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

IF 2.9 3区 医学 Q2 PSYCHOLOGY, CLINICAL
Amy Liang, Kristopher J Preacher, Nathaniel J Williams, Paul D Allison, Steven C Marcus, Sonya K Sterba
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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.

仅在给定相应的双侧检验的幂的情况下确定单侧z检验的幂。
估计统计能力是有效设计行为医学研究和节约有限资源的必要条件。有时,行为医学研究人员对多层结构方程模型或多层混合回归模型等复杂模型中单个参数(如斜率)的单侧z检验的计算能力感兴趣。对于这样的模型,计算单侧z检验的功率是很麻烦的,因为:(a)在线z检验功率计算器工具不适用,(b)常用的功率分析软件只提供双侧z检验的功率,不允许改变alpha, (c)出版的功率表通常只提供双侧z检验的功率结果。因此,在这里,我们引入了简单和资源高效的转换公式,通过使用相应的双侧检验的直接功率转换来估计任何模型中单个参数的单侧z检验的功率。然后我们在可访问的R和Excel软件中实现这些转换公式。因此,这篇简短的报告为行为医学研究人员提供了一种方便实用的功率计算解决方案,最大限度地减少了功率估计通常所需的时间、财务和计算资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Behavioral Medicine
Journal of Behavioral Medicine PSYCHOLOGY, CLINICAL-
CiteScore
5.70
自引率
3.20%
发文量
112
期刊介绍: The Journal of Behavioral Medicine is a broadly conceived interdisciplinary publication devoted to furthering understanding of physical health and illness through the knowledge, methods, and techniques of behavioral science. A significant function of the journal is the application of this knowledge to prevention, treatment, and rehabilitation and to the promotion of health at the individual, community, and population levels.The content of the journal spans all areas of basic and applied behavioral medicine research, conducted in and informed by all related disciplines including but not limited to: psychology, medicine, the public health sciences, sociology, anthropology, health economics, nursing, and biostatistics. Topics welcomed include but are not limited to: prevention of disease and health promotion; the effects of psychological stress on physical and psychological functioning; sociocultural influences on health and illness; adherence to medical regimens; the study of health related behaviors including tobacco use, substance use, sexual behavior, physical activity, and obesity; health services research; and behavioral factors in the prevention and treatment of somatic disorders.  Reports of interdisciplinary approaches to research are particularly welcomed.
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