Multilevel multivariate meta-analysis made easy: An introduction to MLMVmeta

The basic random effects meta-analytic model is overwhelmingly dominant in psychological research. Indeed, it is typically employed even when more complex multilevel multivariate meta-analytic models are warranted. In this paper, we aim to help overcome challenges so that multilevel multivariate meta-analytic models will be more often employed in practice. We do so by introducing MLMVmeta-an easy-to-use web application that implements multilevel multivariate meta-analytic methodology that is both specially tailored to contemporary psychological research and easily estimable, interpretable, and parsimonious-and illustrating it across three case studies. The three case studies demonstrate the more accurate and extensive results that can be obtained via multilevel multivariate meta-analytic models. Further, they sequentially build in complexity featuring increasing numbers of experimental factors and conditions, dependent variables, and levels; this in turn necessitates increasingly complex model specifications that also sequentially build upon one another.