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Effect size, statistical power, and sample size for assessing interactions between categorical and continuous variables.
British Journal of Mathematical and Statistical Psychology ( IF 2.6 ) Pub Date : 2018-11-23 , DOI: 10.1111/bmsp.12147
Gwowen Shieh

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.

中文翻译:

效应量,统计功效和样本量,用于评估分类变量和连续变量之间的相互作用。

在许多心理学和相关学科的学术期刊中广泛主张对效应大小估计值的报告和解释。但是,对于涉及分类变量和连续变量之间的相互作用的分析,尚未充分解决此类问题。为了改进当前的实践,本文介绍了标准斜率方差的基本特征和理论发展,作为对几种斜率系数之间的差异程度进行合乎需要的标准化效果量度的方法。为了估计效果的大小,描述了一个一致且几乎无偏的估计量,并在适当情况下强调了针对极端情况的简单改进。还考虑了用于检验斜率系数相等性的功效和样本大小计算的基本问题。根据分析论证和经验评估,精确方法比近似方法具有明显的优势。提供了SAS和R计算机代码,以方便在交互研究中实际使用所提出的技术。
更新日期:2018-11-23
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