A Framework for the Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data. (arXiv:2112.07602v3 [stat.ME] UPDATED)

A central obstacle in the objective assessment of treatment effect (TE)
estimators in randomized control trials (RCTs) is the lack of ground truth (or
validation set) to test their performance. In this paper, we provide a novel
cross-validation-like methodology to address this challenge. The key insight of
our procedure is that the noisy (but unbiased) difference-of-means estimate can
be used as a ground truth "label" on a portion of the RCT, to test the
performance of an estimator trained on …

analysis applications arxiv data framework meta meta-analysis