Survival Analysis - Online Course
A 4-Week On-Demand Seminar Taught by
Paul AllisonMonday, September 14 —
Monday, October 12, 2026
Each Monday you will receive an email with instructions for the following week.
All course materials are available 24 hours a day. Materials will be accessible for an additional 2 weeks after the official close on October 12.
For more than 30 years, Dr. Paul Allison has been teaching his acclaimed seminar on Survival Analysis to live audiences around the world. Now you can take that course in a convenient, on-demand format. This seminar covers both the theory and practice of statistical methods for event-time data. You will receive a thorough introduction to such topics as censoring, Kaplan-Meier estimation, Cox regression, discrete-time methods, competing risks, and repeated events.
The course takes place in a series of four weekly installments of videos, quizzes, readings, and assignments, and requires about 6-8 hours/week. You can participate at your own convenience; there are no set times when you are required to be online. You can access the course through any recent web browser on most computers and mobile devices, including iPhones, iPads, and Android devices. It consists of 10 modules:
-
- Elementary Concepts of Survival Analysis
- Univariate Survival Analysis
- The Kaplan-Meier Method
- Cox Regression
- Time-dependent Covariates
- Competing Risks
- Discrete Time Analysis
- Some Tools and Tests
- Models for Non-proportional Hazards
- Repeated Events
The modules contain videos of the live version of the course in its entirety. Each module is followed by a short multiple-choice quiz to test your knowledge. There are also weekly exercises that ask you to apply what you’ve learned to a real data set.
Each week, there are 2-3 assigned articles to read. There is also an online discussion forum where you can post questions or comments about any aspect of the course. All questions will be promptly answered by Dr. Allison.
Downloadable course materials include the following PDF files:
-
- All slides displayed in the videos.
- Exercises for each week.
- Readings for each week.
- Computer code for all exercises (in SAS, Stata, and R formats).
- A certificate of completion.
ECTS Equivalent Points: 1
More details about the course content
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 challenging problems:
-
- 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?
- 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, marketing, and many other fields.
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 to practice survival analysis.
The examples and exercises will emphasize SAS and Stata, but slides and code will also be provided for R.
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 challenging problems:
-
- 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?
- 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, marketing, and many other fields.
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 to practice survival analysis.
The examples and exercises will emphasize SAS and Stata, but slides and code will also be provided for R.
Computing
To do the exercises, you will need a computer with Stata, SAS, or R installed.
For Stata users, version 16 will be used for the examples, but the exercises can also be done with versions 13-19.
If you’d like to take this course but are concerned that you don’t know enough Stata, we recommend following along with a “getting started” video like the one here before the seminar begins.
Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s 30-day software return policy.
There is now a free version of SAS, called SAS OnDemand for Academics, that is available to anyone.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent online resources for building your R skills.
To do the exercises, you will need a computer with Stata, SAS, or R installed.
For Stata users, version 16 will be used for the examples, but the exercises can also be done with versions 13-19.
If you’d like to take this course but are concerned that you don’t know enough Stata, we recommend following along with a “getting started” video like the one here before the seminar begins.
Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s 30-day software return policy.
There is now a free version of SAS, called SAS OnDemand for Academics, that is available to anyone.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent online resources for building your R skills.
Who should register?
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.
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.
Registration instructions
The fee of $695 USD includes all course materials. All major credit cards are accepted.
This course is hosted on a platform called DigitalChalk. To register, you’ll need to go to statisticalhorizons.digitalchalk.com and click on Create Account. Then you will enter your name and email address, and create a password. Be sure to save your password because you will need it to log on to the course itself.
When you have created your account, you’ll be taken to your new home page. Click on the Register Now button (or click the Catalog icon on the left-hand column), and you’ll see “Survival Analysis” as one of the available courses. At the bottom of the box for that course, click the green button Add to Cart. Next click the green button at the top that says Checkout. You will then be prompted for your credit card information.
When you have finished the payment process, you will be taken back to your home page. Click on Dashboard to see Survival Analysis. When the course begins on September 14, you can click the play button to get started.
The fee of $695 USD includes all course materials. All major credit cards are accepted.
This course is hosted on a platform called DigitalChalk. To register, you’ll need to go to statisticalhorizons.digitalchalk.com and click on Create Account. Then you will enter your name and email address, and create a password. Be sure to save your password because you will need it to log on to the course itself.
When you have created your account, you’ll be taken to your new home page. Click on the Register Now button (or click the Catalog icon on the left-hand column), and you’ll see “Survival Analysis” as one of the available courses. At the bottom of the box for that course, click the green button Add to Cart. Next click the green button at the top that says Checkout. You will then be prompted for your credit card information.