrated health plans would experience under risk adjustment if they enrolled beneficiaries with a history of MH/SA problems. Models included basic demographic adjustment, Adjusted Diagnostic Groups, Hierarchical Condition Categories, and specifications designed for behavioral health. PRINCIPAL FINDINGS: Differences in predictive ability among risk adjustment models were small and generally insignificant. Specifications based on relatively few MH/SA diagnostic categories did as well as or better than models controlling for additional variables such as medical diagnoses at predicting MH/SA expenditures among adults. Simulation analyses revealed that among both adults and minors considerable scope remained for behavioral health care carve outs to make profits or losses after risk adjustment based on differential enrollment of severely ill patients. Similarly, integrated health plans have strong financial incentives to avoid MH/SA users even after adjustment. CONCLUSIONS: Current risk adjustment methodologies do not eliminate the financial incentives for integrated health plans and behavioral health care carve-out plans to avoid high-utilizing patients with psychiatric disorders. PMID:11508640

  6. Parametric regression model for survival data: Weibull regression model as an example

    PubMed Central

    2016-01-01

    Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

  7. Computational tools for exact conditional logistic regression.

    PubMed

    Corcoran, C; Mehta, C; Patel, N; Senchaudhuri, P

    Logistic regression analyses are often challenged by the inability of unconditional likelihood-based approximations to yield consistent, valid estimates and p-values for model parameters. This can be due to sparseness or separability in the data. Conditional logistic regression, though useful in such situations, can also be computationally unfeasible when the sample size or number of explanatory covariates is large. We review recent developments that allow efficient approximate conditional inference, including Monte Carlo sampling and saddlepoint approximations. We demonstrate through real examples that these methods enable the analysis of significantly larger and more complex data sets. We find in this investigation that for these moderately large data sets Monte Carlo seems a better alternative, as it provides unbiased estimates of the exact results and can be executed in less CPU time than can the single saddlepoint approximation. Moreover, the double saddlepoint approximation, while computationally the easiest to obtain, offers little practical advantage. It produces unreliable results and cannot be computed when a maximum likelihood solution does not exist. Copyright 2001 John Wiley & Sons, Ltd.

  8. Examining the components of children's peer liking as antecedents of school adjustment.

    PubMed

    Betts, Lucy R; Rotenberg, Ken J; Trueman, Mark; Stiller, James

    2012-06-01

    Children's social interactions with their peers influence their psychosocial adjustment; consequently, the relationship between class-wide peer liking, same-gender peer liking, and school adjustment was explored in two age groups. Peer liking was analysed using the social relations model (SRM). In Study 1, 205 children (103 female and 102 male, M(age) = 7.15, SD= 7 months) completed measures of peer liking and school adjustment, and teachers completed the Short-Form Teacher Rating Scale of School Adjustment (Short-Form TRSSA). In Study 2, 197 children (98 female and 90 male, M(age) = 9.87, SD= 5.9 months) completed measures of peer liking and school adjustment. Both studies yielded evidence of reciprocal liking and individual differences in the ratings of liking awarded to, and elicited from, both peer groups. Multigroup path analysis, with groups created according to gender, revealed that elements of liking predicted different aspects of school adjustment with some variation according to age and gender. Together, these findings suggest that the SRM can be used to examine peer liking and underscore the importance of children's peers for school adjustment. © 2011 The British Psychological Society.

  9. Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes.

    PubMed

    Petersen, Laura A; Pietz, Kenneth; Woodard, LeChauncy D; Byrne, Margaret

    2005-01-01

    Many possible methods of risk adjustment exist, but there is a dearth of comparative data on their performance. We compared the predictive validity of 2 widely used methods (Diagnostic Cost Groups [DCGs] and Adjusted Clinical Groups [ACGs]) for 2 clinical outcomes using a large national sample of patients. We studied all patients who used Veterans Health Administration (VA) medical services in fiscal year (FY) 2001 (n = 3,069,168) and assigned both a DCG and an ACG to each. We used logistic regression analyses to compare predictive ability for death or long-term care (LTC) hospitalization for age/gender models, DCG models, and ACG models. We also assessed the effect of adding age to the DCG and ACG models. Patients in the highest DCG categories, indicating higher severity of illness, were more likely to die or to require LTC hospitalization. Surprisingly, the age/gender model predicted death slightly more accurately than the ACG model (c-statistic of 0.710 versus 0.700, respectively). The addition of age to the ACG model improved the c-statistic to 0.768. The highest c-statistic for prediction of death was obtained with a DCG/age model (0.830). The lowest c-statistics were obtained for age/gender models for LTC hospitalization (c-statistic 0.593). The c-statistic for use of ACGs to predict LTC hospitalization was 0.783, and improved to 0.792 with the addition of age. The c-statistics for use of DCGs and DCG/age to predict LTC hospitalization were 0.885 and 0.890, respectively, indicating the best prediction. We found that risk adjusters based upon diagnoses predicted an increased likelihood of death or LTC hospitalization, exhibiting good predictive validity. In this comparative analysis using VA data, DCG models were generally superior to ACG models in predicting clinical outcomes, although ACG model performance was enhanced by the addition of age.

  10. Environmental Chemicals in Urine and Blood: Improving Methods for Creatinine and Lipid Adjustment.

    PubMed

    O'Brien, Katie M; Upson, Kristen; Cook, Nancy R; Weinberg, Clarice R

    2016-02-01

    Investigators measuring exposure biomarkers in urine typically adjust for creatinine to account for dilution-dependent sample variation in urine concentrations. Similarly, it is standard to adjust for serum lipids when measuring lipophilic chemicals in serum. However, there is controversy regarding the best approach, and existing methods may not effectively correct for measurement error. We compared adjustment methods, including novel approaches, using simulated case-control data. Using a directed acyclic graph framework, we defined six causal scenarios for epidemiologic studies of environmental chemicals measured in urine or serum. The scenarios include variables known to influence creatinine (e.g., age and hydration) or serum lipid levels (e.g., body mass index and recent fat intake). Over a range of true effect sizes, we analyzed each scenario using seven adjustment approaches and estimated the corresponding bias and confidence interval coverage across 1,000 simulated studies. For urinary biomarker measurements, our novel method, which incorporates both covariate-adjusted standardization and the inclusion of creatinine as a covariate in the regression model, had low bias and possessed 95% confidence interval coverage of nearly 95% for most simulated scenarios. For serum biomarker measurements, a similar approach involving standardization plus serum lipid level adjustment generally performed well. To control measurement error bias caused by variations in serum lipids or by urinary diluteness, we recommend improved methods for standardizing exposure concentrations across individuals.

  11. Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models

    ERIC Educational Resources Information Center

    Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

    2015-01-01

    Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…

  12. Adjusting for the Confounding Effects of Treatment Switching-The BREAK-3 Trial: Dabrafenib Versus Dacarbazine.

    PubMed

    Latimer, Nicholas R; Abrams, Keith R; Amonkar, Mayur M; Stapelkamp, Ceilidh; Swann, R Suzanne

    2015-07-01

    Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48-1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, "treatment group" (assumes treatment effect could continue until death) and "on-treatment observed" (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE "treatment group" and "on-treatment observed" analyses performed similarly well. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching-a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Treatment switching is common in oncology trials, and the implications of this for the interpretation of the clinical effectiveness and cost-effectiveness of the novel treatment are important to consider. If

  13. Adjusting for the Confounding Effects of Treatment Switching—The BREAK-3 Trial: Dabrafenib Versus Dacarbazine

    PubMed Central

    Abrams, Keith R.; Amonkar, Mayur M.; Stapelkamp, Ceilidh; Swann, R. Suzanne

    2015-01-01

    Background. Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48–1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Materials and Methods. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, “treatment group” (assumes treatment effect could continue until death) and “on-treatment observed” (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. Results. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE “treatment group” and “on-treatment observed” analyses performed similarly well. Conclusion. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching—a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Implications for Practice: Treatment switching is common in oncology trials, and the implications of this for the interpretation of the

  14. Does School Connectedness Buffer the Impact of Peer Victimization on Early Adolescents' Subsequent Adjustment Problems?

    ERIC Educational Resources Information Center

    Loukas, Alexandra; Pasch, Keryn E.

    2013-01-01

    The current study examined the role of school connectedness as a moderator of the associations between overt and relational forms of peer victimization and early adolescents' subsequent adjustment problems. Data were collected from 490 adolescents when they were initially in the sixth and seventh grades and again 1 year later. Regression analyses…

  15. Assessment of Glacial Isostatic Adjustment in Greenland using GPS

    NASA Astrophysics Data System (ADS)

    Khan, S. A.; Bevis, M. G.; Sasgen, I.; van Dam, T. M.; Wahr, J. M.; Wouters, B.; Bamber, J. L.; Willis, M. J.; Knudsen, P.; Helm, V.; Kuipers Munneke, P.; Muresan, I. S.

    2015-12-01

    The Greenland GPS network (GNET) was constructed to provide a new means to assess viscoelastic and elastic adjustments driven by past and present-day changes in ice mass. Here we assess existing glacial isostatic adjustments (GIA) predictions by analysing 1995-2015 data from 61 continuous GPS receivers located along the margin of the Greenland ice sheet. Since GPS receivers measure both the GIA and elastic signals, we isolate GIA, by removing the elastic adjustments of the lithosphere due to present-day mass changes using high-resolution fields of ice surface elevation change derived from satellite and airborne altimetry measurements (ERS1/2, ICESat, ATM, ENVISAT, and CryoSat-2). For most GPS stations, our observed GIA rates contradict GIA predictions; particularly, we find huge uplift rates in southeast Greenland of up to 14 mm/yr while models predict rates of 0-2 mm/yr. Our results suggest possible improvements of GIA predictions, and hence of the poorly constrained ice load history and Earth structure models for Greenland.

  16. Adjusted hospital death rates: a potential screen for quality of medical care.

    PubMed

    Dubois, R W; Brook, R H; Rogers, W H

    1987-09-01

    Increased economic pressure on hospitals has accelerated the need to develop a screening tool for identifying hospitals that potentially provide poor quality care. Based upon data from 93 hospitals and 205,000 admissions, we used a multiple regression model to adjust the hospitals crude death rate. The adjustment process used age, origin of patient from the emergency department or nursing home, and a hospital case mix index based on DRGs (diagnostic related groups). Before adjustment, hospital death rates ranged from 0.3 to 5.8 per 100 admissions. After adjustment, hospital death ratios ranged from 0.36 to 1.36 per 100 (actual death rate divided by predicted death rate). Eleven hospitals (12 per cent) were identified where the actual death rate exceeded the predicted death rate by more than two standard deviations. In nine hospitals (10 per cent), the predicted death rate exceeded the actual death rate by a similar statistical margin. The 11 hospitals with higher than predicted death rates may provide inadequate quality of care or have uniquely ill patient populations. The adjusted death rate model needs to be validated and generalized before it can be used routinely to screen hospitals. However, the remaining large differences in observed versus predicted death rates lead us to believe that important differences in hospital performance may exist.

  17. 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

  18. Family functioning and children's adjustment: associations among parents' depressed mood, marital hostility, parent-child hostility, and children's adjustment.

    PubMed

    Low, Sabina M; Stocker, Clare

    2005-09-01

    Relations between parents' depressed mood, marital conflict, parent-child hostility, and children's adjustment were examined in a community sample of 136 ten-year-olds and their parents. Videotaped observational and self-report data were used to examine these relations in path analyses. A proposed model was tested in which mothers' and fathers' depressed mood and marital hostility were associated with children's adjustment problems through disruptions in parent-child relationships. Results showed that both mothers' and fathers' marital hostility were linked to parent-child hostility, which in turn was linked to children's internalizing problems. Fathers' depressed mood was linked to children's internalizing problems indirectly through father-child hostility. Fathers' depressed mood was directly linked to children's externalizing problems and indirectly linked through father-child hostility. For mothers, marital hostility was directly linked to children's externalizing problems, and marital hostility in fathers was indirectly linked to children's externalizing problems through father-child hostility. (c) 2005 APA, all rights reserved

  19. Drop-Weight Impact Test on U-Shape Concrete Specimens with Statistical and Regression Analyses

    PubMed Central

    Zhu, Xue-Chao; Zhu, Han; Li, Hao-Ran

    2015-01-01

    According to the principle and method of drop-weight impact test, the impact resistance of concrete was measured using self-designed U-shape specimens and a newly designed drop-weight impact test apparatus. A series of drop-weight impact tests were carried out with four different masses of drop hammers (0.875, 0.8, 0.675 and 0.5 kg). The test results show that the impact resistance results fail to follow a normal distribution. As expected, U-shaped specimens can predetermine the location of the cracks very well. It is also easy to record the cracks propagation during the test. The maximum of coefficient of variation in this study is 31.2%; it is lower than the values obtained from the American Concrete Institute (ACI) impact tests in the literature. By regression analysis, the linear relationship between the first-crack and ultimate failure impact resistance is good. It can suggested that a minimum number of specimens is required to reliably measure the properties of the material based on the observed levels of variation. PMID:28793540

  20. Association of surgical care improvement project infection-related process measure compliance with risk-adjusted outcomes: implications for quality measurement.

