Covariate balance under Bayesian decision theory
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914017127170048 |
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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 |