Regression-adjusted distribution regression for distributional treatment effects under covariate-adaptive randomization is asymptotically normal and attains the semiparametric efficiency bound.
empirical estimator across quantiles for continuous outcomes, with n ∈ {1,000, 5,000, 10,000}
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On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
Regression-adjusted distribution regression for distributional treatment effects under covariate-adaptive randomization is asymptotically normal and attains the semiparametric efficiency bound.