» The Statistical Analysis of Recurrent Events (Statistics for Biology and Health)
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The Statistical Analysis of Recurrent Events (Statistics for Biology and Health) Details
Binding: HardcoverDewey Decimal Number: 614
EAN: 9780387698090
ISBN: 0387698094
Label: Springer
Manufacturer: Springer
Number Of Items: 1
Number Of Pages: 404
Publication Date: 2007-08-02
Publisher: Springer
Studio: Springer
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The Statistical Analysis of Recurrent Events (Statistics for Biology and Health) Reviews
Customer Rating:Summary: new book on recurrent events
Comment: 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.
Editorial Review for The Statistical Analysis of Recurrent Events (Statistics for Biology and Health):
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.
