Optimizing the use of simulation methods in multilevel sample size calculations

Browne, William John, Charlton, Christopher Michael John, Price, Toni, Leckie, George and Steele, Fiona ORCID: 0000-0001-6417-7444 (2025) Optimizing the use of simulation methods in multilevel sample size calculations. Journal of Educational and Behavioral Statistics. ISSN 1076-9986

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Abstract

Simulation-based methods are an alternative approach to sample size calculations, particularly for complex multilevel models where analytical calculations may be less straightforward. A criticism of simulation-based approaches is that they are computationally intensive, so in this paper we contrast different approaches of using the information within each simulation and sharing information across scenarios. We describe the “standard error” method (using the known effect estimate and simulations to estimate the standard error for a scenario) and show that it requires far fewer simulations than other methods. We also show that transforming power calculations onto different scales results in linear relationships with a particular family of functions of the sample size to be optimized, resulting in an easy route to sharing information across scenarios.

Item Type:	Article
Additional Information:	© 2025 The Author(s)
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	18 Jul 2025 11:48
Last Modified:	18 Jul 2025 12:03
URI:	http://eprints.lse.ac.uk/id/eprint/128881

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