ESMARConf2023: Location-scale models for meta-analysis using the metafor package
Channel: ESMARConf
Date: 29/03/2023

Presenter: Wolfgang Viechtbauer
Authors: Viechtbauer, Wolfgang
Session: Quantitative synthesis 1
Title: Location-scale models for meta-analysis using the metafor package
Abstract: The purpose of most meta-analyses is to estimate the size of the average effect and/or to examine under what circumstances the effect tends to be higher/lower. However, equally important is the question how much the effect varies across studies. The latter question is focused on the amount of heterogeneity in the effects, which we can estimate under a random-effects model using well-established methods. However, these methods assume that the amount of heterogeneity does not depend on the study characteristics and hence is assumed to be constant (homoscedastic). An extension of the standard random-effects model - the meta-analytic location-scale model - relaxes this assumption and allows researchers to examine under what circumstances the amount of heterogeneity tends to be higher/lower. In this tutorial, I will demonstrate how such location-scale models can be fitted using the metafor package and discuss the potential and limitations of such models.
GitHub repository: https://github.com/wviechtb/metafor