Synopses & Reviews
This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. Over 170 figures are included in the book.
Synopsis
The balanced mix of real data examples, modeling software, and theory makes this book a useful reference for practitioners who use mixed-effects models. Researchers in statistical computing will also learn novel and efficient computational methods for fitting linear and non-linear mixed effects models. 172 illus.
Synopsis
Mixed Effects Models involve measurements made over time on an individual in an experiment. This book presents the most recent techniques for analyzing this type of data in the statistical software program S-PLUS. It will be of interest to researchers and graduate students in statistics, biostatistics, and epidemiology.
Description
Includes bibliographical references (p. [415]-421) and index.