Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both. The focus is applied, where necessary, to help readers thoroughly understand the statistical properties of those methods, and the behavior of the accompanying algorithms.
All techniques are illustrated with real dataexamples, with extended discussion and practical advice. All of the algorithms described in this book have been implemented by the author for general use in the statistical languages S and S Plus. The software is available free of charge on the Internet.
-Rainer Schlittgen in Statistical Papers
"This book provides an excellent introduction to statistical inference...Thanks to the clear and relatively complete treatment of many of the main ideas in this area, even theoretically oriented readers may find this book worthwhile."
-Mark Steel, Mathematical Reviews