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单因素方差分析中加权 eta-squared 效应量的置信区间和样本量计算。

Confidence intervals and sample size calculations for the weighted eta-squared effect sizes in one-way heteroscedastic ANOVA.

机构信息

Department of Management Science, National Chiao Tung University, Hsinchu, Taiwan, 30010, Republic of China.

出版信息

Behav Res Methods. 2013 Mar;45(1):25-37. doi: 10.3758/s13428-012-0228-7.

Abstract

Effect size reporting and interpreting practices have been extensively recommended in academic journals when primary outcomes of all empirical studies have been analyzed. This article presents an alternative approach to constructing confidence intervals of the weighted eta-squared effect size within the context of one-way heteroscedastic ANOVA models. It is shown that the proposed interval procedure has advantages over an existing method in its theoretical justification, computational simplicity, and numerical performance. For design planning, the corresponding sample size procedures for precise interval estimation of the weighted eta-squared association measure are also delineated. Specifically, the developed formulas compute the necessary sample sizes with respect to the considerations of expected confidence interval width and tolerance probability of interval width within a designated value. Supplementary computer programs are provided to aid the implementation of the suggested techniques in practical applications of ANOVA designs when the assumption of homogeneous variances is not tenable.

摘要

在分析所有实证研究的主要结果时,学术期刊广泛推荐报告和解释效应量的做法。本文提出了一种在单向异方差 ANOVA 模型背景下构建加权 eta 平方效应量置信区间的替代方法。结果表明,与现有方法相比,该方法在理论证明、计算简单性和数值性能方面具有优势。对于设计规划,还描述了用于精确区间估计加权 eta 平方关联度量的相应样本量程序。具体来说,开发的公式根据预期置信区间宽度和区间宽度在指定值内的容忍概率考虑,计算了必要的样本量。提供了补充的计算机程序,以在方差分析设计的实际应用中,当方差同质的假设不可行时,帮助实施建议的技术。

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