Generalized, Linear, and Mixed Models (Wiley Series in Probability and Statistics)
Synopsis "Generalized, Linear, and Mixed Models (Wiley Series in Probability and Statistics)"
An accessible and self-contained introduction to statisticalmodels-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Editionprovides an up-to-date treatment of the essential techniques fordeveloping and applying a wide variety of statistical models. Thebook presents thorough and unified coverage of the theory behindgeneralized, linear, and mixed models and highlights theirsimilarities and differences in various construction, application,and computational aspects.A clear introduction to the basic ideas of fixed effects models,random effects models, and mixed models is maintained throughout,and each chapter illustrates how these models are applicable in awide array of contexts. In addition, a discussion of generalmethods for the analysis of such models is presented with anemphasis on the method of maximum likelihood for the estimation ofparameters. The authors also provide comprehensive coverage of thelatest statistical models for correlated, non-normally distributeddata. Thoroughly updated to reflect the latest developments in thefield, the Second Edition features: A new chapter that covers omitted covariates, incorrect randomeffects distribution, correlation of covariates and random effects,and robust variance estimationA new chapter that treats shared random effects models, latentclass models, and properties of modelsA revised chapter on longitudinal data, which now includes adiscussion of generalized linear models, modern advances inlongitudinal data analysis, and the use between and withincovariate decompositionsExpanded coverage of marginal versus conditional modelsNumerous new and updated examplesWith its accessible style and wealth of illustrative exercises,Generalized, Linear, and Mixed Models, Second Edition is anideal book for courses on generalized linear and mixed models atthe upper-undergraduate and beginning-graduate levels. It alsoserves as a valuable reference for applied statisticians,industrial practitioners, and researchers.
