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评估分类变量与连续变量之间相互作用的效应量、统计功效和样本量。

Effect size, statistical power, and sample size for assessing interactions between categorical and continuous variables.

作者信息

Shieh Gwowen

机构信息

Department of Management Science, National Chiao Tung University, Hsinchu, Taiwan.

出版信息

Br J Math Stat Psychol. 2019 Feb;72(1):136-154. doi: 10.1111/bmsp.12147. Epub 2018 Nov 23.

Abstract

The reporting and interpretation of effect size estimates are widely advocated in many academic journals of psychology and related disciplines. However, such concern has not been adequately addressed for analyses involving interactions between categorical and continuous variables. For the purpose of improving current practice, this article presents fundamental features and theoretical developments for the variance of standardized slopes as a desirable standardized effect size measure for the degree of disparity between several slope coefficients. To estimate the effect size, a consistent and nearly unbiased estimator is described and a simple refinement is emphasized for extreme situations whenever appropriate. The essential problems of power and sample size calculations for testing the equality of slope coefficients are also considered. According to the analytic justification and empirical assessment, the exact approach has a clear advantage over the approximate methods. Both SAS and R computer codes are provided to facilitate practical accessibility of the proposed techniques in interaction studies.

摘要

在许多心理学及相关学科的学术期刊中,效应量估计值的报告与解释受到广泛提倡。然而,对于涉及分类变量与连续变量交互作用的分析,此类关注尚未得到充分解决。为改进当前的做法,本文介绍了标准化斜率方差的基本特征和理论发展,将其作为衡量几个斜率系数之间差异程度的理想标准化效应量指标。为估计效应量,本文描述了一个一致且几乎无偏的估计量,并在适当的时候针对极端情况强调了一种简单的改进方法。还考虑了用于检验斜率系数相等性的功效和样本量计算的基本问题。根据分析论证和实证评估,精确方法比近似方法具有明显优势。本文提供了SAS和R计算机代码,以促进所提技术在交互作用研究中的实际应用。

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