A commentary on Lv and Maeda (2019)

Meta-analytic structural equation modeling (MASEM) is a statistical technique to fit hypothesized models on the combined data of multiple independent studies. Lv and Maeda (2019) present a simulation study on the performance of three fixed-effects correlation-based MASEM methods with varying levels of data missing completely at random (MCAR). In this commentary, we discuss several coding errors and other issues that we identified, which demonstrate that Lv and Maeda did not evaluate any of the three intended methods. Furthermore, the authors report very surprising results and offer specific recommendations for the application of the three methods; these actions compel us to express our concerns regarding the validity of the conclusions provided by Lv and Maeda.