Survival Analysis Using Stata DC 2012

Washington , DC
Friday, April 13, 2012
Survival Analysis Using Stata DC 2012
Friday, April 13, 2012 9:00 AM -
Saturday, April 14, 2012 4:00 PM (Eastern Time)

Courtyard Washington Embassy Row
1600 Rhode Island Avenue
NW
Washington , DC 20036

Map and Directions

Survival Analysis Using Stata 
A 2-Day Seminar on the Analysis of Event Data 
Taught by Paul D. Allison, Ph.D.

Read 5 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.
  • 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.  

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 on Friday, April 13, and Saturday, April 14, at the Courtyard Washington Embassy Row, located at 1600 Rhode Island Avenue, NW, Washington,DC.  Class will begin at 9 a.m. each day and end at approximately 4 p.m., with a 1-hour break for lunch.  A block of guest rooms has been reserved at the hotel (see Lodging Tab at the top of this page for details).

The fee of $795.00 includes all seminar materials.

All 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 are available on request.

Course 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. Choice of time axis
13. Testing the proportional hazards assumption
14. Stratification
15. Heterogeneity and time dependence
16. R-squared
17. Repeated events
18. Left censoring, left truncation

Comments from last year's participants

Of the 18 participants who completed course evaluation forms, 12 rated it "excellent" and 6 rated it "very good."

“I greatly enjoyed this course and thought it was very comprehensive and covered most of the important issues in conducting survival analysis. I highly recommend it to any scientist working with time to event data.”
   May Baydoun, National Institute on Aging

“As someone who uses statistics in a strictly applied (non-academic) setting, I am always a bit intimidated by courses such as this. However, Dr. Allison’s presentation is crystal-clear, allowing students to understand both the theoretical underpinnings and the potential applications of survival analysis.”
   Sarah Hurley, Youth Villages

“This is an excellent refresher course on survival analysis that brings the student up to date. Both continuous time and discrete time methods are covered in detail, and nuances of applying each type of method are discussed well. An excellent investment of two days’ time.”
   Samuel Clark

“This is a very structured and informative class. Very applicable for applied researchers.”
   Yuchen Fama

“The courses provides detailed explanations with proper real empirical examples,  makes it easier to understand and to apply in research. The instructor makes complicated material easy to understand. The lecture notes will be valuable resources for later work.”
   Yuping Zhang, Lehigh University

For information on other seminars, go to
www.statisticalhorizons.com.

 

 

Contact Information

  • Phone: 610-642-1941
    Fax: 419-818-1220
    Email: allison@statisticalhorizons.com

Payment Instructions

  • The course fee is $795, which includes all course materials. All major credit cards are accepted via online registration.

    If you prefer to pay by check, complete your registration on line, then make the check out to Statistical Horizons LLC and send to

    Statistical Horizons LLC
    530 New Gulph Rd.
    Haverford, PA  19041

    If you want to pay by purchase order, send the purchase order to the address above, or to allison@statisticalhorizons.com.

    Our Tax ID number is 26-4576270.

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