Effect sizes for contrasts of estimated marginal effects

IF 3.2 2区 数学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS Stata Journal Pub Date : 2022-03-01 DOI:10.1177/1536867X221083901
B. Shaw
{"title":"Effect sizes for contrasts of estimated marginal effects","authors":"B. Shaw","doi":"10.1177/1536867X221083901","DOIUrl":null,"url":null,"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.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"134 - 157"},"PeriodicalIF":3.2000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stata Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/1536867X221083901","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Cluster randomized controlled trial analysis at the cluster level: The clan command. mpitb: A toolbox for multidimensional poverty indices Iterative intercensal single-decrement life tables using Stata Facilities for optimizing and designing multiarm multistage (MAMS) randomized controlled trials with binary outcomes hdps: A suite of commands for applying high-dimensional propensity-score approaches
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1