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Survival Analysis Using Stata New

Description

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.

Price: $1,295  

We offer a 15% discount for group enrollments of three or more participants.

Course leader

Meghan Cain portrait

Meghan Cain is a Senior Statistician at StataCorp. 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 develops and presents training on these and other topics. She also conducts webinars, works with developers to produce Stata documentation, and contributes to Stata blogs.

Course topics

  • Introduction to survival analysis
    • What is survival analysis?
    • Censoring and truncation
    • Survivor and hazard functions
  • Setting and summarizing survival-time data
    • Setting your data with stset
    • Summarizing survival data
    • Creating life tables
  • Nonparametric analysis
    • The Kaplan–Meier product-limit estimator
    • The Nelson–Aalen estimator of the cumulative hazard
  • Fitting Cox proportional hazards models with the stcox command
    • Incorporating time-varying variables
    • Testing the proportional-hazards assumption
    • Assessing goodness of fit
  • Fitting parametric survival models with the streg command
    • Proportional hazards (PH) and accelerated failure time (AFT) models
    • Exponential, Weibull, and Gompertz regression
    • Choosing among parametric models
  • 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

Prerequisite

Basic knowledge of statistics and regression analysis and a working knowledge of Stata.

Next session

Currently, there are no scheduled sessions of this course.

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Notes

Enrollment is limited. This course is offered in both classroom and web-based settings.

Classroom training courses are two-day courses that run from 8:30 a.m. to 4:30 p.m. each day. These courses take place at a training center where computers with Stata installed are provided. A continental breakfast, lunch, and an afternoon snack will also be provided; the breakfast is available before the course begins.

Web-based training courses are four-day courses that run for three and a half hours each day. You will be provided with a temporary Stata license to install on your computer, a printed copy of the course notes, and all the course datasets so that you can easily follow along. Learn more about how our web-based training courses work, watch a video demonstration, and find technical requirements for participating in this type of training.

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