An Introduction to Survival Analysis Using Stata, Third Edition

Stata survival analysis, explained from first principles

An Introduction to Survival Analysis Using Stata, Third Edition is a hands-on guide to time-to-event data that balances statistical foundations with the practical realities of working in Stata. It starts with the ideas that shape survival analysis—hazard functions, survivor functions, censoring, and truncation—then shows how those ideas are turned into an analysis workflow using Stata’s st tools.

The book is especially valuable because it does not treat survival analysis as a black box. Instead, it moves methodically from data setup and nonparametric estimation through Cox regression and parametric modeling, helping readers see how the pieces fit together. For analysts who need to go beyond a menu-driven approach, that structure makes the subject much easier to use confidently in real projects.

What the third edition emphasizes

This edition reflects updated Stata capabilities and includes coverage of topics that matter in applied survival work, including multiple imputation, survey data, stronger diagnostic tools, and competing-risks analysis. The result is a reference that is practical without being simplistic.

Topics covered

• Survivor and hazard functions
• Censoring and truncation
• Recording and declaring survival data with stset
• Kaplan–Meier and Nelson–Aalen estimation
• Cox proportional hazards models
• Model building and diagnostics
• Parametric survival models
• Power and sample-size calculations
• Competing risks

Who will find it useful?

This book is well suited to biomedical researchers, statisticians, students, and Stata users who want a clear, methodical introduction to survival analysis with enough depth to serve as a working reference. If you want to understand not just which command to run, but why the method works, this title fits the brief beautifully.

At Digital Delights, this is the kind of technical ebook that earns its place on a serious research shelf: focused, reliable, and built for actual analysis rather than theory alone.