Richard J Cook, Jerald F. Lawless

Multistate Models for the Analysis of Life History Data (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 854
• Erscheinungstermin: 15. Mai 2018
• Englisch
• ISBN-13: 9781498715614
• Artikelnr.: 54790178

Autorenporträt

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)

Inhaltsangabe

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.

Rezensionen

"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