Determining the power of a 1-sided z-test given only the power of the corresponding 2-sided test

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.

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Publication Details

Journal
Journal of Behavioral Medicine
Published
2025-09-09
DOI
https://doi.org/10.1007/s10865-025-00595-6
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
0.00

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article

Determining the power of a 1-sided z-test given only the power of the corresponding 2-sided test

Amy Liang, Paul D. Allison, Nathaniel J. Williams, Kristopher J. Preacher et al.
1 links
Journal of Behavioral Medicine
Statistical Methods in Clinical Trials
article

Determining the power of a 1-sided z-test given only the power of the corresponding 2-sided test

Amy Liang, Paul D. Allison, Nathaniel J. Williams, Kristopher J. Preacher, Sonya K. Sterba, Steven C. Marcus
article en

Abstract

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.

Journal of Behavioral Medicine
Boise State University (US), Vanderbilt University (US), Penn Center for AIDS Research (US), Statistical Research (United States) (US), University of Pennsylvania (US)
University of Pennsylvania, National Institute of Mental Health
Openalex Percentile: Top 77%
Statistical Methods in Clinical Trials
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Determining the power of a 1-sided z-test given only the power of the corresponding 2-sided test — Amy Liang, Paul D. Allison, et al. · Journal of Behavioral Medicine (2025) | TGRS Research Map | TGRS