    PubMed

    Ingraham, Angela M; Cohen, Mark E; Bilimoria, Karl Y; Dimick, Justin B; Richards, Karen E; Raval, Mehul V; Fleisher, Lee A; Hall, Bruce L; Ko, Clifford Y

    2010-12-01

    Facility-level process measure adherence is being publicly reported. However, the association between measure adherence and surgical outcomes is not well-established. Our objective was to determine the degree to which Surgical Care Improvement Project (SCIP) process measures are associated with American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) risk-adjusted outcomes. This cross-sectional study included hospitals participating in the ACS NSQIP and SCIP (n = 200). ACS NSQIP outcomes (30-day overall morbidity, serious morbidity, surgical site infections [SSI], and mortality) and adherence to SCIP SSI-related process measures (from the Hospital Compare database) were collected from January 1, 2008, through December 31, 2008. Hospital-level correlation coefficients between compliance with 4 process measures (ie, antibiotic administration within 1 hour before incision [SCIP-1]; appropriate antibiotic prophylaxis [SCIP-2]; antibiotic discontinuation within 24 hours after surgery [SCIP-3]; and appropriate hair removal [SCIP 6]) and 4 risk-adjusted outcomes were calculated. Regression analyses estimated the contribution of process measure adherence to risk-adjusted outcomes. Of 211 ACS NSQIP hospitals, 95% had data reported by Hospital Compare. Depending on the measure, hospital-level compliance ranged from 60% to 100%. Of the 16 correlations, 15 demonstrated nonsignificant associations with risk-adjusted outcomes. The exception was the relationship between SCIP-2 and SSI (p = 0.004). SCIP-1 demonstrated an intriguing but nonsignificant relationship with SSI (p = 0.08) and overall morbidity (p = 0.08). Although adherence to SCIP-2 was a significant predictor of risk-adjusted SSI (p < 0.0001) and overall morbidity (p < 0.0001), inclusion of compliance for SCIP-1 and SCIP-2 caused only slight improvement in model quality. Better adherence to infection-related process measures over the observed range was not significantly associated with

  1. Identifying individual changes in performance with composite quality indicators while accounting for regression to the mean.

    PubMed

    Gajewski, Byron J; Dunton, Nancy

    2013-04-01

    Almost a decade ago Morton and Torgerson indicated that perceived medical benefits could be due to "regression to the mean." Despite this caution, the regression to the mean "effects on the identification of changes in institutional performance do not seem to have been considered previously in any depth" (Jones and Spiegelhalter). As a response, Jones and Spiegelhalter provide a methodology to adjust for regression to the mean when modeling recent changes in institutional performance for one-variable quality indicators. Therefore, in our view, Jones and Spiegelhalter provide a breakthrough methodology for performance measures. At the same time, in the interests of parsimony, it is useful to aggregate individual quality indicators into a composite score. Our question is, can we develop and demonstrate a methodology that extends the "regression to the mean" literature to allow for composite quality indicators? Using a latent variable modeling approach, we extend the methodology to the composite indicator case. We demonstrate the approach on 4 indicators collected by the National Database of Nursing Quality Indicators. A simulation study further demonstrates its "proof of concept."

  2. Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

    ERIC Educational Resources Information Center

    Bulcock, J. W.

    The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

  3. Adaptive kernel regression for freehand 3D ultrasound reconstruction

    NASA Astrophysics Data System (ADS)

    Alshalalfah, Abdel-Latif; Daoud, Mohammad I.; Al-Najar, Mahasen

    2017-03-01

    Freehand three-dimensional (3D) ultrasound imaging enables low-cost and flexible 3D scanning of arbitrary-shaped organs, where the operator can freely move a two-dimensional (2D) ultrasound probe to acquire a sequence of tracked cross-sectional images of the anatomy. Often, the acquired 2D ultrasound images are irregularly and sparsely distributed in the 3D space. Several 3D reconstruction algorithms have been proposed to synthesize 3D ultrasound volumes based on the acquired 2D images. A challenging task during the reconstruction process is to preserve the texture patterns in the synthesized volume and ensure that all gaps in the volume are correctly filled. This paper presents an adaptive kernel regression algorithm that can effectively reconstruct high-quality freehand 3D ultrasound volumes. The algorithm employs a kernel regression model that enables nonparametric interpolation of the voxel gray-level values. The kernel size of the regression model is adaptively adjusted based on the characteristics of the voxel that is being interpolated. In particular, when the algorithm is employed to interpolate a voxel located in a region with dense ultrasound data samples, the size of the kernel is reduced to preserve the texture patterns. On the other hand, the size of the kernel is increased in areas that include large gaps to enable effective gap filling. The performance of the proposed algorithm was compared with seven previous interpolation approaches by synthesizing freehand 3D ultrasound volumes of a benign breast tumor. The experimental results show that the proposed algorithm outperforms the other interpolation approaches.

  4. Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

    PubMed

    Bennett, Bradley C; Husby, Chad E

    2008-03-28

    Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

  5. HMO penetration, competition, and risk-adjusted hospital mortality.

    PubMed

    Mukamel, D B; Zwanziger, J; Tomaszewski, K J

    2001-12-01

    HMOs have been shown to have an effect on the care provided directly to their enrollees. They may also influence the care provided to individuals in fee-for-service plans through a spill-over effect. The objective of this study was to investigate the associations among HMO market penetration, HMO and hospital competition, and the quality of care received by Medicare fee-for-service patients measured by risk-adjusted hospital mortality rates. The 1990 data for 1,927 hospitals in 134 metropolitan statistical areas (with five or more hospitals) included Medicare fee-for-service risk-adjusted mortality rates from the Medicare Hospital Information Reports, hospital characteristics from the American Hospital Association annual survey, and HMO market penetration and competition calculated from InterStudy and Group Health Association of America data. Statistical regression techniques were used to identify the associations between HMO market penetration, competition, and risk-adjusted mortality, controlling for other hospital characteristics and region. Higher HMO market penetration and to a lesser degree increased HMO competition were associated with better mortality outcomes for fee-for-service Medicare enrollees. Competition between hospitals did not exhibit a significant association. HMOs may have a spill-over effect on quality of care received by individuals enrolled in fee-for-service plans. These findings may be explained by a positive effect on local practice styles or a preferential selection by HMOs for areas with better hospital care.

  6. HMO penetration, competition, and risk-adjusted hospital mortality.

    PubMed Central

    Mukamel, D B; Zwanziger, J; Tomaszewski, K J

    2001-01-01

    OBJECTIVE: HMOs have been shown to have an effect on the care provided directly to their enrollees. They may also influence the care provided to individuals in fee-for-service plans through a spill-over effect. The objective of this study was to investigate the associations among HMO market penetration, HMO and hospital competition, and the quality of care received by Medicare fee-for-service patients measured by risk-adjusted hospital mortality rates. DATA SOURCES: The 1990 data for 1,927 hospitals in 134 metropolitan statistical areas (with five or more hospitals) included Medicare fee-for-service risk-adjusted mortality rates from the Medicare Hospital Information Reports, hospital characteristics from the American Hospital Association annual survey, and HMO market penetration and competition calculated from InterStudy and Group Health Association of America data. STUDY DESIGN: Statistical regression techniques were used to identify the associations between HMO market penetration, competition, and risk-adjusted mortality, controlling for other hospital characteristics and region. PRINCIPAL FINDINGS: Higher HMO market penetration and to a lesser degree increased HMO competition were associated with better mortality outcomes for fee-for-service Medicare enrollees. Competition between hospitals did not exhibit a significant association. CONCLUSIONS: HMOs may have a spill-over effect on quality of care received by individuals enrolled in fee-for-service plans. These findings may be explained by a positive effect on local practice styles or a preferential selection by HMOs for areas with better hospital care. PMID:11775665

  7. Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

    PubMed

    Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

    2017-04-01

    To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

  8. Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

    PubMed

    Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

    2018-02-01

    1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE < 10.3%. The external data evaluation showed that the models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

  9. NCCS Regression Test Harness

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

    Tharrington, Arnold N.

    2015-09-09

    The NCCS Regression Test Harness is a software package that provides a framework to perform regression and acceptance testing on NCCS High Performance Computers. The package is written in Python and has only the dependency of a Subversion repository to store the regression tests.

  10. Factors Affecting Regression-Discontinuity.

    ERIC Educational Resources Information Center

    Schumacker, Randall E.

    The regression-discontinuity approach to evaluating educational programs is reviewed, and regression-discontinuity post-program mean differences under various conditions are discussed. The regression-discontinuity design is used to determine whether post-program differences exist between an experimental program and a control group. The difference…

  11. A quantile regression model for failure-time data with time-dependent covariates

    PubMed Central

    Gorfine, Malka; Goldberg, Yair; Ritov, Ya’acov

    2017-01-01

    Summary Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297–331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset. PMID:27485534

  12. Adjustment of ionized calcium concentration for serum pH is not a valid marker of calcium homeostasis: implications for identifying individuals at risk of calcium metabolic disorders.

    PubMed

    Lam, Virginie; Dhaliwal, Satvinder S; Mamo, John C

    2013-05-01

    Ionized calcium (iCa) is the biologically active form of this micronutrient. Serum determination of iCa is measured via ion-electrode potentiometry (IEP) and reporting iCa relative to pH 7.4 is normally utilized to avoid the potential confounding effects of ex vivo changes to serum pH. Adjustment of iCa for pH has not been adequately justified. In this study, utilizing carefully standardized protocols for blood collection, the preparation of serum and controlling time of collection-to-analysis, we determined serum iCa and pH utilizing an IEP-analyser hosted at an accredited diagnostic laboratory. Regression analysis of unadjusted-iCa (iCa(raw)) concentration versus pH was described by linear regression and accounted for 37% of serum iCa(raw) variability. iCa(raw) was then expressed at pH 7.4 by either adjusting iCa(raw) based on the linear regression equation describing the association of iCa with serum pH (iCa(regr)) or using IEP coded published normative equations (iCa(pub)). iCa(regr) was comparable to iCa(raw), indicating that blood collection and processing methodologies were sound. However, iCa(pub) yielded values that were significantly lower than iCa(raw). iCa(pub) did not identify 15% subjects who had greater than desirable serum concentration of iCa based on iCa(raw). Sixty percent of subjects with low levels of iCa(raw) were also not detected by iCa(pub). Determination of the kappa value measure of agreement for iCa(raw) versus iCa(pub) showed relatively poor concordance (κ = 0.42). With simple protocols that avoid sampling artefacts, expressing iCa(raw) is likely to be a more valid and physiologically relevant marker of calcium homeostasis than is iCa(pub).

  13. Teasing and social rejection among obese children enrolling in family-based behavioural treatment: effects on psychological adjustment and academic competencies.

    PubMed

    Gunnarsdottir, T; Njardvik, U; Olafsdottir, A S; Craighead, L W; Bjarnason, R

    2012-01-01

    The first objective was to determine the prevalence of psychological maladjustment (emotional and behavioural problems), low academic competencies and teasing/social rejection among obese Icelandic children enrolling in a family-based behavioural treatment. A second objective was to explore the degree to which teasing/social rejection specifically contributes to children's psychological adjustment and academic competencies when controlling for other variables, including demographics, children's physical activity, parental depression and life-stress. Participants were 84 obese children (mean body mass index-standard deviation score=3.11, age range=7.52-13.61 years). Height and weight, demographics and measures of children's psychological adjustment, academic competencies, teasing/social rejection and physical activity were collected from children, parents and teachers. Parental depression and life-stress was self-reported. Over half the children exceeded cutoffs indicating concern on at least one measure of behavioural or emotional difficulties. Children endorsed significant levels of teasing/social rejection, with almost half acknowledging they were not popular with same-gender peers. Parent reports of peer problems were even higher, with over 90% of both boys and girls being rated by their parents as having significant peer difficulties. However, rates of low academic competencies as reported by teachers were not different from those of the general population. In regression analyses controlling for other variables, self-reported teasing/social rejection emerged as a significant contributor to explaining both child psychological adjustment and academic competencies. The results indicate that among obese children enrolled in family-based treatment, self-reported teasing/social rejection is quite high and it is associated with poorer psychological adjustment as well as lower academic competencies. Parent reports corroborate the presence of substantial peer

  14. Child, parent and family factors as predictors of adjustment for siblings of children with a disability.

    PubMed

    Giallo, R; Gavidia-Payne, S

    2006-12-01

    Siblings adjust to having a brother or sister with a disability in diverse ways. This study investigated a range of child, parent and family factors as predictors of sibling adjustment outcomes. Forty-nine siblings (aged 7-16 years) and parents provided information about (1) sibling daily hassles and uplifts; (2) sibling coping; (3) parent stress; (4) parenting; and (5) family resilience. Multiple regression techniques were used. It was found that parent and family factors were stronger predictors of sibling adjustment difficulties than siblings' own experiences of stress and coping. Specifically, socio-economic status, past attendance at a sibling support group, parent stress, family time and routines, family problem-solving and communication, and family hardiness-predicted sibling adjustment difficulties. Finally, siblings' perceived intensity of daily uplifts significantly predicted sibling prosocial behaviour. The results revealed that the family level of risk and resilience factors were better predictors of sibling adjustment than siblings' own experiences of stress and coping resources, highlighting the importance of familial and parental contributions to the sibling adjustment process. The implications of these results for the design of interventions and supports for siblings are discussed.

