Bootstrap power analysis offers flexibility for prospective studies, highlighting implications across diverse research designs.
Bootstrapping offers a flexible approach to estimating statistical power, when planning a new study based on a previous one. In this article, we explore both parametric and non-parametric bootstrap power calculations and demonstrate how to incorporate uncertainty about effect size in bootstrap power analysis. We use real examples to illustrate bootstrap power calculations in independent t -test and ANCOVA. Finally, we discuss the broader implications of bootstrap power calculation for a variety of research designs.
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Liu et al. (2025) studied this question.
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