JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 69
Type: Contributed
Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract #311503
Title: Adjustment for Mismeasured Exposure Using Validation Data and Propensity Scores
Author(s): Danielle Braun*+ and Malka Gorfine and Corwin Zigler and Francesca Dominici and Giovanni Parmigiani
Companies: Harvard and Technion - Israel Institute of Technology and Harvard School of Public Health and HSPH and Dana-Farber Cancer Institute
Keywords: Measurement Error ; Comparative Effectiveness Research ; Causal Inference ; Propensity Score ; Exposure ; Validation Data
Abstract:

Propensity score methods are widely used to analyze observational studies in which patient characteristics might not be balanced by treatment group. These methods assume that exposure, or treatment assignment, is error-free, but in reality these variables can be subject to measurement error. This arises in the context of comparative effectiveness research, in which accurate procedural codes are not always available. When using propensity score based methods, this error affects the exposure variable directly, as well as the propensity score. We propose a two step maximum likelihood approach using validation data to adjust for the error. First, we use a likelihood approach to estimate an adjusted propensity score. Using the adjusted propensity score, we use a likelihood approach on the outcome model to adjust for the error in the exposure variable directly. In addition, we show the bias in the inverse probability weighting (IPW) estimator and propose an approach to eliminate this bias. Simulations show our proposed approaches reduce the bias and mean squared error (MSE) of the treatment effect estimator compared to using the error-prone treatment assignment.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development 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.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.