As software programs for fitting linear mixed models (LMMs) proliferate, so does confusion. In this introduction to primary concepts, notation, software implementation, model interpretation and visualization of clustered and longitudinal data West (statistical consultation and research, U. of Michigan-Ann Arbor) and his co-authors give readers sufficient theory to make informed decisions but focus on the practical to describe the model-building process step by step. Beginning with an overview of LMMs, they turn to real-world data sets (including those concerning rat brains and dental veneers) to help readers compare model fitting options and results and link software to procedures in two-level models and three-level models for clustered data, models for repeated-measures data, random coefficient models for longitudinal data, and models for clustered longitudinal data. They include descriptions of statistical software resources and useful Internet links. Annotation ©2007 Book News, Inc., Portland, OR (booknews.com)
Read More
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on both general and hierarchical model specifications, develop the model-building process step-by-step, and demonstrate the estimation, testing, and interpretation of fixed-effect parameters and covariance parameters associated with random effects. These concepts are illustrated through examples using real-world data sets that enable comparisons of model fitting options and results across the software procedures. The book also gives an overview of important options and features available in each procedure. Making popular software procedures for fitting LMMs easy-to-use, this valuable resource shows how to perform LMM analyses and provides a clear explanation of mixed modeling techniques and theories.
Read Less