Balanced and Robust Multi-Treatment Experimental Designs via Randomized Differencing

Qing Chen, Jing Jia, Peng Zhang

TL;DR: We propose the first multi-arm RCT design that achieves exponential covariate balance improvements, preserves robustness, and runs in near-linear time.

Abstract: We introduce GKK+, a new design for multi-arm randomized controlled trials. Standard Bernoulli randomization is robust but often yields poor covariate balance, while existing restricted-randomness designs mainly address two-arm settings. GKK+ extends the Karmarkar–Karp (KK) differencing method to multiple arms. When covariates are smooth and well-behaved, GKK+ achieves an exponentially better covariate balance than the standard Bernoulli design while preserving sufficient randomness. GKK+ improves efficiency in estimating treatment effects and supports standard asymptotic inference. Simulations on synthetic and real datasets demonstrate improved balance and lower estimator variance compared to existing methods.

Code Dataset Promise: Yes

Code Dataset Url: https://github.com/jjia131/GKK_plus

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Submission Number: 634