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Block Empirical Likelihood for Semiparametric Varying-Coefficient Partially Linear Errors-in-Variables Models with Longitudinal Data

Yafeng Xia, Hu Da
2013 Journal of Probability and Statistics  
Block empirical likelihood inference for semiparametric varying-coeffcient partially linear errors-in-variables models with longitudinal data is investigated.  ...  We apply the block empirical likelihood procedure to accommodate the within-group correlation of the longitudinal data.  ...  Methodology In this section, we are to extend the result of Hu [21] to the semivarying coefficient errors-in-variables model with longitudinal data.  ... 
doi:10.1155/2013/807135 fatcat:wkblor66fbgohnq7b7fshtlbdm

Block Empirical Likelihood for Longitudinal Single-Index Varying-Coefficient Model

Yunquan Song, Ling Jian, Lu Lin
2013 Journal of Applied Mathematics  
In this paper, we consider a single-index varying-coefficient model with application to longitudinal data.  ...  In order to accommodate the within-group correlation, we apply the block empirical likelihood procedure to longitudinal single-index varying-coefficient model, and prove a nonparametric version of Wilks  ...  In this article, we apply longitudinal data to a single-index varying-coefficient model, and propose a singleindex varying-coefficient longitudinal data model of the form where ( , ) ∈ × is a vector of  ... 
doi:10.1155/2013/792196 fatcat:sfiwdof4e5dhnl5nfuh2cftvqe

Inference Based on Empirical Likelihood for Varying Coefficient Model with Random Effect

Wanbin Li, Liugen Xue
2013 Open Journal of Statistics  
In this article, we develop a statistical inference technique for the unknown coefficient functions in the varying coefficient model with random effect.  ...  A residual-adjusted block empirical likelihood (RABEL) method is suggested to investigate the model by taking the within-subject correlation into account.  ...  For longitudinal data, except for [3, 13] studied an empirical likelihood method for the varying coefficient error-in-variable models with longitudinal data.  ... 
doi:10.4236/ojs.2013.36a006 fatcat:jrbcagngorc4rcyab7neeapene


J Chaudhary
2015 International Journal of Livestock Research  
In longitudinal studies we take repeated measurements of the same individual over a time span to encompass a detectable change in their disease/developmental status.  ...  A key strength of a longitudinal study is the ability to measure change in outcomes and/or exposure at the individual/animal level.  ...  Finally, if we allow the coefficients of the explanatory variables vary from subject to subject, we have mixed effect models, in contrast with the models containing same coefficients of the explanatory  ... 
doi:10.5455/ijlr.20150125015909 fatcat:2qoossqohjghvkqquhfpwnxrxu

Growth mixture modeling as an exploratory analysis tool in longitudinal quantitative trait loci analysis

Su-Wei Chang, Seung Choi, Ke Li, Rose Fleur, Chengrui Huang, Tong Shen, Kwangmi Ahn, Derek Gordon, Wonkuk Kim, Rongling Wu, Nancy R Mendell, Stephen J Finch
2009 BMC Proceedings  
We analyzed the 200 replicates of the simulated data with these programs using three tests: the likelihood-ratio test statistic, a direct test of genetic model coefficients, and the chi-square test classifying  ...  We examined the properties of growth mixture modeling in finding longitudinal quantitative trait loci in a genome-wide association study.  ...  In particular, we thank So-Youn Shin, Ti Zhou, Chrisnel Lamy, Songjie Li, and Qilong Yuan for their time and efforts in this project.  ... 
doi:10.1186/1753-6561-3-s7-s112 pmid:20017977 pmcid:PMC2795884 fatcat:hvwogpxgcfg2dhy36jdrgmb7mi

Semiparametric Bayesian inference in smooth coefficient models

Gary Koop, Justin L. Tobias
2006 Journal of Econometrics  
We describe procedures for Bayesian estimation and testing in both cross sectional and longitudinal data smooth coefficient models (with and without endogeneity problems).  ...  The smooth coefficient model is a generalization of the partially linear or additive model wherein coefficients on linear explanatory variables are treated as unknown functions of an observable covariate  ...  We then develop a generalized set of tools for estimating smooth coefficient models in a hierarchical (longitudinal) context, and finally, in a longitudinal data context with an endogeneity problem.  ... 
doi:10.1016/j.jeconom.2005.06.027 fatcat:ulasuy3korcsvmmohnvwablnoy

Random-Effects Models for Serial Observations with Binary Response

Robert Stiratelli, Nan Laird, James H. Ware
1984 Biometrics  
The authors wish to thank the referees for a number of suggestions that led to significant improvement of this paper.  ...  Support for this research was provided by Grant GM29745 from the National Institutes of Health.  ...  Laird and Ware (1982) discuss this empirical Bayes approach to inference in the case of measured response with linear models and Gaussian error structure.  ... 
doi:10.2307/2531147 pmid:6534418 fatcat:vtf3ud4pevfyro4tj7yldcaqsa

HIV Pandemic, Medical Brain Drain, and Economic Development in Sub-Saharan Africa

