Balanced and Robust Multi-Treatment Experimental Designs via Randomized Differencing
Qing Chen · Jing Jia · Peng Zhang
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 treatment effect estimation while supporting standard asymptotic inference. Simulations on synthetic and real datasets demonstrate improved balance and lower estimator variance compared to existing methods.
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