Liang Amy, Preacher Kristopher J, Williams Nathaniel J, Allison Paul D, Marcus Steven C, Sterba Sonya K
Department of Psychology and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203‑5721, USA.
School of Social Work, Boise State University, Boise, ID, USA.
J Behav Med. 2025 Sep 9. doi: 10.1007/s10865-025-00595-6.
Estimating statistical power is essential for designing behavioral medicine studies efficiently and conserving finite resources. Sometimes behavioral medicine researchers are interested in calculating power for 1-sided z-tests of individual parameters (e.g., slopes) in complex models such as multilevel structural equation models or multilevel mixture regression models. For such models, calculating power for 1-sided z-tests is cumbersome because: (a) online z-test power calculator tools are inapplicable, (b) commonly-used power analysis software provides power only for 2-sided z-tests and does not allow changing alpha, and (c) published power tables typically provide power results only for 2-sided z-tests. Hence, here we introduce straightforward and resource-efficient conversion formulas to estimate the power of 1-sided z-tests of individual parameters in any model by using direct power conversions from the corresponding 2-sided tests. We then implement these conversion formulas in accessible R and Excel software. This brief report thus provides behavioral medicine researchers with a convenient and practical solution for power calculation that minimizes the time, financial, and computational resources typically needed for power estimation.
估计统计功效对于高效设计行为医学研究和节约有限资源至关重要。有时,行为医学研究人员有兴趣计算复杂模型(如多级结构方程模型或多级混合回归模型)中单个参数(如斜率)的单侧z检验的功效。对于此类模型,计算单侧z检验的功效很麻烦,原因如下:(a)在线z检验功效计算器工具不适用;(b)常用的功效分析软件仅提供双侧z检验的功效,且不允许更改α;(c)已发表的功效表通常仅提供双侧z检验的功效结果。因此,我们在此引入简单且资源高效的转换公式,通过使用相应双侧检验的直接功效转换来估计任何模型中单个参数的单侧z检验的功效。然后,我们在易于使用的R和Excel软件中实现这些转换公式。因此,本简要报告为行为医学研究人员提供了一种方便实用的功效计算解决方案,最大限度地减少了功效估计通常所需的时间、资金和计算资源。