Alok Bhargava, Frédéric Docquier
2008 World Bank Economic Review  
A comprehensive longitudinal database was developed by merging the medical brain drain variables with recent data on HIV prevalence, public health expenditures, physicians' wages, and economic and demographic  ...  growth using country-level longitudinal data at 3-year intervals for the period 1990-2004.  ...  The matrices C z and C x contain coefficients of time invariant and time varying regressors, respectively; the matrix U contains the error terms.  ... 
doi:10.1093/wber/lhn005 fatcat:dunhdusz2vafbae5zikthg5rqu

Page 8589 of Mathematical Reviews Vol. , Issue 2003k [page]

2003 Mathematical Reviews  
(t) nonparametrically based on the previous varying coefficient model and a longitudinal sample of (t, Y(t), X) with time-independent covariates X = (X\’,...,. ¥*))T from n in- dependent subjects.  ...  ; Berkeley, CA); Wu, Colin O. (1-JHOP-MS; Baltimore, MD) Smoothing spline estimation for varying coefficient models with repeatedly measured dependent variables.  ... 

Time-varying copula models for longitudinal data

Esra Kürüm, John Hughes, Runze Li, Saul Shiffman
2018 Statistics and its Interface  
We call the new class of models TIMECOP because we model dependence using a time-varying copula.  ...  Our approach permits all model parameters to vary with time, and thus will enable researchers to reveal dynamic response-predictor relationships and response-response associations.  ...  developed below: time-varying copula models for longitudinal data, timecop for short.  ... 
doi:10.4310/sii.2018.v11.n2.a1 pmid:29686744 pmcid:PMC5909848 fatcat:o3tyw34jcndlbbwyuyteykkphu

Outcome Vector Dependent Sampling with Longitudinal Continuous Response Data: Stratified Sampling Based on Summary Statistics

Jonathan S. Schildcrout, Shawn P. Garbett, Patrick J. Heagerty
2013 Biometrics  
The analysis of longitudinal trajectories usually focuses on evaluation of explanatory factors that are either associated with rates of change, or with overall mean levels of a continuous outcome variable  ...  In this manuscript we introduce valid design and analysis methods that permit outcome dependent sampling of longitudinal data for scenarios where all outcome data currently exist, but a targeted sub-study  ...  The work was conducted in part using the advanced computing resources of ACCRE at Vanderbilt University, Nashville, TN.  ... 
doi:10.1111/biom.12013 pmid:23409789 pmcid:PMC3880022 fatcat:artl7jx7ivd4xp6cqsn4t356oq

A Panel Study of Life-Cycle Effects in Residential Mobility

Richard B. Davies, Andrew R. Pickles
2010 Geographical Analysis  
Different specifications for this reference probability give rise to a family of models with varying degrees of flexibility in representing the error variation.  ...  Although the signs of the interaction coefficients are as expected, the improvement in the likelihood over the full model is not significant.  ... 
doi:10.1111/j.1538-4632.1985.tb00841.x fatcat:njzvz4gkprhupkjdlysnlh2nmu

Clustered Mixed Nonhomogeneous Poisson Process Spline Models for the Analysis of Recurrent Event Panel Data

J. D. Nielsen, C. B. Dean
2007 Biometrics  
In this work, we propose penalized spline based methods for functional mixed effects models with varying coefficients.  ...  We use a likelihood based method to select multiple smoothing parameters. Furthermore, we study the asymptotics of the baseline Pspline estimator with longitudinal data.  ...  Acknowledgments The Framingham data was obtained from the Framingham Heart Study of the National Heart Lung and Blood Institute of the National Institutes of Health and Boston University School of Medicine  ... 
doi:10.1111/j.1541-0420.2007.00940.x pmid:18047528 pmcid:PMC2996855 fatcat:obypdf3uyvclhkl7cy4qtqecde

Longitudinal beta regression models for analyzing health-related quality of life scores over time

Matthias Hunger, Angela Döring, Rolf Holle
2012 BMC Medical Research Methodology  
This study examined the use of beta regression models for analyzing longitudinal HRQL data using two empirical examples with distributional features typically encountered in practice.  ...  The mixed beta model showed better likelihood-based fit statistics than the linear mixed model and respected the boundedness of the outcome variable.  ...  We acknowledge with thanks PD Dr. Alarcos Cieza and Dr.  ... 
doi:10.1186/1471-2288-12-144 pmid:22984825 pmcid:PMC3528618 fatcat:6s6t4mtizbbehcne7lbgbm7ple

Estimation of Semiparametric Censored Regression Models: An Application to Changes in Black-White Earnings Inequality during the 1960s

Kenneth Y. Chay, Bo E. Honore
1998 The Journal of human resources  
Sloan Foundation and the Centerfor Advanced Study in the Behavioral Sciences is gratefully acknowledged.  ...  Because y does not vary with the regressors x when it is censored (unlike the true variable y*), standard least squares regression will underestimate the magnitude of the regression slope coefficients.  ...  For each pair of years, the absolute error loss function was used to estimate the identically censored panel data model with fixed effects.  ... 
doi:10.2307/146313 fatcat:yql3p6qpkbdxbjp3qzypjxisoq
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