  15. A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

    PubMed

    Polanczyk, C A; Rohde, L E; Philbin, E A; Di Salvo, T G

    1998-10-01

    Comparative analysis of hospital outcomes requires reliable adjustment for casemix. Although congestive heart failure is one of the most common indications for hospitalization, congestive heart failure casemix adjustment has not been widely studied. The purposes of this study were (1) to describe and validate a new congestive heart failure-specific casemix adjustment index to predict in-hospital mortality and (2) to compare its performance to the Charlson comorbidity index. Data from all 4,608 admissions to the Massachusetts General Hospital from January 1990 to July 1996 with a principal ICD-9-CM discharge diagnosis of congestive heart failure were evaluated. Massachusetts General Hospital patients were randomly divided in a derivation and a validation set. By logistic regression, odds ratios for in-hospital death were computed and weights were assigned to construct a new predictive index in the derivation set. The performance of the index was tested in an internal Massachusetts General Hospital validation set and in a non-Massachusetts General Hospital external validation set incorporating data from all 1995 New York state hospital discharges with a primary discharge diagnosis of congestive heart failure. Overall in-hospital mortality was 6.4%. Based on the new index, patients were assigned to six categories with incrementally increasing hospital mortality rates ranging from 0.5% to 31%. By logistic regression, "c" statistics of the congestive heart failure-specific index (0.83 and 0.78, derivation and validation set) were significantly superior to the Charlson index (0.66). Similar incrementally increasing hospital mortality rates were observed in the New York database with the congestive heart failure-specific index ("c" statistics 0.75). In an administrative database, this congestive heart failure-specific index may be a more adequate casemix adjustment tool to predict hospital mortality in patients hospitalized for congestive heart failure.

  16. Long-term Adjustment After Surviving Open Heart Surgery: The Effect of Using Prayer for Coping Replicated in a Prospective Design

    PubMed Central

    Ai, A. L.; Ladd, K. L.; Peterson, C.; Cook, C. A.; Shearer, M.; Koenig, H. G.

    2010-01-01

    Purpose: Despite the growing evidence for effects of religious factors on cardiac health in general populations, findings are not always consistent in sicker and older populations. We previously demonstrated that short-term negative outcomes (depression and anxiety) among older adults following open heart surgery are partially alleviated when patients employ prayer as part of their coping strategy. The present study examines multifaceted effects of religious factors on long-term postoperative adjustment, extending our previous findings concerning prayer and coping with cardiac disease. Design and Methods: Analyses capitalized on a preoperative survey and medical variables from the Society of Thoracic Surgeons’ National Database of patients undergoing open heart surgery. The current participants completed a mailed survey 30 months after surgery. Two hierarchical regressions were performed to evaluate the extent to which religious factors predicted depression and anxiety, after controlling for key demographics, medical indices, and mental health. Results: Predicting lower levels of depression at the follow-up were preoperative use of prayer for coping, optimism, and hope. Predicting lower levels of anxiety at the follow-up were subjective religiousness, marital status, and hope. Predicting poorer adjustment were reverence in religious contexts, preoperative mental health symptoms, and medical comorbidity. Including optimism and hope in the model did not eliminate effects of religious factors. Several other religious factors had no long-term influences. Implications: The influence of religious factors on the long-term postoperative adjustment is independent and complex, with mediating factors yet to be determined. Future research should investigate mechanisms underlying religion–health relations. PMID:20634280

  17. Maternal acceptance and consistency of discipline as buffers of divorce stressors on children's psychological adjustment problems.

    PubMed

    Wolchik, S A; Wilcox, K L; Tein, J Y; Sandler, I N

    2000-02-01

    This study examines whether two aspects of mothering--acceptance and consistency of discipline--buffer the effect of divorce stressors on adjustment problems in 678 children, ages 8 to 15, whose families had divorced within the past 2 years. Children reported on divorce stressors; both mothers and children reported on mothering and internalizing and externalizing problems. Multiple regressions indicate that for maternal report of mothering, acceptance interacted with divorce stressors in predicting both dimensions of adjustment problems, with the pattern of findings supporting a stress-buffering effect. For child report of mothering, acceptance, consistency of discipline, and divorce stressors interacted in predicting adjustment problems. The relation between divorce stressors and internalizing and externalizing problems is stronger for children who report low acceptance and low consistency of discipline than for children who report either low acceptance and high consistency of discipline or high acceptance and low consistency of discipline. Children reporting high acceptance and high consistency of discipline have the lowest levels of adjustment problems. Implications of these results for understanding variability in children's postdivorce adjustment and interventions for divorced families are discussed.

  18. Uranium Associations with Kidney Outcomes Vary by Urine Concentration Adjustment Method

    PubMed Central

    Shelley, Rebecca; Kim, Nam-Soo; Parsons, Patrick J.; Lee, Byung-Kook; Agnew, Jacqueline; Jaar, Bernard G.; Steuerwald, Amy J.; Matanoski, Genevieve; Fadrowski, Jeffrey; Schwartz, Brian S.; Todd, Andrew C.; Simon, David; Weaver, Virginia M.

    2017-01-01

    Uranium is a ubiquitous metal that is nephrotoxic at high doses. Few epidemiologic studies have examined the kidney filtration impact of chronic environmental exposure. In 684 lead workers environmentally exposed to uranium, multiple linear regression was used to examine associations of uranium measured in a four-hour urine collection with measured creatinine clearance, serum creatinine- and cystatin-C-based estimated glomerular filtration rates, and N-acetyl-β-D-glucosaminidase (NAG). Three methods were utilized, in separate models, to adjust uranium levels for urine concentration - μg uranium/g creatinine; μg uranium/L and urine creatinine as separate covariates; and μg uranium/4 hr. Median urine uranium levels were 0.07 μg/g creatinine and 0.02 μg/4 hr and were highly correlated (rs =0.95). After adjustment, higher ln-urine uranium was associated with lower measured creatinine clearance and higher NAG in models that used urine creatinine to adjust for urine concentration but not in models that used total uranium excreted (μg/4 hr). These results suggest that, in some instances, associations between urine toxicants and kidney outcomes may be statistical, due to the use of urine creatinine in both exposure and outcome metrics, rather than nephrotoxic. These findings support consideration of non-creatinine-based methods of adjustment for urine concentration in nephrotoxicant research. PMID:23591699

  19. Emotional and Meta-Emotional Intelligence as Predictors of Adjustment Problems in Students with Specific Learning Disorders

    ERIC Educational Resources Information Center

    D'Amico, Antonella; Guastaferro, Teresa

    2017-01-01

    The purpose of this study was to analyse adjustment problems in a group of adolescents with a Specific Learning Disorder (SLD), examining to what extent they depend on the severity level of the learning disorder and/or on the individual's level of emotional intelligence. Adjustment problems,, perceived severity levels of SLD, and emotional and…

  20. Understanding poisson regression.

    PubMed

    Hayat, Matthew J; Higgins, Melinda

    2014-04-01

    Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

  1. Parenting and adolescents' psychological adjustment: Longitudinal moderation by adolescents' genetic sensitivity.

    PubMed

    Stocker, Clare M; Masarik, April S; Widaman, Keith F; Reeb, Ben T; Boardman, Jason D; Smolen, Andrew; Neppl, Tricia K; Conger, Katherine J

    2017-10-01

    We examined whether adolescents' genetic sensitivity, measured by a polygenic index score, moderated the longitudinal associations between parenting and adolescents' psychological adjustment. The sample included 323 mothers, fathers, and adolescents (177 female, 146 male; Time 1 [T1] average age = 12.61 years, SD = 0.54 years; Time 2 [T2] average age = 13.59 years, SD = 0.59 years). Parents' warmth and hostility were rated by trained, independent observers using videotapes of family discussions. Adolescents reported their symptoms of anxiety, depressed mood, and hostility at T1 and T2. The results from autoregressive linear regression models showed that adolescents' genetic sensitivity moderated associations between observations of both mothers' and fathers' T1 parenting and adolescents' T2 composite maladjustment, depression, anxiety, and hostility. Compared to adolescents with low genetic sensitivity, adolescents with high genetic sensitivity had worse adjustment outcomes when parenting was low on warmth and high on hostility. When parenting was characterized by high warmth and low hostility, adolescents with high genetic sensitivity had better adjustment outcomes than their counterparts with low genetic sensitivity. The results support the differential susceptibility model and highlight the complex ways that genes and environment interact to influence development.

  2. Regression Model for Light Weight and Crashworthiness Enhancement Design of Automotive Parts in Frontal CAR Crash

    NASA Astrophysics Data System (ADS)

    Bae, Gihyun; Huh, Hoon; Park, Sungho

    This paper deals with a regression model for light weight and crashworthiness enhancement design of automotive parts in frontal car crash. The ULSAB-AVC model is employed for the crash analysis and effective parts are selected based on the amount of energy absorption during the crash behavior. Finite element analyses are carried out for designated design cases in order to investigate the crashworthiness and weight according to the material and thickness of main energy absorption parts. Based on simulations results, a regression analysis is performed to construct a regression model utilized for light weight and crashworthiness enhancement design of automotive parts. An example for weight reduction of main energy absorption parts demonstrates the validity of a regression model constructed.

  3. Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

    PubMed

    Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

    2008-01-01

    This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

  4. A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

    PubMed

    Saunders, Christina T; Blume, Jeffrey D

    2017-10-26

    Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit of only one model reduces the computation time required for complex mediation analyses and permits the use of a rich suite of regression tools that are not easily implemented on a system of three equations, as would be required in the Baron-Kenny framework. Using data from the BRAIN-ICU study, we provide examples to illustrate the advantages of this framework and compare it with the existing approaches. © The Author 2017. Published by Oxford University Press.

  5. 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.

  6. Interrupted time series regression for the evaluation of public health interventions: a tutorial.

    PubMed

    Bernal, James Lopez; Cummins, Steven; Gasparrini, Antonio

    2017-02-01

    Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.

  7. Interrupted time series regression for the evaluation of public health interventions: a tutorial

    PubMed Central

    Bernal, James Lopez; Cummins, Steven; Gasparrini, Antonio

    2017-01-01

    Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design. PMID:27283160

  8. Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses.

    PubMed

    Samdal, Gro Beate; Eide, Geir Egil; Barth, Tom; Williams, Geoffrey; Meland, Eivind

    2017-03-28

    This systematic review aims to explain the heterogeneity in results of interventions to promote physical activity and healthy eating for overweight and obese adults, by exploring the differential effects of behaviour change techniques (BCTs) and other intervention characteristics. The inclusion criteria specified RCTs with ≥ 12 weeks' duration, from January 2007 to October 2014, for adults (mean age ≥ 40 years, mean BMI ≥ 30). Primary outcomes were measures of healthy diet or physical activity. Two reviewers rated study quality, coded the BCTs, and collected outcome results at short (≤6 months) and long term (≥12 months). Meta-analyses and meta-regressions were used to estimate effect sizes (ES), heterogeneity indices (I 2 ) and regression coefficients. We included 48 studies containing a total of 82 outcome reports. The 32 long term reports had an overall ES = 0.24 with 95% confidence interval (CI): 0.15 to 0.33 and I 2  = 59.4%. The 50 short term reports had an ES = 0.37 with 95% CI: 0.26 to 0.48, and I 2  = 71.3%. The number of BCTs unique to the intervention group, and the BCTs goal setting and self-monitoring of behaviour predicted the effect at short and long term. The total number of BCTs in both intervention arms and using the BCTs goal setting of outcome, feedback on outcome of behaviour, implementing graded tasks, and adding objects to the environment, e.g. using a step counter, significantly predicted the effect at long term. Setting a goal for change; and the presence of reporting bias independently explained 58.8% of inter-study variation at short term. Autonomy supportive and person-centred methods as in Motivational Interviewing, the BCTs goal setting of behaviour, and receiving feedback on the outcome of behaviour, explained all of the between study variations in effects at long term. There are similarities, but also differences in effective BCTs promoting change in healthy eating and physical activity and

  9. Psychosocial adjustment and adherence to dialysis treatment regimes.

    PubMed

    Brownbridge, G; Fielding, D M

    1994-12-01

    Sixty children and adolescents in end-stage renal failure who were undergoing either haemodialysis or continuous ambulatory peritoneal dialysis at one of five United Kingdom dialysis centres were assessed on psychosocial adjustment and adherence to their fluid intake, diet and medication regimes. Parental adjustment was also measured and data on sociodemographic and treatment history variables collected. A structured family interview and standardised questionnaire measures of anxiety, depression and behavioural disturbance were used. Multiple measures of treatment adherence were obtained, utilising children's and parents' self-reports, weight gain between dialysis, blood pressure, serum potassium level, blood urea level, dietitians' surveys and consultants' ratings. Correlational analyses showed that low treatment adherence was associated with poor adjustment to diagnosis and dialysis by children and parents (P < 0.01), self-ratings of anxiety and depression in children and parents (P < 0.001), age (adolescents tended to show poorer adherence than younger children, P < 0.001), duration of dialysis (P < 0.05), low family socioeconomic status (P < 0.05) and family structure (P < 0.01). These findings demonstrate the importance of psychosocial care in the treatment of this group of children. Future research should develop and evaluate psychosocial interventions aimed at improving treatment adherence.

