Relative importance analysis in multiple mediator models.

IF 7.6 1区心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY

Psychological methods Pub Date : 2025-02-13 DOI:10.1037/met0000725

Xun Zhu, Xin Gu

{"title":"Relative importance analysis in multiple mediator models.","authors":"Xun Zhu, Xin Gu","doi":"10.1037/met0000725","DOIUrl":null,"url":null,"abstract":"Mediation analysis is widely used in psychological research to identify the relationship between independent and dependent variables through mediators. Assessing the relative importance of mediators in parallel mediator models can help researchers better understand mediation effects and guide interventions. The traditional coefficient-based measures of indirect effect merely focus on the partial effect of each mediator, which may reach undesirable results of importance assessment. This study develops a new method of measuring the importance of multiple mediators. Three R² measures of indirect effect proposed by MacKinnon (2008) are extended to parallel mediator models. Dominance analysis, a popular method of evaluating relative importance, is applied to decompose the R² indirect effect and attribute it to each mediator. This offers new measures of indirect effect in terms of relative importance. Both frequentist and Bayesian methods are used to make statistical inference for the dominance measures. Simulation studies investigate the performance of the dominance measures and their inference. A real data example illustrates how the relative importance can be assessed in multiple mediator models. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6000,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological methods","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/met0000725","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Mediation analysis is widely used in psychological research to identify the relationship between independent and dependent variables through mediators. Assessing the relative importance of mediators in parallel mediator models can help researchers better understand mediation effects and guide interventions. The traditional coefficient-based measures of indirect effect merely focus on the partial effect of each mediator, which may reach undesirable results of importance assessment. This study develops a new method of measuring the importance of multiple mediators. Three R² measures of indirect effect proposed by MacKinnon (2008) are extended to parallel mediator models. Dominance analysis, a popular method of evaluating relative importance, is applied to decompose the R² indirect effect and attribute it to each mediator. This offers new measures of indirect effect in terms of relative importance. Both frequentist and Bayesian methods are used to make statistical inference for the dominance measures. Simulation studies investigate the performance of the dominance measures and their inference. A real data example illustrates how the relative importance can be assessed in multiple mediator models. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

查看原文本刊更多论文

多中介模型的相对重要性分析。

中介分析在心理学研究中被广泛应用，通过中介来识别自变量和因变量之间的关系。在平行中介模型中评估中介的相对重要性可以帮助研究者更好地理解中介效应并指导干预。传统的基于系数的间接效应度量只关注各中介的局部效应，可能会得到不理想的重要性评估结果。本研究提出了一种新的测量多重介质重要性的方法。MacKinnon（2008）提出的间接效应的三个R²度量被扩展到平行中介模型。优势分析是一种评价相对重要性的常用方法，该方法用于分解R²间接效应并将其归因于每个中介。这就间接影响的相对重要性提供了新的衡量标准。利用频率论和贝叶斯方法对优势度测度进行统计推断。仿真研究考察了优势度量及其推断的性能。一个真实的数据示例说明了如何在多个中介模型中评估相对重要性。（PsycInfo Database Record (c) 2025 APA，版权所有）。

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分钟内获得全文求助全文

来源期刊

Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-

CiteScore

13.10

自引率

7.10%

发文量

159

期刊介绍： Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.