Performance of Location-Scale Models in Meta-Analysis: A Simulation Study

Abstract

With the present work, we examine the performance of currently available procedures in the metafor R package for fitting location-scale models in meta-analyses from a frequentist approach. More specifically, the present work consists of a Monte Carlo simulation study in which estimation and inference procedures concerning the coefficients of the scale part of the model (involving the effect of a predictor for the heterogeneity variance component of a meta-analysis) are tested and compared. This work highlights the potential of recently extended location-scale models in the meta-analytical practice and shows their performance under conditions in which many researchers in the health and social sciences would be able to include their research