This is an introduction to survival analysis. The authors focused on intuitions. The partial likelihood was illustrated with a small dataset and simple derivations. There are plenty of application examples in the book, which provides an excellent coverage of commonly used nonparametric, semiparametric, and parametric analyses of survival data. Stata has been used to lay out the implementation of each survival approach. Coxmodels with time-varying covariates, shared frailty models, multiple imputations, and competing risk regression are included in the book. Those topics are usually missing from an introductory book of survival analysis. The welcome additions in Stata 14 have been reflected in the revised third edition. The third edition provides an excellent primer to anyone who is interested in learning survival models with examples, as well as a reference to researchers who would like to perform survival analyses in Stata. Yu Cheng is from the University of Pittsburgh. The Statistician of the United States. April of this year.

–This text refers to the paperback edition.

Mario Cleves. At the University of Arkansas for Medical Sciences, he is the Chief of the Biostatistics Section.

William Gould. He is the head of development at StataCorp.

Marchenko is the daughter of Yulia Marchenko. A senior statistician at StataCorp.

Stata?s widely used survival analysis suite is written by all of the authors.

–This text refers to the paperback edition.