2014 Stata Summer School:

Survival Analysis Using Stata

Taught by Paul Allison, Ph.D.
August 14-15, Hotel Birger Jarl Conference
Stockholm, Sweden 

Read reviews of this seminar 

For event-time data, ordinary regression analysis won’t do the job

If you’ve ever used regression analysis on longitudinal event data, you’ve probably come up against two intractable problems:

1. Censoring: Nearly every sample contains some cases that do not experience an event. If the dependent variable is the time of the event, what do you do with these “censored” cases?

2. Time-dependent covariates: Many explanatory variables (like income or blood pressure) change in value over time. How do you put such variables in a regression analysis? 

Makeshift solutions to these questions can lead to severe biases. Survival methods are explicitly designed to deal with censoring and time-dependent covariates in a statistically correct way. Originally developed by biostatisticians, these methods have become popular in sociology, demography, psychology, economics, political science, and marketing.

How you will benefit from this seminar

Survival Analysis covers both the theory and practice of survival methodology. Assuming no previous knowledge of survival analysis, this course will turn you into a knowledgeable and skilled user of these indispensable techniques. Here are a few of the skills you will acquire:

  • How to organize survival data.
  • How to choose the right time axis.
  • When to use discrete vs. continuous time methods.
  • What to do about nonproportionality.
  • How to compute R-squared.
  • When and how to correct for unobserved heterogeneity.
  • How frequently to measure independent variables.
  • What to do if there is more than one kind of event.
  • How to test for sensitivity to informative censoring.  


If you need to analyze longitudinal event data and have a basic statistical background, this seminar is for you. You should have a good working knowledge of the principles and practice of multiple regression, as well as elementary statistical inference. But you do not need to know matrix algebra, calculus, or likelihood theory. 

Previous participants have come from a wide variety of fields: sociology, demography, psychology, economics, management, finance, history, marketing, biology, medicine, veterinary medicine and criminal justice.


This seminar will use Stata for all the examples. Although not required, participants are strongly encouraged to bring their own laptop computers with a recent version of Stata installed.  If you do not currently have Stata, we can provide a temporary license for Stata 13 which you can download and install before coming to the course. Power outlets will be available at each seat.


Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking. 

All examples and lecture notes will use Stata. However, lecture notes using SAS and R are also available on request. 

The following Stata commands will be covered:  stset, streset, sts list, sts graph, sts test, stcox, stcurve, stcrreg, stcompet, logistic, mlogit, cloglog, reshape.


 Please go to the Metrika website for information on registration, and discounted hotel accommodations.


1.  Fundamentals of survival analysis
2.  Problems with conventional methods
3. Types of censoring 
4. Kaplan-Meier estimation 
5. Proportional hazards models 
6. Partial likelihood estimation 
7. Interpretation of parameters 
8. Competing risks 
9. Time dependent covariates 
10. Discrete time analysis 
11. Sensitivity analysis for censoring 
12. Choice of time axis 
13. Testing the proportional hazards assumption 
14. Stratification
15. Heterogeneity and time dependence 
16. Repeated events 
17. Left censoring, left truncation


“This is an extremely well-organized course that is taught in a challenging but intuitive way.”
   Michael McPherson, University of North Texas 

“This course offered a great introduction to the practical application of survival analysis using Stata. I would highly recommend it to anyone who needs a crash course or  a refresher on the mechanics of running survival analysis in Stata.”
  Jillian Stein, Mathematica Policy Research 

“A great course with a very specific focus on survival analysis techniques and when/how to use various models. A good working knowledge of basic statistics is necessary, but advanced knowledge of survival analysis is not.”
  Jennifer McKeon, Ithaca College  

“I have completed 3 courses with Statistical Horizons and have found all to be extremely useful. This course on survival analysis had broad coverage of both discrete time and continuous time methods, and clear explanations of Stata commands and applicability, as well as interpretation of results. I found the hands-on exercises to be especially useful in beginning to apply course concepts, followed by further discussion in class. I found discussion of repeated events to be very informative beyond thinking about a single event occurrence.”
  Holly Foster, Texas A&M Univeristy