This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 296
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #307212
Title: A Doubly Robust Estimator of the Attributable Benefit of a Dynamic Treatment Regime
Author(s): Jason Brinkley*+ and Anastasios Tsiatis
Companies: East Carolina University and North Carolina State University
Address: , Greenville, NC, 27834,
Keywords: Attributable Benefit ; Treatment Regime ; Causal Inference ; Doubly Robust

It can sometimes be the case that there is no general consensus for treating patients with a particular disease or disorder. In such cases the best strategy may be to devise a regime or policy that individualizes treatment based on patient covariates and risk factors. Attributable benefit measures the proportion of poor outcomes that could have been prevented had such a policy been implemented. When estimating these quantities from observed data, model misspecification creates bias in the estimation of both the treatment policy and that policy's attributable benefit. Using the idea of potential outcomes and notions from causal inference we propose an estimator for this measure that augments an outcome regression model with a propensity score model for treatment. The result is an estimate of the regime's attributable benefit that is doubly robust in terms of model misspecification.

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 2010 program

2010 JSM Online Program Home

For information, contact or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.