JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 32
Type: Contributed
Date/Time: Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #310081
Title: Performance of Various Propensity Score Estimation Techniques for Estimating Relative Risks: A Simulation Study
Author(s): Jiaxiao Shi*+ and Wansu Chen
Companies: Kaiser Permanente and Kaiser Permanente
Keywords: Logistic Regression ; CART ; GBM ; NNET

Propensity score (PS) method has been increasingly used to address confounding issues when evaluating causal effects. The score is often estimated using the logistic regression model (LR), an approach that is not flexible for handling non-linear relationships between the exposure and covariates used to predict the score. Several non-parametric methods have been suggested as alternative techniques to estimate PS. They include classification and regression trees (CART), generalized boosted models (GBM) and neural networks (NNET). Simulation was conducted to compare the performance of LR, CART, GBM, and NN under varying degrees of non-linearity between the exposure and covariates, and at various levels of outcome rates and relative risks (RR). PS was applied into the outcome models by using regression adjustment. Our results showed that CART performed the best in both bias and mean square error (MSE) when outcome rate was low (1%). When outcome rate was not extremely rare (10%), the biases and MSEs for all other techniques were comparable and were smaller than those of CART. Users may need to be aware of the outcome rate when selecting a PS method.

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.

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