000 04782nam a22005775i 4500
001 978-0-387-69810-6
003 DE-He213
005 20161121231124.0
007 cr nn 008mamaa
008 100301s2007 xxu| s |||| 0|eng d
020 _a9780387698106
024 7 _a10.1007/978-0-387-69810-6
050 4 _aRA648.5-654
072 7 _aMBNS
072 7 _aMED028000
082 0 4 _a614.4
100 1 _aCook, Richard J.
245 1 4 _aThe Statistical Analysis of Recurrent Events
_h[electronic resource] /
_cby Richard J. Cook, Jerald F. Lawless.
264 1 _aNew York, NY :
_bSpringer New York,
300 _aXX, 404 p.
_bonline resource.
336 _atext
337 _acomputer
338 _aonline resource
347 _atext file
490 1 _aStatistics for Biology and Health,
505 0 _aModels and Frameworks for Analysis of Recurrent Events -- Methods Based on Counts and Rate Functions -- Analysis of Gap Times -- General Intensity-Based Models -- Multitype Recurrent Events -- Observation Schemes Giving Incomplete or Selective Data -- OtherTopics.
520 _aRecurrent 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. Richard J. Cook is Professor in the Department of Statistics and Actuarial Science at the University of Waterloo and Canada Research Chair in Statistical Methods for Health Research. He is an Associate Editor for Lifetime Data Analysis. Jerald F. Lawless is Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He is a former Editor of Technometrics and from 1994-2004 held the General Motors Canada-NSERC Industrial Research Chair in Quality and Productivity. He is the author of Statistical Models and Methods for Lifetime Data, Second Edition (2003).
650 0 _aMedicine.
650 0 _aPublic health.
650 0 _aEpidemiology.
650 0 _aStatistics.
650 0 _aQuality control.
650 0 _aReliability.
650 0 _aIndustrial safety.
650 0 _aEconometrics.
650 1 4 _aMedicine & Public Health.
650 2 4 _aEpidemiology.
650 2 4 _aEconometrics.
650 2 4 _aStatistics for Life Sciences, Medicine, Health Sciences.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aQuality Control, Reliability, Safety and Risk.
650 2 4 _aPublic Health.
700 1 _aLawless, Jerald F.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
830 0 _aStatistics for Biology and Health,
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-69810-6
912 _aZDB-2-SMA
950 _aMathematics and Statistics (Springer-11649)
999 _c508914