Method for Sample Size Determination for Cluster-Randomized Trials Using the Bayes Factor

Camila Natalia Barragan Ibanez; Mirjam Moerbeek

doi:10.3102/10769986251362404

Method for Sample Size Determination for Cluster-Randomized Trials Using the Bayes Factor

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Determining sample size is crucial in research study design. The hierarchical structure of the data in cluster-randomized trials (CRTs) complicates this process, thereby necessitating the determination of the sample size at each level. Most methods for these trials are based on null hypothesis significance testing, which has numerous pitfalls. Using the Bayes factor may avoid these drawbacks, but existing methods are limited to trials without a multilevel structure. This study presents a method to determine the sample size for a one-period two-treatment parallel CRT using the Bayes factor. We introduce the implementation of this method in an R package. Simulation results show that the required sample size increases with decreasing effect sizes and with increasing intraclass correlation and Bayes factors.

Original language	English
Number of pages	33
Journal	Journal of Educational and Behavioral Statistics
DOIs	https://doi.org/10.3102/10769986251362404
Publication status	E-pub ahead of print - Sept 2025

Bibliographical note

Publisher Copyright:
© 2025 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 Lficense (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by the Netherlands Organisation of Scientific Research (NWO), grant number 406.21.GO.006.

Funders	Funder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	406.21

Keywords

Bayes factor
cluster-randomized trials
multilevel model
sample size
sample size determination

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10.3102/10769986251362404Licence: CC BY

Cite this

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title = "Method for Sample Size Determination for Cluster-Randomized Trials Using the Bayes Factor",

abstract = "Determining sample size is crucial in research study design. The hierarchical structure of the data in cluster-randomized trials (CRTs) complicates this process, thereby necessitating the determination of the sample size at each level. Most methods for these trials are based on null hypothesis significance testing, which has numerous pitfalls. Using the Bayes factor may avoid these drawbacks, but existing methods are limited to trials without a multilevel structure. This study presents a method to determine the sample size for a one-period two-treatment parallel CRT using the Bayes factor. We introduce the implementation of this method in an R package. Simulation results show that the required sample size increases with decreasing effect sizes and with increasing intraclass correlation and Bayes factors.",

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Method for Sample Size Determination for Cluster-Randomized Trials Using the Bayes Factor

Abstract

Bibliographical note

Funding

Keywords

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