Survival Analysis

A 2-Day Seminar taught by Paul D. Allison, Ph.D. 

Read reviews of this course

To see a sample of the course materials, click here.

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.

This is a hands-on course with ample opportunity for participants to practice survival analysis.


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 is a hands-on course with at least one hour each day devoted to carefully structured and supervised assignments. To do the exercises, you will need to bring your own laptop computer with either SAS or Stata installed. Power outlets will be provided at each seat.

For Stata users, version 15 will be used for the examples, but the exercises can also be done with versions 13 or 14. Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s free 30-day evaluation offer or their 30-day software return policy.

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.


The class will meet from 9 am to 5 pm each day with a 1-hour lunch break at Temple University Center City, 1515 Market Street, Philadelphia, PA 19103. 

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. 

Registration and lodging

The fee of $995.00 includes all course materials.

Refund Policy

If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50). 

Lodging Reservation Instructions

A block of guest rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut Street, Philadelphia, PA at a special rate of $159 per night. This location is about a 5-minute walk to the seminar location. In order to make reservations, call 203-905-2100 during business hours and identify yourself by using group code STSH01 or click here. For guaranteed rate and availability, you must reserve your room no later than Monday, October 1, 2018. 

If you make reservations after the cut-off date, ask for the Statistical Horizons room rate (do not use the code) and they will try to accommodate your request.


  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 


“Survival Analysis is an incredibly useful tool in the methodological toolbox. Understanding both theory and application of this method has the ability to not only improve statistical skill, but change how you see the world. This is a useful and pragmatic course for anyone, regardless of skill level. Plus, Dr. Allison is a phenomenal teacher, you won’t be disappointed.”
  Margaret Traeger, Yale University

“Excellent, a semester of course material fit into two days, well done!”
  Joanna Woersching, New York University

“This is a very well-structured workshop that balances the theoretical and practical concepts of Survival Analysis. I would highly recommend it for those who want to gain an in-depth understanding of this topic.”
  Rahul Khanna, Johnson and Johnson

“A good overview of Survival Analysis. This stuff is typically learned in one semester-long course. Direct application to day-to-day projects.”
  Amol Karmarkar, University of Texas Medical Branch, Sealy Center of Aging

“I learned the whole picture of the application of survival methodology and obtained more insights on the understanding of the Cox proportional hazard model, discrete time survival model. I look forward to attending more statistical courses offered by Professor Allison in the future.”
  Chuanliang Jiang, HSBC Bank

“I have read about Survival Analysis extensively and understood the process prior to attending the class. Dr. Allison really helped me to understand the nuances of the approach including different tradeoffs and their strength and limitation now. I feel as if I will be able to talk about my proposed work a lot more confidently.”
  Alecia Slade-Clary, University of North Carolina