{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T06:49:52Z","timestamp":1792046992046,"version":"4.4.0"},"reference-count":51,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Res. synth. methods"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Meta-analytic structural equation modeling (MASEM) is a flexible modeling framework that combines the strengths of meta-analysis and structural equation modeling. Despite the increasing popularity of the MASEM technique, its usage and scope are limited to relatively simple meta-analytic data structures and moderator hypotheses. Within-study variability in moderator variables and dependence in primary studies\u2019 correlation estimates tend to be handled using ad hoc methods. In this study, we demonstrate use of multilevel multivariate modeling with robust variance estimation (RVE) for handling within-study dependence when pooling studies\u2019 correlation estimates and we propose how to incorporate categorical moderator values directly into the structural equation model for moderators with values varying within studies. We outline the proposed approach using three stages: (a) specification of the structural equation model using moderator variable categories, (b) pooling correlation matrix elements using the three-level multivariate model with RVE, and (c) testing the moderator hypotheses through either model comparison or direct estimation of structural equation model\u2019s path differences. We illustrate the approach using three examples to demonstrate its flexibility across different MASEM models. This framework broadens the scope of moderator hypotheses that can be tested using MASEM and enhances the methodological rigor for handling dependencies in studies\u2019 correlation estimates for MASEM.<\/jats:p>","DOI":"10.1017\/rsm.2026.10113","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T06:34:02Z","timestamp":1792046042000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":0,"title":["Handling within-study variability in moderators and dependence in correlation coefficients: Meta-analytic structural equation modeling"],"prefix":"10.1017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0172-9106","authenticated-orcid":false,"given":"Jihyun","family":"Lee","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00v97ad02","id-type":"ROR","asserted-by":"publisher"}],"name":"University of North Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. Natasha","family":"Beretvas","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00hj54h04","id-type":"ROR","asserted-by":"publisher"}],"name":"The University of Texas at Austin"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"key":"S1759287926101136_r46","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.107.2.238"},{"key":"S1759287926101136_r2","doi-asserted-by":"publisher","DOI":"10.1002\/9781118957813"},{"key":"S1759287926101136_r7","doi-asserted-by":"publisher","DOI":"10.1111\/j.1744-6570.1995.tb01784.x"},{"key":"S1759287926101136_r41","doi-asserted-by":"publisher","DOI":"10.1023\/A:1025681223921"},{"key":"S1759287926101136_r49","doi-asserted-by":"publisher","DOI":"10.1207\/S15328007SEM0902_5"},{"key":"S1759287926101136_r22","first-page":"16","article-title":"Dealing with dependent effect sizes in MASEM","volume":"230","author":"Stolwijk","year":"2022","journal-title":"Z Psychol"},{"key":"S1759287926101136_r48","volume-title":"EQS Structural Equations Program Manual","volume":"6","author":"Bentler","year":"1995"},{"key":"S1759287926101136_r18","doi-asserted-by":"publisher","DOI":"10.1111\/j.2044-8317.1974.tb00543.x"},{"key":"S1759287926101136_r25","first-page":"1","article-title":"A cautionary note on using univariate methods for meta-analytic structural equation modeling. Advances in methods and practices","volume":"7","author":"Jak","year":"2024","journal-title":"Psychol Sci"},{"key":"S1759287926101136_r36","doi-asserted-by":"publisher","DOI":"10.1002\/jrsm.1498"},{"key":"S1759287926101136_r20","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.108.2.330"},{"key":"S1759287926101136_r5","doi-asserted-by":"publisher","DOI":"10.1037\/1082-989X.10.1.40"},{"key":"S1759287926101136_r28","doi-asserted-by":"publisher","DOI":"10.1037\/met0000011"},{"key":"S1759287926101136_r26","doi-asserted-by":"publisher","DOI":"10.3102\/10769986017004341"},{"key":"S1759287926101136_r31","unstructured":"[31] Pustejovsky, J . clubSandwich: cluster-robust (sandwich) variance estimators with small-sample corrections. 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Published by Cambridge University Press on behalf of The Society for Research Synthesis Methodology","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https:\/\/creativecommons.org\/licenses\/by\/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}