Richard Cook is Canada Research Chair in Statistical Methods for Health Research at the University of Waterloo. He has received the Gold Medal of the Statistical Society of Canada and is a Fellow of the American Statistical Association. He collaborates and consults widely on health research and has given many short courses. He and Dr. Lawless previously coauthored the influential book, The Statistical Analysis of Recurrent Events (Springer, 2007).

Jerald Lawless is Distinguished Professor Emeritus at the University of Waterloo. He is a Fellow of the Royal Society of Canada, a Gold Medal recipient of the Statistical Society of Canada and Fellow of the American Statistical Association. He is a past editor of Technometrics and has collaborated and consulted in numerous areas. He has presented many short courses, with Dr. Cook and individually.

"The authors of the book are internationally renowned experts in the field of multi-state modeling and have written an extremely clear and comprehensive book on the topic that covers many different aspects, from the fundamental theory to the practical side of analyzing data and interpreting results. The examples are well chosen to represent the most common types of multi-state processes that public health researchers could encounter. The inclusion of software code to illustrate how the models can be fit and interpreted is especially helpful to readers." (Mimi Kim, Albert Einstein College of Medicine)

This book will describe a variety of statistical models useful for the analysis of data arising from life history processes. Particular attention will be paid to models useful for the study of chronic diseases to better understand the dynamics of the disease process, the effects of fixed and time-varying covariates, and the use of models for prediction. Observation of the full course of processes for individuals in a study is typically incomplete, so methods of analysis must address this. This book will cover methods for analysis when process data are right -censored, left-truncated or intervalcensored.

1. Introduction to Life History Processes and Multistate Models. 2. Event History Processes and Multistate Models. 3. Multistate Analysis Based on Continuous Observation. 4. Some examples of analysis with multistate models. 5. Studies with Intermittent Observation of Individuals. 6. Heterogeneity and Dependence in Multistate Processes. 7. Process-dependent Sampling Schemes. 8. Additional Topics.