Abstract Details
Activity Number:
|
397
|
Type:
|
Invited
|
Date/Time:
|
Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Survey Research Methods Section
|
Abstract - #307201 |
Title:
|
The Role of Covariates and Secondary Outcomes in Causal Studies with Intermediate Variables
|
Author(s):
|
Fabrizia Mealli*+
|
Companies:
|
University of Florence
|
Keywords:
|
Mutiple Outcomes ;
Covariates ;
Principal Stratification ;
Principal Causal Effects
|
Abstract:
|
Confounded post-treatment variables are often present in intervention studies. Principal Stratification (PS) is a framework to deal with such intermediate variables. Due to the latent nature of the principal strata, strong structural assumptions are often invoked to sharpen inference. Distributional assumptions may also be invoked, usually leading to weakly identified models. Information on multiple outcomes is routinely collected in practice, but rarely used to improve inference. Covariates are also collected, but often used to either make the assumptions more plausible, or improve the prediction of missing potential outcomes. We show, using various inferential paradigms, including Bayesian and frequentist perspectives, the potential inferential gains from jointly modeling two (or more) outcomes, or jointly modeling outcomes and covariates. These results can also be used to assess the plausibility of structural assumptions, such as exclusion restrictions. The role of the auxiliary information is shown in two examples to evaluate the effects of a real social job training program on participants' employment and of another real job training program on trainees' depression.
|
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.