Author:

Keywords:

Social Sciences, Psychology, Mathematical, Psychology, Experimental, Psychology, Systematic review, meta-analysis, multiple effect sizes, multilevel models, ROBUST VARIANCE-ESTIMATION, BRIEF ALCOHOL INTERVENTIONS, META-REGRESSION, 3-LEVEL METAANALYSIS, PARENTING INTERVENTIONS, CULTURAL METAANALYSIS, RESISTANCE EXERCISE, MUSCLE HYPERTROPHY, PHYSICAL-ACTIVITY, CASEIN INFUSION, Computer Simulation, Humans, Meta-Analysis as Topic, Multilevel Analysis, 0801 Artificial Intelligence and Image Processing, 1701 Psychology, 1702 Cognitive Sciences, Experimental Psychology, 4905 Statistics, 5202 Biological psychology, 5204 Cognitive and computational psychology

Abstract:

In meta-analysis, study participants are nested within studies, leading to a multilevel data structure. The traditional random effects model can be considered as amodel with a randomstudy effect, but additional random effects can be added in order to account for dependent effects sizes within or across studies. The goal of this systematic review is three-fold. First, we will describe how multilevel models with multiple random effects (i.e., hierarchical three-, four-, five-level models and cross-classified random effects models) are applied in meta-analysis. Second, we will illustrate how in some specific three-level meta-analyses, a more sophisticated model could have been used to deal with additional dependencies in the data. Third and last, we will describe the distribution of the characteristics of multilevel meta-analyses (e.g., distribution of the number of outcomes across studies or which dependencies are typically modeled) so that future simulation studies can simulate more realistic conditions. Results showed that four- or five-level or cross-classified randomeffects models are not often used although theymight account better for the meta-analytic data structure of the analyzed datasets. Also, we found that the simulation studies done on multilevel metaanalysis with multiple random factors could have used more realistic simulation factor conditions. The implications of these results are discussed, and further suggestions are given.