Abstract Details
Activity Number:
|
457
|
Type:
|
Invited
|
Date/Time:
|
Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Biometrics Section
|
Abstract - #307289 |
Title:
|
Causal Mediation Analysis in Comparative Effectiveness Research
|
Author(s):
|
Xiao-Hua Andrew Zhou*+ and Cheng Zheng
|
Companies:
|
University of Washington and University of Washington
|
Keywords:
|
Comparative effectiveness; propensity score; high-dimensional data
|
Abstract:
|
Mediation analysis is an important topic in comparative effectiveness research as it helps to understand why an intervention works. In this talk, we proposed a new mediation model for count data that does not require "sequential ignorability" assumption. We compared the proposed estimator with both Poisson and Negative binomial regression method assuming sequential ignorability in both simulation study and a real data problem. The results show that the proposed method performs well.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 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.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.