  10. 49 CFR 393.53 - Automatic brake adjusters and brake adjustment indicators.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... indicators. 393.53 Section 393.53 Transportation Other Regulations Relating to Transportation (Continued... brake adjustment indicators. (a) Automatic brake adjusters (hydraulic brake systems). Each commercial... vehicle at the time it was manufactured. (c) Brake adjustment indicator (air brake systems). On each...

  11. 49 CFR 393.53 - Automatic brake adjusters and brake adjustment indicators.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... indicators. 393.53 Section 393.53 Transportation Other Regulations Relating to Transportation (Continued... brake adjustment indicators. (a) Automatic brake adjusters (hydraulic brake systems). Each commercial... vehicle at the time it was manufactured. (c) Brake adjustment indicator (air brake systems). On each...

  12. Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

    PubMed

    Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

    2015-01-01

    Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

  13. Epidemiologic programs for computers and calculators. A microcomputer program for multiple logistic regression by unconditional and conditional maximum likelihood methods.

    PubMed

    Campos-Filho, N; Franco, E L

    1989-02-01

    A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.

  14. Synthesizing US Colonial Climate: Available Data and a "Proxy Adjustment" Method

    NASA Astrophysics Data System (ADS)

    Zalzal, K. S.; Munoz-Hernandez, A.; Arrigo, J. S.

    2008-12-01

    Climate and its variability is a primary driver of hydrologic systems. A paucity of instrumental data makes reconstructing seventeenth- and eighteenth-century climatic conditions along the Northeast corridor difficult, yet this information is necessary if we are to understand the conditions, changes and interactions society had with hydrosystems during this first period of permanent European settlement. For this period (approx. 1600- 1800) there are instrumental records for some regions such as annual temperature and precipitation data for Philadelphia beginning in 1738; Cambridge, Mass., from 1747-1776; and temperature for New Haven, Conn., from 1780 to 1800. There are also paleorecords, including tree-rings analyses and sediment core examinations of pollen and overwash deposits, and historical accounts of extreme weather events. Our analyses of these data show that correlating even the available data is less than straightforward. To produce a "best track" climate record, we introduce a new method of "paleoadjustment" as a means to characterize climate statistical properties as opposed to a strict reconstruction. Combining the instrumented record with the paleorecord, we estimated two sets of climate forcings to use in colonial hydrology study. The first utilized a recent instrumented record (1817-1917) from Baltimore, Md, statistically adjusted in 20-year windows to match trends in the paleorecords and anecdotal evidence from the Middle Colonies and Chesapeake Bay region. The second was a regression reconstruction for New England using climate indices developed from journal records and the Cambridge, Mass., instrumental record. The two climate reconstructions were used to compute the annual potential water yield over the 200-year period of interest. A comparison of these results allowed us to make preliminary conclusions regarding the effect of climate on hydrology during the colonial period. We contend that an understanding of historical hydrology will improve

  15. Unitary Response Regression Models

    ERIC Educational Resources Information Center

    Lipovetsky, S.

    2007-01-01

    The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

  16. Development of a Mentoring Program for Chinese Immigrant Adolescents' Cultural Adjustment

    ERIC Educational Resources Information Center

    Yeh, Christine J.; Ching, Alison M.; Okubo, Yuki; Luthar, Suniya S.

    2007-01-01

    The development and evaluation of a peer mentoring program for Chinese immigrant adolescents' cultural adjustment is described. Twenty-three high school students who recently immigrated from Mainland China participated in the year-long program and 4 high school students served as their peer mentors. Data analyses revealed that the students who…

  17. Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

    PubMed

    Brenn, T; Arnesen, E

    1985-01-01

    For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

  18. An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

    NASA Astrophysics Data System (ADS)

    Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

    2018-03-01

    In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

  19. Femoral anteversion and tibial torsion only explain 25% of variance in regression analysis of foot progression angle in children with diplegic cerebral palsy

    PubMed Central

    2013-01-01

    Background The relationship between torsional bony deformities and rotational gait parameters has not been sufficiently investigated. This study was to investigate the degree of contribution of torsional bony deformities to rotational gait parameters in patients with diplegic cerebral palsy (CP). Methods Thirty three legs from 33 consecutive ambulatory patients (average age 9.5 years, SD 6.9 years; 20 males and 13 females) with diplegic CP who underwent preoperative three dimensional gait analysis, foot radiographs, and computed tomography (CT) were included. Adjusted foot progression angle (FPA) was retrieved from gait analysis by correcting pelvic rotation from conventional FPA, which represented the rotational gait deviation of the lower extremity from the tip of the femoral head to the foot. Correlations between rotational gait parameters (FPA, adjusted FPA, average pelvic rotation, average hip rotation, and average knee rotation) and radiologic measurements (acetabular version, femoral anteversion, knee torsion, tibial torsion, and anteroposteriortalo-first metatarsal angle) were analyzed. Multiple regression analysis was performed to identify significant contributing radiographic measurements to adjusted FPA. Results Adjusted FPA was significantly correlated with FPA (r=0.837, p<0.001), contralateral FPA (r=0.492, p=0.004), pelvic rotation during gait (r=−0.489, p=0.004), knee rotation during gait (r=0.376, p=0.031), and femoral anteversion (r=0.350, p=0.046). In multiple regression analysis, femoral anteversion (p=0.026) and tibial torsion (p=0.034) were found to be the significant contributing structural deformities to the adjusted FPA (R2=0.247). Conclusions Femoral anteversion and tibial torsion were found to be the significant structural deformities that could affect adjusted FPA in patients with diplegic CP. Femoral anteversion and tibial torsion could explain only 24.7% of adjusted FPA. PMID:23767833

  20. Interparental violence and children's long-term psychosocial adjustment: the mediating role of parenting practices.

    PubMed

    Gámez-Guadix, Manuel; Almendros, Carmen; Carrobles, José Antonio; Muñoz-Rivas, Marina

    2012-03-01

    The objectives of this study were: (a) to examine the direct and indirect relationships among witnessing interparental violence, parenting practices, and children's long-term psychosocial adjustment; (b) to analyze the possible gender differences in the relationships specified. The sample consisted of 1295 Spanish university students (M age = 21.21, SD = 4.04). We performed statistical analyses using structural equation modeling. The results showed that witnessing parental violence as a child is related to poor long-term psychosocial adjustment during the child's adult years. Furthermore, we found that parenting practices fully mediated the relation between witnessing interparental violence and the child's long-term adjustment. The multigroup analyses showed that most of the relations among the variables did not differ significantly by gender. However, the relation between harsh discipline and antisocial behavior was stronger for males, whereas the relation between harsh discipline and depressive symptoms was stronger for females. Finally, we discuss the implications of these findings for the clinicians and specialists who plan and develop intervention programs for populations at risk.

  1. Nonresident Fathers' Parenting Style and the Adjustment of Late-Adolescent Boys

    ERIC Educational Resources Information Center

    Karre, Jennifer K.; Mounts, Nina S.

    2012-01-01

    This study investigates the relation between nonresident fathers' parenting style, mothers' parenting style and behaviors, and depression and antisocial behavior in a sample of late-adolescent boys (n = 177). Hierarchical regression analyses were performed. Maternal psychological well-being was associated with fewer adolescent depression symptoms.…

  2. Neuromagnetic brain activity associated with anticipatory postural adjustments for bimanual load lifting.

    PubMed

    Ng, Tommy H B; Sowman, Paul F; Brock, Jon; Johnson, Blake W

    2013-02-01

    During bimanual load lifting, the brain must anticipate the effects of unloading upon the load-bearing arm. Little is currently known about the neural networks that coordinate these anticipatory postural adjustments. We measured neuromagnetic brain activity with whole-head magnetoencephalography while participants performed a bimanual load-lifting task. Anticipatory adjustments were associated with reduction in biceps brachii muscle activity of the load-bearing arm and pre-movement desynchronization of the cortical beta rhythm. Beamforming analyses localized anticipatory brain activity to the precentral gyrus, basal ganglia, supplementary motor area, and thalamus, contralateral to the load-bearing arm. To our knowledge this is the first human neuroimaging study to directly investigate anticipatory postural adjustments and to explicitly partition the anticipatory and volitional aspects of brain activity in bimanual load lifting. These data contribute to our understanding of the neural systems supporting anticipatory postural adjustments in healthy adults. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Quality of pancreatic transplant program assessment using a risk-adjusted cumulative sum chart: experience from a single, small center.

    PubMed

    Grochowiecki, T; Jakimowicz, T; Grabowska-Derlatka, L; Szmidt, J

    2014-10-01

    The high rate of complication after pancreas transplantation not only had an impact on recipient quality of life and survival but also had significant financial implications. Thus, monitoring transplant center performance was crucial to indentifying changes in clinical practice that result in quality deterioration. To evaluate retrospectively the quality of the single, small pancreatic transplant program and to establish prospective monitoring of the center using risk-adjusted cumulative sum (CUSUM). From 1988 to 2014, 119 simultaneous pancreas and the kidney transplantations (SPKTx) were performed. The program was divided into 3 eras, based on surgical technique and immunosuppression. Analyses of the 15 fatal outcomes due to complication from pancreatic graft were performed. The risk model was developed using multivariable logistic regression analysis based on retrospective data of 112 SPKTx recipients. The risk-adjusted 1-sided CUSUM chart was plotted for retrospective and prospective events. The upper control limit was set to 2. There were 2 main causes of death: multiorgan failure (73.3%; 11/15) and septic hemorrhage (26.7%; 4/15). Quality analysis using the CUSUM chart revealed that the process was not homogeneous; however, no significant signal of program deterioration was obtained and the performance of the whole program was within the settled control limit. For a single pancreatic transplant center. The risk-adjusted CUSUM chart was a useful tool for quality program assessment. It could support decision making during traditional surgical morbidity and mortality conferences. For small transplant centers, increasing the sensitivity of the CUSUM method by lowering the upper control limit should be considered. However, an individual assessment approach of the for particular centers is recommended.

  4. Quantile regression analyses of associated factors for body mass index in Korean adolescents.

    PubMed

    Kim, T H; Lee, E K; Han, E

    2015-05-01

    This study examined the influence of home and school environments, and individual health-risk behaviours on body weight outcomes in Korean adolescents. This was a cross-sectional observational study. Quantile regression models to explore heterogeneity in the association of specific factors with body mass index (BMI) over the entire conditional BMI distribution was used. A nationally representative web-based survey for youths was used. Paternal education level of college or more education was associated with lower BMI for girls, whereas college or more education of mothers was associated with higher BMI for boys; for both, the magnitude of association became larger at the upper quantiles of the conditional BMI distribution. Girls with good family economic status were more likely to have higher BMIs than those with average family economic status, particularly at the upper quantile of the conditional BMI distribution. Attending a co-ed school was associated with lower BMI for both genders with a larger association at the upper quantiles. Substantial screen time for TV watching, video games, or internet surfing was associated with a higher BMI with a larger association at the upper quantiles for both girls and boys. Dental prevention was negatively associated with BMI, whereas suicide consideration was positively associated with BMIs of both genders with a larger association at a higher quantile. These findings suggest that interventions aimed at behavioural changes and positive parental roles are needed to effectively address high adolescent BMI. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  5. Predictors of unsuccessful outcome in cemented femoral revisions using bone impaction grafting; Cox regression analysis of 208 cases.

