Higher Moments for Optimal Balance Weighting in Causal Estimation.

ABSTRACT: We expand upon a simulation study that compared three promising methods for estimating weights for assessing the average treatment effect on the treated for binary treatments: generalized boosted models, covariate-balancing propensity scores, and entropy balance. The original study showed that generalized boosted models can outperform covariate-balancing propensity scores, and entropy balance when there are likely to be nonlinear associations in both the treatment assignment and outcome models and when the other two models are fine-tuned to obtain balance only on first-order moments. We explore the potential benefit of using higher-order moments in the balancing conditions for covariate-balancing propensity scores and entropy balance. Our findings showcase that these two models should, by

SUBMITTER: Huang MY 

PROVIDER: S-EPMC9156532 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature