Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods applicable to many types of life history data. Special models such as illness-death, competing risks and progressive processes are considered, as well as more complex models. The book provides both theoretical development and illustrations of analysis based on data from randomized trials and observational cohort studies in health research. It features: Discusses a wide range of applications of multistate models, Presents methods for both continuously and intermittently observed life history processes, Gives a thorough discussion of conditionally independent censoring and observation processes, Discusses models with random effects and joint models for two or more multistate processes, Discusses and illustrates software for multistate analysis that is available in R, Target audience includes those engaged in research and applications involving multistate models.
Table of Contents
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.
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)
"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 is a very nice book that does not exist on the market yet, and the multistate models for example are not well covered in terms of text books. We here have a book that really takes the multistate aspect seriously and provides many genuine examples that are discussed in depth. I cannot recall seeing examples in such depth in other books that deal with similar topics. This is not easy to do but the authors succeed in this fully."
~Thomas Scheike, University of Copenhagen
"This book includes a wide-ranging review of the use of multistate models for the analysis of longitudinal data arising from healthcare. The presentation is very clear and strikes a good balance between general description and rigorous specification of appropriate statistical models, including assumptions and limitations. Illustration of the methods using some substantive datasets, based on the authors’ experience of monitoring complex diseases, provides further insight into the value of different approaches. Both the level of detail and the pace of the arguments is very good."
~Linda Sharples, London School of Hygiene and Tropical Medicine