{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Speyer LG"],"funding":["Wellcome Trust"],"pagination":["315-327"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7615284"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["30(2)"],"pubmed_abstract":["Random-Intercept Cross-Lagged Panel Models allow for the decomposition of measurements into between- and within-person components and have hence become popular for testing developmental hypotheses. Here, we describe how developmental researchers can implement, test and interpret interaction effects in such models using an empirical example from developmental psychopathology research. We illustrate the analysis of <i>Within × Within</i> and <i>Between × Within</i> interactions utilising data from the United Kingdom-based Millennium Cohort Study within a Bayesian Structural Equation Modelling framework. We provide annotated Mplus code, allowing users to isolate, estimate and interpret the complexities of within-person and between person dynamics as they unfold over time."],"journal":["Structural equation modeling : a multidisciplinary journal"],"pubmed_title":["Testing for <i>Within × Within</i> and <i>Between × Within</i> Moderation using Random Intercept Cross-Lagged Panel Models."],"pmcid":["PMC7615284"],"funding_grant_id":["107496","104908"],"pubmed_authors":["Blakemore SJ","Ushakova A","Murray AL","Speyer LG","Kievit R"],"additional_accession":[]},"is_claimable":false,"name":"Testing for <i>Within × Within</i> and <i>Between × Within</i> Moderation using Random Intercept Cross-Lagged Panel Models.","description":"Random-Intercept Cross-Lagged Panel Models allow for the decomposition of measurements into between- and within-person components and have hence become popular for testing developmental hypotheses. Here, we describe how developmental researchers can implement, test and interpret interaction effects in such models using an empirical example from developmental psychopathology research. We illustrate the analysis of <i>Within × Within</i> and <i>Between × Within</i> interactions utilising data from the United Kingdom-based Millennium Cohort Study within a Bayesian Structural Equation Modelling framework. We provide annotated Mplus code, allowing users to isolate, estimate and interpret the complexities of within-person and between person dynamics as they unfold over time.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Mar","modification":"2025-04-04T14:29:15.858Z","creation":"2025-04-04T14:29:15.858Z"},"accession":"S-EPMC7615284","cross_references":{"pubmed":["37937063"],"doi":["10.31234/osf.io/wktrb"]}}