{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["10(1)"],"submitter":["Li X"],"pubmed_abstract":["In meta-analytic studies, there are often multiple moderators available (eg, study characteristics). In such cases, traditional meta-analysis methods often lack sufficient power to investigate interaction effects between moderators, especially high-order interactions. To overcome this problem, meta-CART was proposed: an approach that applies classification and regression trees (CART) to identify interactions, and then subgroup meta-analysis to test the significance of moderator effects. The aim of this study is to improve meta-CART upon two aspects: 1) to integrate the two steps of the approach into one and 2) to consistently take into account the fixed-effect or random-effects assumption in both the the interaction identification and testing process. For fixed effect meta-CART, weights ar"],"journal":["Research synthesis methods"],"pagination":["134-152"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6590644"],"repository":["biostudies-literature"],"pubmed_title":["A flexible approach to identify interaction effects between moderators in meta-analysis."],"pmcid":["PMC6590644"],"pubmed_authors":["Li X","Dusseldorp E","Meulman JJ"],"additional_accession":[]},"is_claimable":false,"name":"A flexible approach to identify interaction effects between moderators in meta-analysis.","description":"In meta-analytic studies, there are often multiple moderators available (eg, study characteristics). In such cases, traditional meta-analysis methods often lack sufficient power to investigate interaction effects between moderators, especially high-order interactions. To overcome this problem, meta-CART was proposed: an approach that applies classification and regression trees (CART) to identify interactions, and then subgroup meta-analysis to test the significance of moderator effects. The aim of this study is to improve meta-CART upon two aspects: 1) to integrate the two steps of the approach into one and 2) to consistently take into account the fixed-effect or random-effects assumption in both the the interaction identification and testing process. For fixed effect meta-CART, weights ar","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Mar","modification":"2025-04-04T21:00:09.323Z","creation":"2019-07-24T07:27:13Z"},"accession":"S-EPMC6590644","cross_references":{"pubmed":["30511514"],"doi":["10.1002/jrsm.1334"]}}