Fitting Flexible Meta-Analytic Models with Structural Equation Modeling

Date of Seminar: October 18, 2024 Speaker: Dr. Mike Cheung, National University of Singapore Description: Understanding the differences between various meta-analytic models, such as the fixed-effect, random-effects, and multiplicative error models, can be challenging for researchers. This presentation explains these models using a graphical representation within a structural equation modeling (SEM) framework. Users specify meta-analytic models using lavaan syntax. The metaSEM package in R can convert these models to graphical models, model-implied mean and variance, and fit models using the Full Information Maximum Likelihood (FIML) estimation method. Complex meta-analytic models, such as multivariate meta-analysis and mediation models, can also be fitted. Users without strong statistical and programming backgrounds can still develop and implement novel meta-analytic models that are not available in standard meta-analysis software.