Effect sizes for contrasts of estimated marginal effects

IF 3.2 2区 数学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS
B. Shaw
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引用次数: 1

Abstract

The statistical literature is replete with calls to report standardized measures of effect size alongside traditional p-values and null hypothesis tests. While effect-size measures such as Cohen’s d and Hedges’s g are straightforward to calculate for t tests, this is not the case for parameters in more complex linear models, where traditional effect-size measures such as η 2 and ω 2 face limitations. After a review of effect sizes and their implementation in Stata, I introduce the community-contributed command mces. This postestimation command reports standardized effect-size statistics for dichotomous comparisons of marginal-effect contrasts obtained from margins and mimrgns, including with complex samples, for continuous outcome variables. mces provides Stata users the ability to report straightforward estimates of effect size in many modeling applications.
估计边际效应对比度的效应大小
统计文献中充斥着报告效应大小的标准化测量以及传统p值和零假设检验的呼声。虽然Cohen的d和Hedges的g等效应大小度量对于t检验来说很容易计算,但对于更复杂的线性模型中的参数来说却不是这样,因为η2和ω2等传统效应大小度量面临限制。在回顾了效果大小及其在Stata中的实现之后,我介绍了社区贡献的命令mces。该后估计命令报告了标准化的效应大小统计数据,用于对从边际和最小rgn获得的边际效应对比进行二分比较,包括对连续结果变量的复杂样本。mces为Stata用户提供了在许多建模应用程序中直接报告效应大小估计的能力。
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
Stata Journal
Stata Journal 数学-统计学与概率论
CiteScore
7.80
自引率
4.20%
发文量
44
审稿时长
>12 weeks
期刊介绍: The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.
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