Event History &
Survival Analysis

A five-day seminar taught by Paul D. Allison, Ph.D. 

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

Event History & Survival Analysis covers both the theory and practice of survival methodology. Assuming no previous knowledge of survival analysis, this seminar 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.
  • How to handle left censoring.
  • 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.


All examples and exercises will use SAS, but no previous experience with SAS is required. Four SAS procedures will be covered in detail: LIFETEST, LIFEREG, PHREG and LOGISTIC.  Lecture notes and exercises using Stata are available on request. For most of the lecture notes, an R version is also available. 

This is a hands-on course with at least one hour each day devoted to carefully structured and supervised assignments.  Additional time is available for exploring other sample data sets. Or you can bring your own data and try out new techniques as you learn them. To do the exercises, you will need to bring your own laptop computer with SAS (or Stata) installed. Power outlets will be provided at each seat. 

There is now a free version of SAS, called the SAS University Edition, that is available to anyone. It has everything needed to run the exercises in this course, and it will run on Windows, Mac or Linux computers. However, you do need a 64-bit machine with at least 1 GB of RAM. You also have to download and install virtualization software that is available free from third-party vendors. The SAS Studio interface runs in your browser, but you do not have to be connected to the Internet. The download and installation are a bit complicated, but well worth the time and effort.  

Who should attend?

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. 

Location, format, materials.

The seminar meets 9 a.m. to 5 p.m. on Monday through Friday at The Hub Commerce Square, 2001 Market Street, Philadelphia. 

Here is a typical day’s schedule:

9-12 Lecture
12-1 Lunch break
1-3 Lecture
3-5 Computing and consulting 

You’ll get a free copy of the Professor Allison’s book, Survival Analysis Using SAS® (second edition). You’ll also 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 notetaking.

Registration and lodging

The fee of $1795 includes all course materials. 

Lodging Reservation Instructions

Guests room blocks have been reserved at the following nearby hotels.

Sonesta, 1800 Market Street, Philadelphia.  Call 1-800-SONESTA (766-3782) by June 12 and mention Statistical Horizons for the $159 group rate.  Distance to seminar site – .2 miles/4 min. walk.

Embassy Suites, 1776 Benjamin Franklin Parkway, Philadelphia. Call 1-800-EMBASSY (362-2779) by June 12 and mention Statistical Horizons for the $159 group rate. Distance to seminar site – .5 mile/10 min. walk.

Club Quarters Hotel, 1628 Chestnut Street, Philadelphia. Call 203-905-2100 by June 12 and mention UPN712 for the $127 group rate. Distance to seminar site – .6 mi/12 min. walk.

Course outline

  1. Kaplan-Meier estimation
  2. Accelerated failure time models
  3. Types of censoring
  4. Maximum likelihood estimation
  5. Interpretation of parameters
  6. Proportional hazards models
  7. Partial likelihood estimation
  8. Competing risks
  9. Time dependent covariates
10. Discrete time analysis
11. Sensitivity analysis for censoring
12. Choice of time axis
13. Model choice and goodness of fit
14. Testing the proportional hazards assumption
15. Heterogeneity and time dependence
16. R-squared and standardized coefficients
17. Repeated events
18. Left censoring, left truncation

Comments from recent participants 

“It was an extremely beneficial course because you do hands-on assignments to help apply principles as you learn them. Also, the examples are given across numerous fields throughout the course which helps you think about your data and your own research.”
  Sophia L. Johnson, University of Wisconsin, Madison

“This course covers all the topics of survival analysis with the SAS codes in the latest version, including new options that were just released last week. Paul Allison is a great educator. He can explain complex techniques with such simplicity. Fascinating!”
  Min You, Bristol-Myers Squibb

“This course was extremely clear, well organized, and extremely comprehensive. It has added greatly to my survival analysis toolkit and I am looking forward to applying this knowledge to my current projects.”
  Tiffany Ho, University of Pennsylvania

“I liked how the course materials are organized and delivered. It is applicable to different areas. The course helped me refine my research projects and conduct analyses that I used to want to do but couldn’t. Thanks Dr. Allison!”
  Yang Yang, Rohrer College of Business, Rowan University

“This is an excellent course for someone who knows statistics well and wants to understand and use survival analysis in real life.”
  Amit Patki, University of Alabama at Birmingham 

“An excellent course– I now feel I have a pretty solid understanding of survival analysis and the confidence to approach such analysis in the future.”
  Tracy Anderson, Wharton, University of Pennsylvania 

“A very comprehensive course that covers all aspects of Event History Analysis. I would highly recommend this class to students who wish to learn this technique.”
  Thomas Cohen, Office of the US Courts