Propensity score methods to adjust for confounding in assessing treatment effects: bias and precision

Abstract

There is an increasing interest in the use of propensity score (PS) methods for confounding control, with generally three ways of estimating adjusted treatment effects in pharmacoepidemiological studies: 1) stratification on PS, 2) matching on PS and 3) using PS as a covariate. To assess bias and precision of different methods, we conducted simulations in three scenarios: 1) treatment had no effect but the crude estimate showed a protective effect; 2) treatment was protective and the crude estimate was more extreme; and 3) treatment increased the risk but the crude estimate showed protective. Adjusting for confounders in all methods shifted the effect estimates toward the true values. Adjusted odds ratios using the PS stratification and the method using PS as a covariate were biased due to either residual confounding or over-adjustment. Matching on PS produced less biased average estimates than other methods but the precision of effect estimates was lower. --------------------------------------------------------------------------------