Dataset for: Dealing with Dependent Effect Sizes in MASEM: A comparison of different approaches using empirical data. Manuscript submitted for publication.

Dataset and codebook for: Stolwijk, I., Jak, S., Eichelsheim, V., & Hoeve, M. (2022). Dealing With Dependent Effect Sizes in MASEM. Zeitschrift für Psychologie, 230(1), 16-32. https://doi.org/10.1027/2151-2604/a000485

The objective of the present study was to examine whether different methods for dealing with dependency in meta-analytic structural equation modeling (MASEM) lead to different results. Four different methods for dealing with dependent effect sizes in MASEM were applied to empirical data, including: (1) ignoring dependency; (2) aggregation; (3) elimination; and (4) a multilevel approach. Random-effects two-stage structural equation modeling was conducted for each method separately, and potential moderators were examined using subgroup analysis. Results demonstrated that the different methods of dealing with dependency in MASEM lead to different results. Thus, the decision on which approach should be used in MASEM-analysis should be carefully considered. Given that the multilevel approach is the only approach that includes all available information while explicitly modeling dependency, it is currently the theoretically preferred approach for dealing with dependency in MASEM. Future research should evaluate the multilevel approach with simulated data.