An Introduction to Survival Analysis Using Stata, revised 3rd ed. Mario Cleves, William W. Gould, and Yulia V. Marchenko. College Station, TX: Stata Press, 2016, xxx + 428 pp., $82.95 (P), ISBN: 978-1-59-718174-7.
This is an application-oriented introduction to survival analysis using Stata. The authors have focused on intuitions without getting into technical details. For example, in the technical note on pages 23–24, 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 Cox models 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. More specifically, Stata 14 now provides marginal predictions and marginal effects from survival regression models. One can also perform regression models for competing risk outcomes in Stata 14, including the commonly used Cox model for causespecific hazard functions and the Fine and Gray (1999) model for cumulative incidence functions. More details on the two topics can be found in Section 9.1 and Chapter 17, respectively. 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.
Fine, J. P., and Gray, R. J. (1999), “A Proportional Hazards Model for the Subdistribution of a Competing Risk,” Journal of the American Statistical Association, 94, 496–509. 
University of Pittsburgh
Excerpt from "Reviews of Books and Teaching Materials." 2018. The American Statistician, 72:1, 105–113, DOI: 10.1080/00031305.2018.1444855.