The design of experiments involves a compromise between covariate balance and
robustness. This article provides a formalization of this tradeoff and describes an …

Asymptotic properties of high-dimensional random forests Page 1 The Annals of Statistics
2022, Vol. 50, No. 6, 3415–3438 https://doi.org/10.1214/22-AOS2234 © Institute of …

First, we provide additional finite-sample diagnosis tools for rerandomization, and conduct a
simulation study. Second, we extend the asymptotic theory to regression adjustment under …

We describe a new design-based framework for drawing causal inference in randomized
experiments. Causal effects in the framework are defined as linear functionals evaluated at …

Classical randomized experiments, equipped with randomization-based inference, provide
assumption-free inference for treatment effects. They have been the gold standard for …

Blocking is commonly used in randomized experiments to increase efficiency of estimation.
A generalization of blocking removes allocations with imbalance in covariate distributions …

We consider the random number partitioning problem (\texttt {NPP}): given a list $
X\sim\mathcal {N}(0, I_n) $ of numbers, find a partition $\sigma\in\{-1, 1\}^ n $ with a small …

Rerandomization is a strategy for improving balance on observed covariates in randomized
controlled trials. It has been both advocated and advised against by renowned scholars of …

Rerandomization discards assignments with covariates unbalanced in the treatment and
control groups to improve estimation and inference efficiency. However, the acceptance …

In game theory and statistical decision theory, a random (ie, mixed) decision strategy often
outperforms a deterministic strategy in minimax expected loss. As experimental design can …