Includes bibliographical references (pages 671-693) and index.
CONTENTS NOTE
Text of Note
Longitudinal and clustered data -- Longitudinal data: basic concepts -- overview of linear models for longitudinal data -- Estimation and statistics inference -- Modeling the mean: analyzing response profiles -- Modeling the mean: parametric curves -- Modeling the covariance -- Linear mixed effect models -- Fixed effects versus random effects models -- Residual analyses and diagnostics -- Review of generalized linear models -- Marginal models: introduction and overview -- Marginal models: generalized estimating equations (GEE) -- Generalized linear mixed effect models -- Generalized linear mixed effect models: approximate methods of estimation -- Contrasting marginal and mixed effects models -- Missing data and dropout: overview of concepts and methods -- Missing data and dropouts: multiple imputation and weighting methods -- Smoothing longitudinal data: semiparametric regression models -- Sample size and power -- Repeated measures and related designs -- Multilevel models
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SUMMARY OR ABSTRACT
Text of Note
"Since the publication of the first edition, the authors have solicited feedback from both the instructors who use the book as a text for their courses as well as the researchers who use the book as a resource for their research. Thus, the improved Second Edition of Applied Longitudinal Analysis features many additions and revisions based on the feedback of readers, making it the go-to reference for applied use in public health, epidemiology, and pharmaceutical sciences"--