Machine learning outcome regression improves doubly robust estimation of average causal effects.
Journal:
Pharmacoepidemiology and drug safety
Published Date:
Sep 1, 2020
Abstract
BACKGROUND: Doubly robust estimation produces an unbiased estimator for the average treatment effect unless both propensity score (PS) and outcome models are incorrectly specified. Studies have shown that the doubly robust estimator is subject to more bias than the standard weighting estimator when both PS and outcome models are incorrectly specified.