The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
|
Activity Number:
|
130
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, July 30, 2012 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Biometrics Section
|
| Abstract - #305889 |
|
Title:
|
Use of a Joint Modeling Approach to Estimate Covariate Effects When Competing Risks Are Present
|
|
Author(s):
|
Bo Fu*+ and Chung-Chou H Chang
|
|
Companies:
|
and University of Pittsburgh
|
|
Address:
|
5030 Centre Ave., Pittsburgh, PA, 15213, United States
|
|
Keywords:
|
competing risks ;
joint modeling
|
|
Abstract:
|
We propose a joint modeling approach that estimates covariate effects on survival by adjusting for the informative dropout caused by the presence of competing risks. The approach allows us to set different covariates for the main event model and the competing event model, thereby allowing for the inclusion of appropriate model selection for different events. We used three estimation methods to simultaneously estimate the covariate effects and the dependence between the main and competing events. In simulations, we compared the performance of the three estimation methods. When we applied the approach to a dataset, we were able to estimate the effects of several risk factors on the development of Alzheimer's disease.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.