Bibliografía: p. 393-399.

Preface to the third edition -- Preface to the second edition -- Preface to the revised edition -- Preface to the first edition -- Notation and typography -- 1. The problem of survival analysis -- 2. Describing the distribution of failure times -- 3. Hazard models -- 4. Censoring and truncation -- 5. Recording survival data -- 6. Using stset -- 7. After stset -- 8. Nonparametric analysis -- 9.The Cox proportional hazards model -- 10. Model building using stcox -- 11. The Cox model : diagnostics -- 12. Parametric models -- 13. A survey of parametric regression models in Stata -- 14. Postestimation commands for parametric models -- 15. Generalizing the parametric regression model -- 16. Power and sample-size determination for survival analysis -- 17. Competing risks.

"An Introduction to Survival Analysis Using Stata, Third Edition provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves as not only as a tutorial for learning survival analysis but also as a valuable reference for experienced researchers interested in using Stata to analyze survival data." "The book is written for professional researchers form all disciplines, including biostatistics, epidemiology, public health, medicine, sociology, economics, political science, engineering, and other fields where survival analysis is applicable. Although the book assumes knowledge of statistical principles, basic probability, and working knowledge of Stata, it is practical rather than mathematical in its approach to the subject. The reader of this book will come away not just with understanding of the formulas, but also with intuition of how the various survival analysis estimators work and what information they exploit. The reader will also come away with deeper and more comprehensive knowledge of the syntax, features, and underpinnings of Stata's survival analysis routines." "The third edition has been updated to highlight the new features of Stata 11, in particular, competing-risks analysis and the treatment of missing values via multiple imputation. Among the other additions are new diagnostic measures after Cox regression, Stata's new treatment of categorical variables and interactions, and a new syntax for obtaining predictions and diagnostics after Cox regression." --From cover.