Written by the developers of Stata’s widely used survival analysis suite, this book provides the foundation to understand various approaches for analyzing time-to-event data. Taking a practical approach to the subject, the authors discuss how survival analysis estimators work and what information they exploit. They also present the syntax, features, and underpinnings of Stata’s survival analysis routines. This edition highlights the new aspects of Stata 10, including its power and sample-size calculations for survival data. Other updates include in-graph at-risk tables for Kaplan–Meier and related curves, survival analysis for survey data, and regression models with flexible functional forms via fractional polynomials.
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Unlike some glorified manuals available in the market, this book is a genuine text for an introductory course in survival analysis using Stata. This book is also an excellent supplement for a graduate-level survival analysis course as well as a reference book for a data analyst dealing with survival data. The book presents the essential models, formulas, background, and relevant references in a compact and adequate manner, and then continues to present the relevant tools, their implementation, and explanation of outputs. The present edition includes new materials related to changes in Stata 9 and 10. Particularly, the addition of an entire new chapter on power, effect size, and sample size evaluations is a welcome addition for practitioners and students.
―The American Statistician, November 2010, Vol. 64, No. 4
Written by the developers of Stata’s widely used survival analysis suite, this book provides the foundation to understand various approaches for analyzing time-to-event data. Taking a practical approach to the subject, the authors discuss how survival analysis estimators work and what information they exploit. They also present the syntax, features, and underpinnings of Stata’s survival analysis routines.
This edition highlights the new aspects of Stata 10, including its power and sample-size calculations for survival data. Other updates include in-graph at-risk tables for Kaplan–Meier and related curves, survival analysis for survey data, and regression models with flexible functional forms via fractional polynomials.
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