Product Description

Recurrent event data arise in diverse fields such as medicine, public health, insurance, social science, economics, manufacturing and reliability. The purpose of this book is to present models and statistical methods for the analysis of recurrent event data. No single comprehensive treatment of these areas currently exists. The authors provide broad but detailed coverage of the major approaches to analysis, while also emphasizing the modeling assumptions that they are based on. Thus, they consider important models such as Poisson and renewal processes, with extensions to incorporate covariates or random effects.

More general intensity-based models are also considered, as well as simpler models that focus on rate or mean functions. Parametric, nonparametric and semiparametric methodologies are all covered, with clear descriptions of procedures for estimation, testing and model checking. Important practical topics such as observation schemes and selection of individuals for study, the planning of randomized experiments, events of several types, and the prediction of future events are considered.

Methods of modeling and analysis are illustrated through many examples taken from health research and industry. The objectives and interpretations of different analyses are discussed in detail, and issues of robustness are addressed. Statistical analysis of the examples is carried out with S-PLUS software and code is given for some examples.

This book is directed at graduate students, researchers, and applied statisticians working in industry, government or academia. Some familiarity with survival analysis is beneficial since survival software is used to carry out many of the analyses considered. This book can be used as a textbook for a graduate course on the analysis of recurrent events or as a reference for a more general course on event history analysis. Problems are given at the end of chapters to reinforce the material presented and to provide additional background or extensions to certain topics.

Product Details

• Amazon Sales Rank: #880274 in Books
• Published on: 2007-08-02
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 404 pages

Review

From the Reviews:

"The book provides many good real life examples to demonstrate application of the methods discussed....[it] is excellent for teaching an advanced class in statistics on this topic as it also contains many good exercises at the end of each chapter, some being extensions of the discussions." (Journal of Biopharmaceutical Statistics (JBS), Issue #5, 2008)

"This book provides a timely and comprehensive review of methodologies for recurrent event data analysis and should be beneficial to Biometrics readers who are interested in recurrent events."

"The strength of this book is its scope. It covers most of the methodology that is readily available for general use. ...Overall, we think this is a very good reference for recurrent event data analysis, especially because no other books provide a similar degree of coverage, and it would provide a nice textbook for a graduate-level course on the topic."   (Biometrics, September 2008)

"This book deals with processes generating multiple events over time. … The book comprises eight chapters, four appendices and a useful notational glossary. … it is directed to a much broader target readership, like social scientists, economists and industrial statisticians as well. … Many examples are used to illustrate and discuss the models and statistical methods in great detail. Techniques for estimation, testing and model checking are lucidly described … for a graduate course." (Harald Heinzl, Zentralblatt MATH, Vol. 1159, 2009)

Customer Reviews

new book on recurrent events
These authors along with Wayne Nelson have been doing the pioneering work on recurrent events. Recurrent events are outcomes that occur more than once for the subjects under study. One example that Wayne Nelson used in his course and text is the time of birth and the total number of births by an adult woman. In reliability it could be the number of times and mileage when the car battery fails or a tire goes flat. In onco;ogy it can be the recurrence of a tumor. The methodology is a modification to survival analysis accounting for multiple events. The problem can also be posed as a multvariate survival problem where the multiple events for each subject are represented by a vector times of occurrence. It differs from the standard approach such as given in the text by Hougaard. Nelson concentrates on the mean cumulative function whereas Lawless and Cook are more concerned with hypothesis testing.

This text is very clearly written and covers the state of the art in recurrent event theory. These methods should and will see much more use in the future as there are many applications in reliability with maintenance, warranties and clinical trial data analysis.