{"title":"Heterogeneity in Meta-Analytic Effect Sizes: An Assessment of the Current State of the Literature","authors":"S. Kepes, Wenhao Wang, J. Cortina","doi":"10.1177/10944281231169942","DOIUrl":null,"url":null,"abstract":"Heterogeneity refers to the variability in effect sizes across different samples and is one of the major criteria to judge the importance and advancement of a scientific area. To determine how studies in the organizational sciences address heterogeneity, we conduct two studies. In study 1, we examine how meta-analytic studies conduct heterogeneity assessments and report and interpret the obtained results. To do so, we coded heterogeneity-related information from meta-analytic studies published in five leading journals. We found that most meta-analytic studies report several heterogeneity statistics. At the same time, however, there tends to be a lack of detail and thoroughness in the interpretation of these statistics. In study 2, we review how primary studies report heterogeneity-related results and conclusions from meta-analyses. We found that the quality of the reporting of heterogeneity-related information in primary studies tends to be poor and unrelated to the detail and thoroughness with which meta-analytic studies report and interpret the statistics. Based on our findings, we discuss implications for practice and provide recommendations for how heterogeneity assessments should be conducted and communicated in future research.","PeriodicalId":19689,"journal":{"name":"Organizational Research Methods","volume":" ","pages":""},"PeriodicalIF":8.9000,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Organizational Research Methods","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/10944281231169942","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 1
Abstract
Heterogeneity refers to the variability in effect sizes across different samples and is one of the major criteria to judge the importance and advancement of a scientific area. To determine how studies in the organizational sciences address heterogeneity, we conduct two studies. In study 1, we examine how meta-analytic studies conduct heterogeneity assessments and report and interpret the obtained results. To do so, we coded heterogeneity-related information from meta-analytic studies published in five leading journals. We found that most meta-analytic studies report several heterogeneity statistics. At the same time, however, there tends to be a lack of detail and thoroughness in the interpretation of these statistics. In study 2, we review how primary studies report heterogeneity-related results and conclusions from meta-analyses. We found that the quality of the reporting of heterogeneity-related information in primary studies tends to be poor and unrelated to the detail and thoroughness with which meta-analytic studies report and interpret the statistics. Based on our findings, we discuss implications for practice and provide recommendations for how heterogeneity assessments should be conducted and communicated in future research.
期刊介绍:
Organizational Research Methods (ORM) was founded with the aim of introducing pertinent methodological advancements to researchers in organizational sciences. The objective of ORM is to promote the application of current and emerging methodologies to advance both theory and research practices. Articles are expected to be comprehensible to readers with a background consistent with the methodological and statistical training provided in contemporary organizational sciences doctoral programs. The text should be presented in a manner that facilitates accessibility. For instance, highly technical content should be placed in appendices, and authors are encouraged to include example data and computer code when relevant. Additionally, authors should explicitly outline how their contribution has the potential to advance organizational theory and research practice.