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.


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.


COMPUTING

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.

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.


LOCATION, FORMAT AND MATERIALS

The class will meet from 9 am to 5 pm each day with a 1-hour lunch break at Sheraton Boston Hotel, 39 Dalton Street, Boston, MA, 02199.

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 seminar materials. The early registration fee of $895.00 is available until May 14.

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 rooms has been reserved at the Sheraton Boston Hotel, 39 Dalton Street, Boston, MA, 02199, where the seminar takes place, at a special rate of $289 per night. In order to guarantee rate and availability, make your reservations by calling Starwood Reservations at 1-888-625-4988 or 1-617-236-2000, giving the hotel name (Sheraton Boston Hotel), and the group name (Statistical Horizons LLC) no later than May 13, 2019.

We also recommend going directly to the hotel’s website or checking other online hotel sites. Pricing varies and you may be able to secure a better rate.


SEMINAR OUTLINE

  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. Testing the proportional hazards assumption 
  13. Stratification
  14. Heterogeneity and time dependence 
  15. Repeated events 
  16. Left truncation 

RECENT COMMENTS FROM PARTICIPANTS

“This course is perfect for those wishing to hone their skills in survival analysis. It was presented in a thorough but not overwhelming manner. The material has applicability for many types of research. In addition to the detailed nuance of survival analysis, the course provided an overall lens of how to design, construct, and conduct longitudinal studies involving any time-to-event analyses.”
  Quin Denfeld, Oregon Health & Science University

“This course was especially helpful for someone like myself with no prior experience with hazard modeling. With no background in econometrics, this course made the equations of Kaplan-Meier and Cox Regression analyses approachable so I feel like I have a deeper understanding than simply interpreting coefficients from a software output.”
  Theodore Greenfelder, Penn State University

“As an education researcher, the survival analysis course helped me to better understand its applicability in my field, different techniques, and issues to consider. The course was well-paced and organized, with many examples and exercises to supplement the lectures. I’d highly recommend this course to those who are either new to or familiar with survival analysis. I’m looking forward to applying what I’ve learned to my research.”
  Erika Kato, California State University, Long Beach

“This course was an extremely well-structured course. It started from very basic concepts, but it also covered hands-on applications in SAS/Stata with very relevant (in terms of timing) exercise sessions. It was also useful in that the instructor expressed his own point of view/opinions on specifics of survival analysis.”
  Anonymous

“This is an incredibly useful course. It covers most of the important tools and methods needed to conduct survival analysis and makes use of a series of practical examples that clarify how to apply such tools and methods and interpret the results. Truly a wonderful course! Highly recommended.”
  Gino Cattani, New York University

“This is a good introductory course for individuals with existing knowledge of statistics and Stata/SAS, but want to understand the basics of survival analysis from one of the pioneers and thought leaders.”
  Joseph Smith, University of Pennsylvania