Table of Contents

The problem of survival analysis. Describing the distribution of failure times. Hazard models. Censoring and truncation. Recording survival data. Using stset. After stet. Nonparametric analysis. Using stcox. Model building using stcox. The Cox model: Diagnostics. Parametric models. The exponential model. Postestimation commands for parametric models. Generalizing the parametric regression model. Power and sample-size determination for survival analysis. Competing risks.

About the Author

Mario Cleves is Professor and the Biostatistics Section Chief in the Department of Pediatrics at the University of Arkansas for Medical Sciences.

William Gould is the president and head of development at StataCorp.

Yulia Marchenko is a senior statistician at StataCorp.

All are authors of Stata statistical software, in particular, Stata’s widely used survival analysis suite.

Reviews

"This is an application-oriented introduction to survival analysis using Stata. The authors have focused on intuitions without getting into technical details. For example … the rather mysterious partial likelihood was elegantly illustrated with a small dataset and simple derivations for conditional probabilities. The book provides an excellent coverage of commonly used nonparametric, semiparametric, and parametric analyses of survival data, with ample application examples. The implementation of each survival approach has been carefully laid out in Stata syntax and real data analyses. Moreover, the material covered in the book is surprisingly comprehensive, including Coxmodels with time-varying covariates, shared frailty models, multiple imputations, and competing risk regression. Those topics are often encountered in practice but usually missing from an introductory book of survival analysis. The revised third edition has been updated to reflect the welcome additions in Stata 14 relative to previous versions. … The revised third edition provides not only an excellent tutorial to anyone who is interested in learning survival models with examples, but also an extremely handy reference to researchers who would like to perform survival analyses in Stata."
—Yu Cheng, University of Pittsburgh, in The American Statistician, April 2018