    PubMed

    Te Stroet, Martijn A J; Rijnen, Wim H C; Gardeniers, Jean W M; Schreurs, B Willem; Hannink, Gerjon

    2016-09-29

    Despite improvements in the technique of femoral impaction bone grafting, reconstruction failures still can occur. Therefore, the aim of our study was to determine risk factors for the endpoint re-revision for any reason. We used prospectively collected demographic, clinical and surgical data of all 202 patients who underwent 208 femoral revisions using the X-change Femoral Revision System (Stryker-Howmedica), fresh-frozen morcellised allograft and a cemented polished Exeter stem in our department from 1991 to 2007. Univariable and multivariable Cox regression analyses were performed to identify potential factors associated with re-revision. The mean follow-up was 10.6 (5-21) years. The cumulative re-revision rate was 6.3% (13/208). After univariable selection, sex, age, body mass index (BMI), American Association of Anesthesiologists (ASA) classification, type of removed femoral component, and mesh used for reconstruction were included in multivariable regression analysis.In the multivariable analysis, BMI was the only factor that was significantly associated with the risk of re-revision after bone impaction grafting (BMI ≥30 vs. BMI <30, HR = 6.54 [95% CI 1.89-22.65]; p = 0.003). BMI was the only factor associated with the risk of re-revision for any reason. Besides BMI also other factors, such as Endoklinik score and the type of removed femoral component, can provide guidance in the process of preclinical decision making. With the knowledge obtained from this study, preoperative patient selection, informed consent, and treatment protocols can be better adjusted to the individual patient who needs to undergo a femoral revision with impaction bone grafting.

  6. Correlation and simple linear regression.

    PubMed

    Eberly, Lynn E

    2007-01-01

    This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

  7. Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

    PubMed Central

    Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

    2017-01-01

    Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

  8. Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches.

    PubMed

    Valle, Denis; Lima, Joanna M Tucker; Millar, Justin; Amratia, Punam; Haque, Ubydul

    2015-11-04

    Logistic regression is a statistical model widely used in cross-sectional and cohort studies to identify and quantify the effects of potential disease risk factors. However, the impact of imperfect tests on adjusted odds ratios (and thus on the identification of risk factors) is under-appreciated. The purpose of this article is to draw attention to the problem associated with modelling imperfect diagnostic tests, and propose simple Bayesian models to adequately address this issue. A systematic literature review was conducted to determine the proportion of malaria studies that appropriately accounted for false-negatives/false-positives in a logistic regression setting. Inference from the standard logistic regression was also compared with that from three proposed Bayesian models using simulations and malaria data from the western Brazilian Amazon. A systematic literature review suggests that malaria epidemiologists are largely unaware of the problem of using logistic regression to model imperfect diagnostic test results. Simulation results reveal that statistical inference can be substantially improved when using the proposed Bayesian models versus the standard logistic regression. Finally, analysis of original malaria data with one of the proposed Bayesian models reveals that microscopy sensitivity is strongly influenced by how long people have lived in the study region, and an important risk factor (i.e., participation in forest extractivism) is identified that would have been missed by standard logistic regression. Given the numerous diagnostic methods employed by malaria researchers and the ubiquitous use of logistic regression to model the results of these diagnostic tests, this paper provides critical guidelines to improve data analysis practice in the presence of misclassification error. Easy-to-use code that can be readily adapted to WinBUGS is provided, enabling straightforward implementation of the proposed Bayesian models.

  9. Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

    PubMed Central

    Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

    2015-01-01

    Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

  10. Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

    PubMed

    Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

    2015-01-01

    Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

  11. Requirement for specific gravity and creatinine adjustments for urinary steroids and luteinizing hormone concentrations in adolescents.

    PubMed

    Singh, Gurmeet K S; Balzer, Ben W R; Desai, Reena; Jimenez, Mark; Steinbeck, Katharine S; Handelsman, David J

    2015-11-01

    Urinary hormone concentrations are often adjusted to correct for hydration status. We aimed to determine whether first morning void urine hormones in growing adolescents require adjustments and, if so, whether urinary creatinine or specific gravity are better adjustments. The study population was adolescents aged 10.1 to 14.3 years initially who provided fasting morning blood samples at 0 and 12 months (n = 343) and first morning urine every three months (n = 644). Unadjusted, creatinine and specific gravity-adjusted hormonal concentrations were compared by Deming regression and Bland-Altman analysis and grouped according to self-rated Tanner stage or chronological age. F-ratios for self-rated Tanner stages and age groups were used to compare unadjusted and adjusted hormonal changes in growing young adolescents. Correlations of paired serum and urinary hormonal concentration of unadjusted and creatinine and specific gravity-adjusted were also compared. Fasting first morning void hormone concentrations correlated well and were unbiased between unadjusted or adjusted by either creatinine or specific gravity. Urine creatinine concentration increases with Tanner stages, age and male gender whereas urine specific gravity was not influenced by Tanner stage, age or gender. Adjustment by creatinine or specific gravity of urinary luteinizing hormone, estradiol, testosterone, dihydrotestosterone and dehydroepiandrosterone concentrations did not improve correlation with paired serum concentrations. Urine steroid and luteinizing hormone concentrations in first morning void samples of adolescents are not significantly influenced by hydration status and may not require adjustments; however, if desired, both creatinine and specific gravity adjustments are equally suitable. © The Author(s) 2015.

  12. The necessity of sociodemographic status adjustment in hospital value rankings for perforated appendicitis in children.

    PubMed

    Tian, Yao; Sweeney, John F; Wulkan, Mark L; Heiss, Kurt F; Raval, Mehul V

    2016-06-01

    Hospitals are increasingly focused on demonstration of high-value care for common surgical procedures. Although sociodemographic status (SDS) factors have been tied to various surgical outcomes, the impact of SDS factors on hospital value rankings has not been well explored. Our objective was to examine effects of SDS factors on high-value surgical care at the patient level, and to illustrate the importance of SDS adjustment when evaluating hospital-level performance. Perforated appendicitis hospitalizations were identified from the 2012 Kids' Inpatient Database. The primary outcome of interest was high-value care as defined by evaluation of duration of stay and cost. SDS factors included race, health insurance type, median household income, and patient location. The impact of SDS on high-value care was estimated using regression models after accounting for hospital-level variation. Risk-adjusted value rankings were compared before and after adjustment for SDS. From 9,986 hospitalizations, 998 high-value encounters were identified. African Americans were less likely to experience high-value care compared with white patients after adjusting for all SDS variables. Although private insurance and living in nonmetro counties were associated independently with high-value care, the effects were attenuated in the fully adjusted models. For the 136 hospitals ranked according to risk-adjusted value status, 59 hospitals' rankings improved after adjustment and 53 hospitals' rankings declined. After adjustment for patient and hospital factors, SDS has a small but significant impact on risk-adjusted hospital performance ranking for pediatric appendicitis. Adjustment for SDS should be considered in future comparative performance assessment. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Magnetically adjustable intraocular lens.

    PubMed

    Matthews, Michael Wayne; Eggleston, Harry Conrad; Pekarek, Steven D; Hilmas, Greg Eugene

    2003-11-01

    To provide a noninvasive, magnetic adjustment mechanism to the repeatedly and reversibly adjustable, variable-focus intraocular lens (IOL). University of Missouri-Rolla, Rolla, and Eggleston Adjustable Lens, St. Louis, Missouri, USA. Mechanically adjustable IOLs have been fabricated and tested. Samarium and cobalt rare-earth magnets have been incorporated into the poly(methyl methacrylate) (PMMA) optic of these adjustable lenses. The stability of samarium and cobalt in the PMMA matrix was examined with leaching studies. Operational force testing of the magnetic optics with emphasis on the rotational forces of adjustment was done. Prototype optics incorporating rare-earth magnetic inserts were consistently produced. After 32 days in solution, samarium and cobalt concentration reached a maximum of 5 ppm. Operational force measurements indicate that successful adjustments of this lens can be made using external magnetic fields with rotational torques in excess of 0.6 ounce inch produced. Actual lenses were remotely adjusted using magnetic fields. The magnetically adjustable version of this IOL is a viable and promising means of handling the common issues of postoperative refractive errors without the requirement of additional surgery. The repeatedly adjustable mechanism of this lens also holds promise for the developing eyes of pediatric patients and the changing needs of all patients.

  14. Environmental Chemicals in Urine and Blood: Improving Methods for Creatinine and Lipid Adjustment

    PubMed Central

    O’Brien, Katie M.; Upson, Kristen; Cook, Nancy R.; Weinberg, Clarice R.

    2015-01-01

    Background Investigators measuring exposure biomarkers in urine typically adjust for creatinine to account for dilution-dependent sample variation in urine concentrations. Similarly, it is standard to adjust for serum lipids when measuring lipophilic chemicals in serum. However, there is controversy regarding the best approach, and existing methods may not effectively correct for measurement error. Objectives We compared adjustment methods, including novel approaches, using simulated case–control data. Methods Using a directed acyclic graph framework, we defined six causal scenarios for epidemiologic studies of environmental chemicals measured in urine or serum. The scenarios include variables known to influence creatinine (e.g., age and hydration) or serum lipid levels (e.g., body mass index and recent fat intake). Over a range of true effect sizes, we analyzed each scenario using seven adjustment approaches and estimated the corresponding bias and confidence interval coverage across 1,000 simulated studies. Results For urinary biomarker measurements, our novel method, which incorporates both covariate-adjusted standardization and the inclusion of creatinine as a covariate in the regression model, had low bias and possessed 95% confidence interval coverage of nearly 95% for most simulated scenarios. For serum biomarker measurements, a similar approach involving standardization plus serum lipid level adjustment generally performed well. Conclusions To control measurement error bias caused by variations in serum lipids or by urinary diluteness, we recommend improved methods for standardizing exposure concentrations across individuals. Citation O’Brien KM, Upson K, Cook NR, Weinberg CR. 2016. Environmental chemicals in urine and blood: improving methods for creatinine and lipid adjustment. Environ Health Perspect 124:220–227; http://dx.doi.org/10.1289/ehp.1509693 PMID:26219104

  15. Bootstrap investigation of the stability of a Cox regression model.

    PubMed

    Altman, D G; Andersen, P K

    1989-07-01

    We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.

  16. Future Orientation, Social Support, and Psychological Adjustment among Left-behind Children in Rural China: A Longitudinal Study.

    PubMed

    Su, Shaobing; Li, Xiaoming; Lin, Danhua; Zhu, Maoling

    2017-01-01

    Existing research has found that parental migration may negatively impact the psychological adjustment of left-behind children. However, limited longitudinal research has examined if and how future orientation (individual protective factor) and social support (contextual protective factor) are associated with the indicators of psychological adjustment (i.e., life satisfaction, school satisfaction, happiness, and loneliness) of left-behind children. In the current longitudinal study, we examined the differences in psychological adjustment between left-behind children and non-left behind children (comparison children) in rural areas, and explored the protective roles of future orientation and social support on the immediate (cross-sectional effects) and subsequent (lagged effects) status of psychological adjustment for both groups of children, respectively. The sample included 897 rural children ( M age = 14.09, SD = 1.40) who participated in two waves of surveys across six months. Among the participants, 227 were left-behind children with two parents migrating, 176 were with one parent migrating, and 485 were comparison children. Results showed that, (1) left-behind children reported lower levels of life satisfaction, school satisfaction, and happiness, as well as a higher level of loneliness in both waves; (2) After controlling for several demographics and characteristics of parental migration among left-behind children, future orientation significantly predicted life satisfaction, school satisfaction, and happiness in both cross-sectional and longitudinal regression models, as well as loneliness in the longitudinal regression analysis. Social support predicted immediate life satisfaction, school satisfaction, and happiness, as well as subsequent school satisfaction. Similar to left-behind children, comparison children who reported higher scores in future orientation, especially future expectation, were likely to have higher scores in most indicators of

  17. Error Covariance Penalized Regression: A novel multivariate model combining penalized regression with multivariate error structure.

    PubMed

    Allegrini, Franco; Braga, Jez W B; Moreira, Alessandro C O; Olivieri, Alejandro C

    2018-06-29

    A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS). Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Orthogonal Regression: A Teaching Perspective

    ERIC Educational Resources Information Center

    Carr, James R.

    2012-01-01

    A well-known approach to linear least squares regression is that which involves minimizing the sum of squared orthogonal projections of data points onto the best fit line. This form of regression is known as orthogonal regression, and the linear model that it yields is known as the major axis. A similar method, reduced major axis regression, is…

  19. Personal, social, and game-related correlates of active and non-active gaming among dutch gaming adolescents: survey-based multivariable, multilevel logistic regression analyses.

