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Applied survival analysis. Regression modeling of time to event data. (English) Zbl 0966.62071

Wiley Series in Probability and Mathematical Statistics. Chichester: Wiley. xiv, 386 p. (1999).
The authors claim that the goal of this book is to provide a focused text on regression modeling for the time to event data typically encountered in health related studies. This turns out to be a good description of its contents.
The route followed in the book is by now traditional in this field, by emphasizing the so-called semi-parametric approach, or, Cox regression. The reader is assumed to be familiar with linear and logistic regression. The covered topics include the Kaplan-Meier estimator of the survivor function, the Nelson-Aalen estimator of the cumulative hazard function, the log-rank test, and Cox regression. Residuals, diagnosis of influential observations, frailty models, and recurrent event models are also covered in more or less detail. Finally, data sets used in the examples are available for download from the Internet.

MSC:

62Nxx Survival analysis and censored data
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62P10 Applications of statistics to biology and medical sciences; meta analysis
62J99 Linear inference, regression
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References:

[1] Anderson, P.K., Borgan, O., Gill, R.D., Keiding, N., 1993. Statistical Models based on Counting Processes. Springer, New York. · Zbl 0769.62061
[2] Cox, D.R., 1972. Regression models and life tables (with discussion). J. Roy. Statist. Soc. Ser. B 34, 187–220. · Zbl 0243.62041
[3] Fleming, T.R., Harrington, D.P., 1991. Counting Processes and Survival Analysis. Wiley, New York. · Zbl 0727.62096
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