The SAS routines on mixed models have applications in many areas of statistics, especially biostatistics, but the procedures are not well- documented. Based on short courses given by the authors, this book provides practical guidance for SAS users.

Autorentext
The SAS routines on mixed models have applications in many areas of
statistics, especially biostatistics, but the procedures are not well-
documented. Based on short courses given by the authors, this book
provides practical guidance for SAS users.

Inhalt
Examples.- A Model for Longitudinal Data.- Exploratory Data Analysis.- Estimation of the Marginal Model.- Inference for the Marginal Model.- Inference for the Random Effects.- Fitting Linear Mixed Models with SAS.- General Guidelines for Model Building.- Exploring Serial Correlation.- Local Influence for the Linear Mixed Model.- The Heterogeneity Model.- Conditional Linear Mixed Models.- Exploring Incomplete Data.- Joint Modeling of Measurements and Missingness.- Simple Missing Data Methods.- Selection Models.- Pattern-Mixture Models.- Sensitivity Analysis for Selection Models.- Sensitivity Analysis for Pattern-Mixture Models.- How Ignorable Is Missing At Random ?.- The Expectation-Maximization Algorithm.- Design Considerations.- Case Studies.