    PubMed

    Simons, Monique; de Vet, Emely; Chinapaw, Mai Jm; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-04-04

    Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games-active games-seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; P<.001), a less positive attitude toward non-active games (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; P<.001) and friends (OR 3.4, CI 1.4-8.4; P=.009) who spend more time on active gaming and a little bit lower score on game engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P<.001), having friends who spend more time on non-active gaming (OR 3.3, CI 1.46-7.53; P=.004), and a more positive image of a non-active gamer (OR 2, CI 1.07-3.75; P=.03). Various factors were significantly associated with active gaming ≥1 h/wk and non-active gaming >7 h/wk. Active gaming is most strongly (negatively) associated with attitude with

  20. Whole genome sequence analyses of brain imaging measures in the Framingham Study.

    PubMed

    Sarnowski, Chloé; Satizabal, Claudia L; DeCarli, Charles; Pitsillides, Achilleas N; Cupples, L Adrienne; Vasan, Ramachandran S; Wilson, James G; Bis, Joshua C; Fornage, Myriam; Beiser, Alexa S; DeStefano, Anita L; Dupuis, Josée; Seshadri, Sudha

    2018-01-16

    We sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program. We performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants. We detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, p = 10 -8 ) and in 16q23 for hippocampal volume (MAF 0.05, p = 2.7 × 10 -8 ). Previously identified associations in 12q24 for hippocampal volume (rs7294919, p = 4.4 × 10 -4 ) and in 17q25 for WMH (rs7214628, p = 2.0 × 10 -3 ) were confirmed. Gene-based tests detected associations ( p ≤ 2.3 × 10 -6 ) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease- ( UNC5D ) and Parkinson disease-associated genes ( GBA ). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways. Whole genome sequence-wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings. Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

  1. Return period adjustment for runoff coefficients based on analysis in undeveloped Texas watersheds

    USGS Publications Warehouse

    Dhakal, Nirajan; Fang, Xing; Asquith, William H.; Cleveland, Theodore G.; Thompson, David B.

    2013-01-01

    The rational method for peak discharge (Qp) estimation was introduced in the 1880s. The runoff coefficient (C) is a key parameter for the rational method that has an implicit meaning of rate proportionality, and the C has been declared a function of the annual return period by various researchers. Rate-based runoff coefficients as a function of the return period, C(T), were determined for 36 undeveloped watersheds in Texas using peak discharge frequency from previously published regional regression equations and rainfall intensity frequency for return periods T of 2, 5, 10, 25, 50, and 100 years. The C(T) values and return period adjustments C(T)/C(T=10  year) determined in this study are most applicable to undeveloped watersheds. The return period adjustments determined for the Texas watersheds in this study and those extracted from prior studies of non-Texas data exceed values from well-known literature such as design manuals and textbooks. Most importantly, the return period adjustments exceed values currently recognized in Texas Department of Transportation design guidance when T>10  years.

  2. The mechanical properties of high speed GTAW weld and factors of nonlinear multiple regression model under external transverse magnetic field

    NASA Astrophysics Data System (ADS)

    Lu, Lin; Chang, Yunlong; Li, Yingmin; He, Youyou

    2013-05-01

    A transverse magnetic field was introduced to the arc plasma in the process of welding stainless steel tubes by high-speed Tungsten Inert Gas Arc Welding (TIG for short) without filler wire. The influence of external magnetic field on welding quality was investigated. 9 sets of parameters were designed by the means of orthogonal experiment. The welding joint tensile strength and form factor of weld were regarded as the main standards of welding quality. A binary quadratic nonlinear regression equation was established with the conditions of magnetic induction and flow rate of Ar gas. The residual standard deviation was calculated to adjust the accuracy of regression model. The results showed that, the regression model was correct and effective in calculating the tensile strength and aspect ratio of weld. Two 3D regression models were designed respectively, and then the impact law of magnetic induction on welding quality was researched.

  3. Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

    PubMed

    Chen, Yanguang

    2016-01-01

    In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

  4. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    NASA Astrophysics Data System (ADS)

    Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

    2017-03-01

    This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  5. Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

    PubMed Central

    Chen, Yanguang

    2016-01-01

    In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

  6. Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

    PubMed

    Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

    2017-06-01

    We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Regional abundance of on-premise outlets and drinking patterns among Swiss young men: district level analyses and geographic adjustments.

    PubMed

    Astudillo, Mariana; Kuendig, Hervé; Centeno-Gil, Adriana; Wicki, Matthias; Gmel, Gerhard

    2014-09-01

    This study investigated the associations of alcohol outlet density with specific alcohol outcomes (consumption and consequences) among young men in Switzerland and assessed the possible geographically related variations. Alcohol consumption and drinking consequences were measured in a 2010-2011 study assessing substance use risk factors (Cohort Study on Substance Use Risk Factors) among 5519 young Swiss men. Outlet density was based on the number of on- and off-premise outlets in the district of residence. Linear regression models were run separately for drinking level, heavy episodic drinking (HED) and drinking consequences. Geographically weighted regression models were estimated when variations were recorded at the district level. No consistent association was found between outlet density and drinking consequences. A positive association between drinking level and HED with on-premise outlet density was found. Geographically weighted regressions were run for drinking level and HED. The predicted values for HED were higher in the southwest part of Switzerland (French-speaking part). Among Swiss young men, the density of outlets and, in particular, the abundance of bars, clubs and other on-premise outlets was associated with drinking level and HED, even when drinking consequences were not significantly affected. These findings support the idea that outlet density needs to be considered when developing and implementing regional-based prevention initiatives. © 2014 Australasian Professional Society on Alcohol and other Drugs.

  8. Real time monitoring of risk-adjusted paediatric cardiac surgery outcomes using variable life-adjusted display: implementation in three UK centres

    PubMed Central

    Pagel, Christina; Utley, Martin; Crowe, Sonya; Witter, Thomas; Anderson, David; Samson, Ray; McLean, Andrew; Banks, Victoria; Tsang, Victor; Brown, Katherine

    2013-01-01

    Objective To implement routine in-house monitoring of risk-adjusted 30-day mortality following paediatric cardiac surgery. Design Collaborative monitoring software development and implementation in three specialist centres. Patients and methods Analyses incorporated 2 years of data routinely audited by the National Institute of Cardiac Outcomes Research (NICOR). Exclusion criteria were patients over 16 or undergoing non-cardiac or only catheter procedures. We applied the partial risk adjustment in surgery (PRAiS) risk model for death within 30 days following surgery and generated variable life-adjusted display (VLAD) charts for each centre. These were shared with each clinical team and feedback was sought. Results Participating centres were Great Ormond Street Hospital, Evelina Children's Hospital and The Royal Hospital for Sick Children in Glasgow. Data captured all procedures performed between 1 January 2010 and 31 December 2011. This incorporated 2490 30-day episodes of care, 66 of which were associated with a death within 30 days.The VLAD charts generated for each centre displayed trends in outcomes benchmarked to recent national outcomes. All centres ended the 2-year period within four deaths from what would be expected. The VLAD charts were shared in multidisciplinary meetings and clinical teams reported that they were a useful addition to existing quality assurance initiatives. Each centre is continuing to use the prototype software to monitor their in-house surgical outcomes. Conclusions Timely and routine monitoring of risk-adjusted mortality following paediatric cardiac surgery is feasible. Close liaison with hospital data managers as well as clinicians was crucial to the success of the project. PMID:23564473

  9. A new approach to correct the QT interval for changes in heart rate using a nonparametric regression model in beagle dogs.

    PubMed

    Watanabe, Hiroyuki; Miyazaki, Hiroyasu

    2006-01-01

    Over- and/or under-correction of QT intervals for changes in heart rate may lead to misleading conclusions and/or masking the potential of a drug to prolong the QT interval. This study examines a nonparametric regression model (Loess Smoother) to adjust the QT interval for differences in heart rate, with an improved fitness over a wide range of heart rates. 240 sets of (QT, RR) observations collected from each of 8 conscious and non-treated beagle dogs were used as the materials for investigation. The fitness of the nonparametric regression model to the QT-RR relationship was compared with four models (individual linear regression, common linear regression, and Bazett's and Fridericia's correlation models) with reference to Akaike's Information Criterion (AIC). Residuals were visually assessed. The bias-corrected AIC of the nonparametric regression model was the best of the models examined in this study. Although the parametric models did not fit, the nonparametric regression model improved the fitting at both fast and slow heart rates. The nonparametric regression model is the more flexible method compared with the parametric method. The mathematical fit for linear regression models was unsatisfactory at both fast and slow heart rates, while the nonparametric regression model showed significant improvement at all heart rates in beagle dogs.

  10. Incremental Treatment Costs Attributable to Overweight and Obesity in Patients with Diabetes: Quantile Regression Approach.

    PubMed

    Lee, Seung-Mi; Choi, In-Sun; Han, Euna; Suh, David; Shin, Eun-Kyung; Je, Seyunghe; Lee, Sung Su; Suh, Dong-Churl

    2018-01-01

    This study aimed to estimate treatment costs attributable to overweight and obesity in patients with diabetes who were less than 65 years of age in the United States. This study used data from the Medical Expenditure Panel Survey from 2001 to 2013. Patients with diabetes were identified by using the International Classification of Diseases, Ninth Revision, Clinical Modification code (250), clinical classification codes (049 and 050), or self-reported physician diagnoses. Total treatment costs attributable to overweight and obesity were calculated as the differences in the adjusted costs compared with individuals with diabetes and normal weight. Adjusted costs were estimated by using generalized linear models or unconditional quantile regression models. The mean annual treatment costs attributable to obesity were $1,852 higher than those attributable to normal weight, while costs attributable to overweight were $133 higher. The unconditional quantile regression results indicated that the impact of obesity on total treatment costs gradually became more significant as treatment costs approached the upper quantile. Among patients with diabetes who were less than 65 years of age, patients with diabetes and obesity have significantly higher treatment costs than patients with diabetes and normal weight. The economic burden of diabetes to society will continue to increase unless more proactive preventive measures are taken to effectively treat patients with overweight or obesity. © 2017 The Obesity Society.

  11. Logic regression and its extensions.

    PubMed

    Schwender, Holger; Ruczinski, Ingo

    2010-01-01

    Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

  12. A Longitudinal Study of Perceived Family Adjustment and Emotional Adjustment in Early Adolescence.

    ERIC Educational Resources Information Center

    Ohannessian, Christine McCauley; And Others

    1994-01-01

    Examined the predictive relationship between family adjustment and emotional adjustment during early adolescence and the influence of adolescents' levels of self-worth, peer support, and coping abilities. Found that family adjustment and emotional adjustment are reciprocally related and that high levels of self-worth, peer support, and coping…

  13. Age adjustment in ecological studies: using a study on arsenic ingestion and bladder cancer as an example.

    PubMed

    Guo, How-Ran

    2011-10-20

    Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example. A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.

  14. Bias in Self-Perceptions and Internalizing and Externalizing Problems in Adjustment During Early Adolescence: A Prospective Investigation

    ERIC Educational Resources Information Center

    DuBois, David L.; Silverthorn, Naida

    2004-01-01

    We investigated bias in self-perceptions of competence (relative to parent ratings) for family, school, and peer domains as predictors of adjustment problems among 139 young adolescents over a 1-year period using a prospective design. Regressions examined measures of bias at Time 1 (T1) as predictors of ratings of internalizing and externalizing…

  15. Global dengue death before and after the new World Health Organization 2009 case classification: A systematic review and meta-regression analysis.

    PubMed

    Low, Gary Kim-Kuan; Ogston, Simon A; Yong, Mun-Hin; Gan, Seng-Chiew; Chee, Hui-Yee

    2018-06-01

    Since the introduction of 2009 WHO dengue case classification, no literature was found regarding its effect on dengue death. This study was to evaluate the effect of 2009 WHO dengue case classification towards dengue case fatality rate. Various databases were used to search relevant articles since 1995. Studies included were cohort and cross-sectional studies, all patients with dengue infection and must report the number of death or case fatality rate. The Joanna Briggs Institute appraisal checklist was used to evaluate the risk of bias of the full-texts. The studies were grouped according to the classification adopted: WHO 1997 and WHO 2009. Meta-regression was employed using a logistic transformation (log-odds) of the case fatality rate. The result of the meta-regression was the adjusted case fatality rate and odds ratio on the explanatory variables. A total of 77 studies were included in the meta-regression analysis. The case fatality rate for all studies combined was 1.14% with 95% confidence interval (CI) of 0.82-1.58%. The combined (unadjusted) case fatality rate for 69 studies which adopted WHO 1997 dengue case classification was 1.09% with 95% CI of 0.77-1.55%; and for eight studies with WHO 2009 was 1.62% with 95% CI of 0.64-4.02%. The unadjusted and adjusted odds ratio of case fatality using WHO 2009 dengue case classification was 1.49 (95% CI: 0.52, 4.24) and 0.83 (95% CI: 0.26, 2.63) respectively, compared to WHO 1997 dengue case classification. There was an apparent increase in trend of case fatality rate from the year 1992-2016. Neither was statistically significant. The WHO 2009 dengue case classification might have no effect towards the case fatality rate although the adjusted results indicated a lower case fatality rate. Future studies are required for an update in the meta-regression analysis to confirm the findings. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Reporting and methodological quality of meta-analyses in urological literature.

