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Survival Analysis Using S: Analysis of TimetoEvent Data (Chapman & Hall/CRC Texts in Statistical Science)
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Survival Analysis Using S: Analysis of TimetoEvent Data is designed as a text for a onesemester or onequarter course in survival analysis for upperlevel or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard precalculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics.The authors emphasize parametric loglinear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of lefttruncated and rightcensored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s).In a chapter written by Stephen Portnoy, censored regression quantiles a new nonparametric regression methodology (2003) is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the KaplanMeier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.
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