Unbalanced 3-Group Split-Ballot Multitrait–Multimethod Design?

Published in Structural Equation Modeling: A Multidisciplinary Journal, 2019

Recommended citation: Revilla, M., Bosch, O. J., & Weber, W. (2019). Unbalanced 3-Group Split-Ballot Multitrait–Multimethod Design?. Structural Equation Modeling: A Multidisciplinary Journal, 26(3), 437-447. https://www.tandfonline.com/doi/abs/10.1080/10705511.2018.1536860

Abstract: A common way of estimating measurement quality is the split-ballot multitrait–multimethod (SB-MTMM) approach. However, this approach leads often to non-convergence or improper solutions when using a 2-group design, whereas the 3-group design performs better. Nevertheless, the 3-group design is rarely implemented because it makes it complicated for applied researchers to use the data. Therefore, we propose to draw groups of unequal sample sizes: two larger groups and one third group as small as possible. Using Monte Carlo simulations and real data analyses, we investigate how well such a design works and which size is needed for the third group. Our results suggest that a 3-group SB-MTMM design with smaller size for the third group (reducing till 5–10%) leads to similar levels of accuracy and no large changes in the model or quality estimates.

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