    PubMed

    Xia, Leilei; Xu, Jing; Guzzo, Thomas J

    2017-01-01

    To assess the overall quality of published urological meta-analyses and identify predictive factors for high quality. We systematically searched PubMed to identify meta-analyses published from January 1st, 2011 to December 31st, 2015 in 10 predetermined major paper-based urology journals. The characteristics of the included meta-analyses were collected, and their reporting and methodological qualities were assessed by the PRISMA checklist (27 items) and AMSTAR tool (11 items), respectively. Descriptive statistics were used for individual items as a measure of overall compliance, and PRISMA and AMSTAR scores were calculated as the sum of adequately reported domains. Logistic regression was used to identify predictive factors for high qualities. A total of 183 meta-analyses were included. The mean PRISMA and AMSTAR scores were 22.74 ± 2.04 and 7.57 ± 1.41, respectively. PRISMA item 5, protocol and registration, items 15 and 22, risk of bias across studies, items 16 and 23, additional analysis had less than 50% adherence. AMSTAR item 1, " a priori " design, item 5, list of studies and item 10, publication bias had less than 50% adherence. Logistic regression analyses showed that funding support and " a priori " design were associated with superior reporting quality, following PRISMA guideline and " a priori " design were associated with superior methodological quality. Reporting and methodological qualities of recently published meta-analyses in major paper-based urology journals are generally good. Further improvement could potentially be achieved by strictly adhering to PRISMA guideline and having " a priori " protocol.

  17. Meteorological adjustment of yearly mean values for air pollutant concentration comparison

    NASA Technical Reports Server (NTRS)

    Sidik, S. M.; Neustadter, H. E.

    1976-01-01

    Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

  18. Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

    PubMed

    Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

    2017-02-06

    Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

  19. Distinct patterns of desynchronized limb regression in malagasy scincine lizards (squamata, scincidae).

    PubMed

    Miralles, Aurélien; Hipsley, Christy A; Erens, Jesse; Gehara, Marcelo; Rakotoarison, Andolalao; Glaw, Frank; Müller, Johannes; Vences, Miguel

    2015-01-01

    Scincine lizards in Madagascar form an endemic clade of about 60 species exhibiting a variety of ecomorphological adaptations. Several subclades have adapted to burrowing and convergently regressed their limbs and eyes, resulting in a variety of partial and completely limbless morphologies among extant taxa. However, patterns of limb regression in these taxa have not been studied in detail. Here we fill this gap in knowledge by providing a phylogenetic analysis of DNA sequences of three mitochondrial and four nuclear gene fragments in an extended sampling of Malagasy skinks, and microtomographic analyses of osteology of various burrowing taxa adapted to sand substrate. Based on our data we propose to (i) consider Sirenoscincus Sakata & Hikida, 2003, as junior synonym of Voeltzkowia Boettger, 1893; (ii) resurrect the genus name Grandidierina Mocquard, 1894, for four species previously included in Voeltzkowia; and (iii) consider Androngo Brygoo, 1982, as junior synonym of Pygomeles Grandidier, 1867. By supporting the clade consisting of the limbless Voeltzkowia mira and the forelimb-only taxa V. mobydick and V. yamagishii, our data indicate that full regression of limbs and eyes occurred in parallel twice in the genus Voeltzkowia (as hitherto defined) that we consider as a sand-swimming ecomorph: in the Voeltzkowia clade sensu stricto the regression first affected the hindlimbs and subsequently the forelimbs, whereas the Grandidierina clade first regressed the forelimbs and subsequently the hindlimbs following the pattern prevalent in squamates. Timetree reconstructions for the Malagasy Scincidae contain a substantial amount of uncertainty due to the absence of suitable primary fossil calibrations. However, our preliminary reconstructions suggest rapid limb regression in Malagasy scincids with an estimated maximal duration of 6 MYr for a complete regression in Paracontias, and 4 and 8 MYr respectively for complete regression of forelimbs in Grandidierina and

  20. Distinct Patterns of Desynchronized Limb Regression in Malagasy Scincine Lizards (Squamata, Scincidae)

    PubMed Central

    Miralles, Aurélien; Hipsley, Christy A.; Erens, Jesse; Gehara, Marcelo; Rakotoarison, Andolalao; Glaw, Frank; Müller, Johannes; Vences, Miguel

    2015-01-01

    Scincine lizards in Madagascar form an endemic clade of about 60 species exhibiting a variety of ecomorphological adaptations. Several subclades have adapted to burrowing and convergently regressed their limbs and eyes, resulting in a variety of partial and completely limbless morphologies among extant taxa. However, patterns of limb regression in these taxa have not been studied in detail. Here we fill this gap in knowledge by providing a phylogenetic analysis of DNA sequences of three mitochondrial and four nuclear gene fragments in an extended sampling of Malagasy skinks, and microtomographic analyses of osteology of various burrowing taxa adapted to sand substrate. Based on our data we propose to (i) consider Sirenoscincus Sakata & Hikida, 2003, as junior synonym of Voeltzkowia Boettger, 1893; (ii) resurrect the genus name Grandidierina Mocquard, 1894, for four species previously included in Voeltzkowia; and (iii) consider Androngo Brygoo, 1982, as junior synonym of Pygomeles Grandidier, 1867. By supporting the clade consisting of the limbless Voeltzkowia mira and the forelimb-only taxa V. mobydick and V. yamagishii, our data indicate that full regression of limbs and eyes occurred in parallel twice in the genus Voeltzkowia (as hitherto defined) that we consider as a sand-swimming ecomorph: in the Voeltzkowia clade sensu stricto the regression first affected the hindlimbs and subsequently the forelimbs, whereas the Grandidierina clade first regressed the forelimbs and subsequently the hindlimbs following the pattern prevalent in squamates. Timetree reconstructions for the Malagasy Scincidae contain a substantial amount of uncertainty due to the absence of suitable primary fossil calibrations. However, our preliminary reconstructions suggest rapid limb regression in Malagasy scincids with an estimated maximal duration of 6 MYr for a complete regression in Paracontias, and 4 and 8 MYr respectively for complete regression of forelimbs in Grandidierina and

  1. Unconditional or Conditional Logistic Regression Model for Age-Matched Case-Control Data?

    PubMed

    Kuo, Chia-Ling; Duan, Yinghui; Grady, James

    2018-01-01

    Matching on demographic variables is commonly used in case-control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case-control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case-control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls.

  2. Unconditional or Conditional Logistic Regression Model for Age-Matched Case–Control Data?

    PubMed Central

    Kuo, Chia-Ling; Duan, Yinghui; Grady, James

    2018-01-01

    Matching on demographic variables is commonly used in case–control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case–control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case–control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls. PMID:29552553

  3. On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

    PubMed

    Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

    2011-10-01

    Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

  4. Patterns of attachment and parents' adjustment to the death of their child.

    PubMed

    Wijngaards-de Meij, Leoniek; Stroebe, Margaret; Schut, Henk; Stroebe, Wolfgang; van den Bout, Jan; van der Heijden, Peter G M; Dijkstra, Iris

    2007-04-01

    The impact of adult attachment on psychological adjustment among bereaved parents and the mediating effect of relationship satisfaction were examined among a sample of 219 couples of parents. Data collection took place 6, 13, and 20 months after loss. Use of the actor partner interdependence model in multilevel regression analysis enabled exploration of both individual as well as partner attachment as predictors of grief and depression. Results indicated that the more insecurely attached parents were (on both avoidance and anxiety attachment), the higher the symptoms of grief and depression. Neither the attachment pattern of the partner nor similarity of attachment within the couple had any influence on psychological adjustment of the parent. Marital satisfaction partially mediated the association of anxious attachment with symptomatology. Contrary to previous research findings, avoidant attachment was associated with high grief intensity. These findings challenge the notion that the avoidantly attached are resilient.

  5. The role of thyroid eye disease and other factors in the overcorrection of hypotropia following unilateral adjustable suture recession of the inferior rectus (an American Ophthalmological Society thesis).

    PubMed

    Kerr, Natalie C

    2011-12-01

    Overcorrection of hypotropia subsequent to adjustable suture surgery following inferior rectus recession is undesirable, often resulting in persistent diplopia and reoperation. I hypothesized that overcorrection shift after suture adjustment may be unique to thyroid eye disease, and the use of a nonabsorbable suture may reduce the occurrence of overcorrection. A retrospective chart review of adult patients who had undergone eye muscle surgery with an adjustable suture technique was performed. Overcorrection shifts that occurred between the time of suture adjustment and 2 months postoperatively were examined. Descriptive statistics, linear regression, Anderson-Darling tests, generalized Pareto distributions, odds ratios, and Fisher tests were performed for two overcorrection shift thresholds (>2 and >5 prism diopters [PD]). Seventy-seven patients were found: 34 had thyroid eye disease and inferior rectus recession, 30 had no thyroid eye disease and inferior rectus recession, and 13 patients had thyroid eye disease and medial rectus recession. Eighteen cases exceeded the 2 PD threshold, and 12 exceeded the 5 PD threshold. Statistical analyses indicated that overcorrection was associated with thyroid eye disease (P=6.7E-06), inferior rectus surgery (P=6.7E-06), and absorbable sutures (>2 PD: OR=3.7, 95% CI=0.4-35.0, P=0.19; and >5 PD: OR=6.0, 95% CI=1.1-33.5, P=0.041). After unilateral muscle recession for hypotropia, overcorrection shifts are associated with thyroid eye disease, surgery of the inferior rectus, and use of absorbable sutures. Surgeons performing unilateral inferior rectus recession on adjustable suture in the setting of thyroid eye disease should consider using a nonabsorbable suture to reduce the incidence of postoperative overcorrection.

  6. The Role of Thyroid Eye Disease and Other Factors in the Overcorrection of Hypotropia Following Unilateral Adjustable Suture Recession of the Inferior Rectus (An American Ophthalmological Society Thesis)

    PubMed Central

    Kerr, Natalie C.

    2011-01-01

    Purpose Overcorrection of hypotropia subsequent to adjustable suture surgery following inferior rectus recession is undesirable, often resulting in persistent diplopia and reoperation. I hypothesized that overcorrection shift after suture adjustment may be unique to thyroid eye disease, and the use of a nonabsorbable suture may reduce the occurrence of overcorrection. Methods A retrospective chart review of adult patients who had undergone eye muscle surgery with an adjustable suture technique was performed. Overcorrection shifts that occurred between the time of suture adjustment and 2 months postoperatively were examined. Descriptive statistics, linear regression, Anderson-Darling tests, generalized Pareto distributions, odds ratios, and Fisher tests were performed for two overcorrection shift thresholds (>2 and >5 prism diopters [PD]). Results Seventy-seven patients were found: 34 had thyroid eye disease and inferior rectus recession, 30 had no thyroid eye disease and inferior rectus recession, and 13 patients had thyroid eye disease and medial rectus recession. Eighteen cases exceeded the 2 PD threshold, and 12 exceeded the 5 PD threshold. Statistical analyses indicated that overcorrection was associated with thyroid eye disease (P=6.7E-06), inferior rectus surgery (P=6.7E-06), and absorbable sutures (>2 PD: OR=3.7, 95% CI=0.4–35.0, P=0.19; and >5 PD: OR=6.0, 95% CI=1.1–33.5, P=0.041). Conclusions After unilateral muscle recession for hypotropia, overcorrection shifts are associated with thyroid eye disease, surgery of the inferior rectus, and use of absorbable sutures. Surgeons performing unilateral inferior rectus recession on adjustable suture in the setting of thyroid eye disease should consider using a nonabsorbable suture to reduce the incidence of postoperative overcorrection. PMID:22253487

  7. Adjustment of a Population of South African Children of Mothers Living With/and Without HIV Through Three Years Post-Birth.

