ABSTRACT
Missing data arise in almost all serious statistical analyses. This chapter presents the Bayesian approach to missing data. To begin the chapter, various missing data mechanisms are defined, and then the chapter continues with four topics: (1) linear models for repeated measures with continuous data, (2) liner models with categorical data, (3) nonlinear models with continuous data, and (4) nonlinear models with categorical data. Of course, these four topics have been presented in Chapters 7 through 9, but with complete data for all subjects.
