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.
Authors
- Amy Liang
- Paul D. Allison (ORCID: https://orcid.org/0000-0002-0646-5242)
- Nathaniel J. Williams (ORCID: https://orcid.org/0000-0002-3948-7480)
- Kristopher J. Preacher (ORCID: https://orcid.org/0000-0003-4099-3636)
- Sonya K. Sterba
- Steven C. Marcus (ORCID: https://orcid.org/0000-0001-7819-3824)
Institutions
- Boise State University (US)
- Vanderbilt University (US)
- Penn Center for AIDS Research (US)
- Statistical Research (United States) (US)
- University of Pennsylvania (US)
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
Funders
- University of Pennsylvania
- National Institute of Mental Health