High-dimensional empirical likelihood weighting plus regularized augmented outcome regression gives multiply robust ATE inference: valid confidence intervals if any working propensity score model, a linear mixture of them, or the outcome model is correct.
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Multiply Robust Inference of Average Treatment Effects by High-dimensional Empirical Likelihood
High-dimensional empirical likelihood weighting plus regularized augmented outcome regression gives multiply robust ATE inference: valid confidence intervals if any working propensity score model, a linear mixture of them, or the outcome model is correct.