Simulations show augmented inverse probability weighting yields more robust causal estimates than inverse probability weighting or response surface modeling when propensity score or outcome models are misspecified.
Journal of the Royal Statis- tical Society Series B: Statistical Methodology72(4), 417–473 (2010)
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Application of Propensity Score Models and Causal Estimators in Observational Studies under Model Misspecification
Simulations show augmented inverse probability weighting yields more robust causal estimates than inverse probability weighting or response surface modeling when propensity score or outcome models are misspecified.