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Main Authors: Fumis, André A. F., Fossaluza, Victor, Stern, Rafael B.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2509.01828
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author Fumis, André A. F.
Fossaluza, Victor
Stern, Rafael B.
author_facet Fumis, André A. F.
Fossaluza, Victor
Stern, Rafael B.
contents We study optimal sample allocation between treatment and control groups under Bayesian linear models. We derive an analytic expression for the Bayes risk, which depends jointly on sample size and covariate mean balance across groups. Under a flat conditional prior, the covariate mean balance term simplifies to the Mahalanobis distance. Our results reveal that the optimal allocation does not always correspond to equal sample sizes, and we provide sufficient conditions under which equal allocation is optimal. Finally, we extend the analysis to sequential settings with groups of patients arriving over time.
format Preprint
id arxiv_https___arxiv_org_abs_2509_01828
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Covariate balance under Bayesian decision theory
Fumis, André A. F.
Fossaluza, Victor
Stern, Rafael B.
Statistics Theory
We study optimal sample allocation between treatment and control groups under Bayesian linear models. We derive an analytic expression for the Bayes risk, which depends jointly on sample size and covariate mean balance across groups. Under a flat conditional prior, the covariate mean balance term simplifies to the Mahalanobis distance. Our results reveal that the optimal allocation does not always correspond to equal sample sizes, and we provide sufficient conditions under which equal allocation is optimal. Finally, we extend the analysis to sequential settings with groups of patients arriving over time.
title Covariate balance under Bayesian decision theory
topic Statistics Theory
url https://arxiv.org/abs/2509.01828