    PubMed

    Rotheram-Borus, Mary Jane; Tomlinson, Mark; Scheffler, Aaron; Harris, Danielle M; Nelson, Sandahl

    2017-06-01

    Mothers living with HIV (MLH) and their children are typically studied to ensure that perinatal HIV transmission is blocked. Yet, HIV impacts MLH and their children lifelong. We examine child outcomes from pregnancy to 3 years post-birth among a peri-urban population of pregnant MLH and mothers without HIV (MWOH). Almost all pregnant women in 12 neighborhoods (98 %; N = 584) in Cape Town, South Africa were recruited and repeatedly assessed within 2 weeks of birth (92 %), at 6 months (88 %), 18 months (84 %), and 3 years post-birth (86 %). There were 186 MLH and 398 MWOH. Controlling for neighborhood and repeated measures, child and maternal outcomes were contrasted over time using longitudinal random effects regression analyses. For measures collected only at 3 years, outcomes were analyzed using multiple regressions. Compared to MWOH, MLH had less income, more informal housing and food insecurity, used alcohol more often during pregnancy, and were more depressed during pregnancy and over time. Only 4.8 % of MLH's children were seropositive; seropositive children were excluded from additional analyses. Children of MLH tended to have significantly lower weights (p < .10) over time (i.e., lower weight-for-age Z-scores) and were also hospitalized significantly more often than children of MWOH (p < .01). Children of MLH and MWOH died at similar rates (8.5 %) and were similar in social and behavioral adjustment, vocabulary, and executive functioning at 3 years post-birth. Despite living in households with fewer resources and having more depressed mothers, only the physical health of children of MLH is compromised, compared to children of MWOH. In township neighborhoods with extreme poverty, social, behavioral, language, and cognitive functioning appear similar over the first three years of life between children of MLH and MWOH.

  8. Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

    USGS Publications Warehouse

    Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

    2003-01-01

    We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

  9. Regression in autistic spectrum disorders.

    PubMed

    Stefanatos, Gerry A

    2008-12-01

    A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

  10. Dietary patterns derived by reduced rank regression (RRR) and depressive symptoms in Japanese employees: The Furukawa nutrition and health study.

    PubMed

    Miki, Takako; Kochi, Takeshi; Kuwahara, Keisuke; Eguchi, Masafumi; Kurotani, Kayo; Tsuruoka, Hiroko; Ito, Rie; Kabe, Isamu; Kawakami, Norito; Mizoue, Tetsuya; Nanri, Akiko

    2015-09-30

    Depression has been linked to the overall diet using both exploratory and pre-defined methods. However, neither of these methods incorporates specific knowledge on nutrient-disease associations. The aim of the present study was to empirically identify dietary patterns using reduced rank regression and to examine their relations to depressive symptoms. Participants were 2006 Japanese employees aged 19-69 years. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. Diet was assessed using a validated, self-administered diet history questionnaire. Dietary patterns were extracted by reduced rank regression with 6 depression-related nutrients as response variables. Logistic regression was used to estimate odds ratios of depressive symptoms adjusted for potential confounders. A dietary pattern characterized by a high intake of vegetables, mushrooms, seaweeds, soybean products, green tea, potatoes, fruits, and small fish with bones and a low intake of rice was associated with fewer depressive symptoms. The multivariable-adjusted odds ratios of having depressive symptoms were 0.62 (95% confidence interval, 0.48-0.81) in the highest versus lowest tertiles of dietary score. Results suggest that adherence to a diet rich in vegetables, fruits, and typical Japanese foods, including mushrooms, seaweeds, soybean products, and green tea, is associated with a lower probability of having depressive symptoms. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  11. Item Response Theory Modeling and Categorical Regression Analyses of the Five-Factor Model Rating Form: A Study on Italian Community-Dwelling Adolescent Participants and Adult Participants.

    PubMed

    Fossati, Andrea; Widiger, Thomas A; Borroni, Serena; Maffei, Cesare; Somma, Antonella

    2017-06-01

    To extend the evidence on the reliability and construct validity of the Five-Factor Model Rating Form (FFMRF) in its self-report version, two independent samples of Italian participants, which were composed of 510 adolescent high school students and 457 community-dwelling adults, respectively, were administered the FFMRF in its Italian translation. Adolescent participants were also administered the Italian translation of the Borderline Personality Features Scale for Children-11 (BPFSC-11), whereas adult participants were administered the Italian translation of the Triarchic Psychopathy Measure (TriPM). Cronbach α values were consistent with previous findings; in both samples, average interitem r values indicated acceptable internal consistency for all FFMRF scales. A multidimensional graded item response theory model indicated that the majority of FFMRF items had adequate discrimination parameters; information indices supported the reliability of the FFMRF scales. Both categorical (i.e., item-level) and scale-level regression analyses suggested that the FFMRF scores may predict a nonnegligible amount of variance in the BPFSC-11 total score in adolescent participants, and in the TriPM scale scores in adult participants.

  12. Poisson Regression Analysis of Illness and Injury Surveillance Data

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

    Frome E.L., Watkins J.P., Ellis E.D.

    2012-12-12

    The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to

  13. The impact of statistical adjustment on conditional standard errors of measurement in the assessment of physician communication skills.

    PubMed

    Raymond, Mark R; Clauser, Brian E; Furman, Gail E

    2010-10-01

    The use of standardized patients to assess communication skills is now an essential part of assessing a physician's readiness for practice. To improve the reliability of communication scores, it has become increasingly common in recent years to use statistical models to adjust ratings provided by standardized patients. This study employed ordinary least squares regression to adjust ratings, and then used generalizability theory to evaluate the impact of these adjustments on score reliability and the overall standard error of measurement. In addition, conditional standard errors of measurement were computed for both observed and adjusted scores to determine whether the improvements in measurement precision were uniform across the score distribution. Results indicated that measurement was generally less precise for communication ratings toward the lower end of the score distribution; and the improvement in measurement precision afforded by statistical modeling varied slightly across the score distribution such that the most improvement occurred in the upper-middle range of the score scale. Possible reasons for these patterns in measurement precision are discussed, as are the limitations of the statistical models used for adjusting performance ratings.

  14. Linear regression techniques for use in the EC tracer method of secondary organic aerosol estimation

    NASA Astrophysics Data System (ADS)

    Saylor, Rick D.; Edgerton, Eric S.; Hartsell, Benjamin E.

    A variety of linear regression techniques and simple slope estimators are evaluated for use in the elemental carbon (EC) tracer method of secondary organic carbon (OC) estimation. Linear regression techniques based on ordinary least squares are not suitable for situations where measurement uncertainties exist in both regressed variables. In the past, regression based on the method of Deming [1943. Statistical Adjustment of Data. Wiley, London] has been the preferred choice for EC tracer method parameter estimation. In agreement with Chu [2005. Stable estimate of primary OC/EC ratios in the EC tracer method. Atmospheric Environment 39, 1383-1392], we find that in the limited case where primary non-combustion OC (OC non-comb) is assumed to be zero, the ratio of averages (ROA) approach provides a stable and reliable estimate of the primary OC-EC ratio, (OC/EC) pri. In contrast with Chu [2005. Stable estimate of primary OC/EC ratios in the EC tracer method. Atmospheric Environment 39, 1383-1392], however, we find that the optimal use of Deming regression (and the more general York et al. [2004. Unified equations for the slope, intercept, and standard errors of the best straight line. American Journal of Physics 72, 367-375] regression) provides excellent results as well. For the more typical case where OC non-comb is allowed to obtain a non-zero value, we find that regression based on the method of York is the preferred choice for EC tracer method parameter estimation. In the York regression technique, detailed information on uncertainties in the measurement of OC and EC is used to improve the linear best fit to the given data. If only limited information is available on the relative uncertainties of OC and EC, then Deming regression should be used. On the other hand, use of ROA in the estimation of secondary OC, and thus the assumption of a zero OC non-comb value, generally leads to an overestimation of the contribution of secondary OC to total measured OC.

  15. An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models.

    PubMed

    Bakhtiyari, Mahmood; Mehmandar, Mohammad Reza; Mirbagheri, Babak; Hariri, Gholam Reza; Delpisheh, Ali; Soori, Hamid

    2014-01-01

    Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8%) and 54,480 women (9.2%) are analysed. The mean age is 34.1 ± 14 years. Not maintaining eyes on the road (53.7%) and losing control of the vehicle (21.4%) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95% CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road.

  16. Multivariable confounding adjustment in distributed data networks without sharing of patient-level data.

    PubMed

    Toh, Sengwee; Reichman, Marsha E; Houstoun, Monika; Ding, Xiao; Fireman, Bruce H; Gravel, Eric; Levenson, Mark; Li, Lingling; Moyneur, Erick; Shoaibi, Azadeh; Zornberg, Gwen; Hennessy, Sean

    2013-11-01

    It is increasingly necessary to analyze data from multiple sources when conducting public health safety surveillance or comparative effectiveness research. However, security, privacy, proprietary, and legal concerns often reduce data holders' willingness to share highly granular information. We describe and compare two approaches that do not require sharing of patient-level information to adjust for confounding in multi-site studies. We estimated the risks of angioedema associated with angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), and aliskiren in comparison with beta-blockers within Mini-Sentinel, which has created a distributed data system of 18 health plans. To obtain the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs), we performed (i) a propensity score-stratified case-centered logistic regression analysis, a method identical to a stratified Cox regression analysis but needing only aggregated risk set data, and (ii) an inverse variance-weighted meta-analysis, which requires only the site-specific HR and variance. We also performed simulations to further compare the two methods. Compared with beta-blockers, the adjusted HR was 3.04 (95% CI: 2.81, 3.27) for ACEIs, 1.16 (1.00, 1.34) for ARBs, and 2.85 (1.34, 6.04) for aliskiren in the case-centered analysis. The corresponding HRs were 2.98 (2.76, 3.21), 1.15 (1.00, 1.33), and 2.86 (1.35, 6.04) in the meta-analysis. Simulations suggested that the two methods may produce different results under certain analytic scenarios. The case-centered analysis and the meta-analysis produced similar results without the need to share patient-level data across sites in our empirical study, but may provide different results in other study settings. Copyright © 2013 John Wiley & Sons, Ltd.

  17. Robust inference under the beta regression model with application to health care studies.

    PubMed

    Ghosh, Abhik

    2017-01-01

    Data on rates, percentages, or proportions arise frequently in many different applied disciplines like medical biology, health care, psychology, and several others. In this paper, we develop a robust inference procedure for the beta regression model, which is used to describe such response variables taking values in (0, 1) through some related explanatory variables. In relation to the beta regression model, the issue of robustness has been largely ignored in the literature so far. The existing maximum likelihood-based inference has serious lack of robustness against outliers in data and generate drastically different (erroneous) inference in the presence of data contamination. Here, we develop the robust minimum density power divergence estimator and a class of robust Wald-type tests for the beta regression model along with several applications. We derive their asymptotic properties and describe their robustness theoretically through the influence function analyses. Finite sample performances of the proposed estimators and tests are examined through suitable simulation studies and real data applications in the context of health care and psychology. Although we primarily focus on the beta regression models with a fixed dispersion parameter, some indications are also provided for extension to the variable dispersion beta regression models with an application.

  18. Linear regression in astronomy. II

    NASA Technical Reports Server (NTRS)

    Feigelson, Eric D.; Babu, Gutti J.

    1992-01-01

    A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

  19. Retargeted Least Squares Regression Algorithm.

    PubMed

    Zhang, Xu-Yao; Wang, Lingfeng; Xiang, Shiming; Liu, Cheng-Lin

    2015-09-01

    This brief presents a framework of retargeted least squares regression (ReLSR) for multicategory classification. The core idea is to directly learn the regression targets from data other than using the traditional zero-one matrix as regression targets. The learned target matrix can guarantee a large margin constraint for the requirement of correct classification for each data point. Compared with the traditional least squares regression (LSR) and a recently proposed discriminative LSR models, ReLSR is much more accurate in measuring the classification error of the regression model. Furthermore, ReLSR is a single and compact model, hence there is no need to train two-class (binary) machines that are independent of each other. The convex optimization problem of ReLSR is solved elegantly and efficiently with an alternating procedure including regression and retargeting as substeps. The experimental evaluation over a range of databases identifies the validity of our method.

  20. A comparison between the use of Cox regression and the use of partial least squares-Cox regression to predict the survival of kidney-transplant patients

    NASA Astrophysics Data System (ADS)

    Solimun

    2017-05-01

    The aim of this research is to model survival data from kidney-transplant patients using the partial least squares (PLS)-Cox regression, which can both meet and not meet the no-multicollinearity assumption. The secondary data were obtained from research entitled "Factors affecting the survival of kidney-transplant patients". The research subjects comprised 250 patients. The predictor variables consisted of: age (X1), sex (X2); two categories, prior hemodialysis duration (X3), diabetes (X4); two categories, prior transplantation number (X5), number of blood transfusions (X6), discrepancy score (X7), use of antilymphocyte globulin(ALG) (X8); two categories, while the response variable was patient survival time (in months). Partial least squares regression is a model that connects the predictor variables X and the response variable y and it initially aims to determine the relationship between them. Results of the above analyses suggest that the survival of kidney transplant recipients ranged from 0 to 55 months, with 62% of the patients surviving until they received treatment that lasted for 55 months. The PLS-Cox regression analysis results revealed that patients' age and the use of ALG significantly affected the survival time of patients. The factor of patients' age (X1) in the PLS-Cox regression model merely affected the failure probability by 1.201. This indicates that the probability of dying for elderly patients with a kidney transplant is 1.152 times higher than that for younger patients.