A flexible approach to identify interaction effects between moderators in meta-analysis.

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

SUBMITTER: Li X 

PROVIDER: S-EPMC6590644 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature