Now You See Them, Now You Do Not: The Influence of Indicator–Factor Ratio on Support for Assessment Center Dimensions

Abstract

The inability of assessment center (AC) researchers to find admissible solutions for confirmatory factor analytic (CFA) models that include dimensions has led some to conclude that ACs do not measure dimensions at all. This study investigated whether increasing the indicator–factor ratio facilitates the achievement of convergent and admissible CFA solutions in 2 independent ACs. Results revealed that, when models specify multiple behavioral checklist items as manifest indicators of each latent dimension, all of the AC CFA models tested were identified and returned proper solutions. When armed with the ability to undertake a full set of model comparisons using model fit rather than solution convergence and admissibility as comparative criteria, we found clear evidence for modest dimension effects. These results suggest that the frequent failure to find dimensions in models of the internal structure of ACs is a methodological artifact and that one approach to increase the likelihood for reaching a proper solution is to increase the number of manifest indicators for each dimension factor. In addition, across exercise dimension ratings and the overall assessment rating were both strongly correlated with dimension and exercise factors, indicating that regardless of how an AC is scored, exercise variance will continue to play a key role in the scoring of ACs.