4 days
3–4 hours daily
Learn how to effectively analyze survival-time data using Stata. This training introduces the concepts of censoring, truncation, hazard rates, and survival functions. Participants will learn how to prepare data for survival analysis, compute descriptive statistics, create life tables, obtain Kaplan–Meier curves, and fit both semiparametric (Cox) regression and parametric regression models. Discover how to set the survival-time characteristics of your dataset just once and then use many of Stata's survival-time estimators and summary statistics commands with those data.
The course will be interactive, use real data, and offer ample opportunity for working exercises to reinforce what is learned. By the end of the course, participants should be able to describe and graph their data, fit an appropriate survival-analysis model in Stata, and interpret the results.
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Currently, there are no scheduled sessions of this course.
Meghan Cain
Assistant Director, Educational Services
Meghan Cain is the Assistant Director of Educational Services at StataCorp LLC. She earned her PhD in quantitative psychology from the University of Notre Dame, where her research focused on structural equation modeling, multilevel modeling, and Bayesian statistics. At Stata, she oversees training courses, webinars, and videos, and develops and presents many of them herself. She also reviews Stata Press books and provides statistical expertise for marketing content.
Introduction to survival analysis
Setting and summarizing survival-time data
Nonparametric analysis
Fitting Cox proportional-hazards models with the stcox command
Fitting parametric survival models with the streg command
Fitting models to interval-censored data
Interpreting coefficients and other results
Predicting time of failure and survivor, hazard, or related functions
Graphing survivor, hazard, or related functions
