Beschreibung:
In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.
Introduction.- Linear Models.- Univariate Exponential Family of Distributions.- Generalized Linear Model.- Covariate Dependent Markov Models.- Model for Bivariate Binary Data.- Model for Bivariate Geometric Model.- Model for Bivariate Count Data.- Models for Bivariate Exponential and Weibull Data.- Quasi -Likelihood Methods.- Generalized Estimating Equations.- A Generalized Multivariate Model.- Multistate and Multistage Models.- Analysing Data Using R and SAS.