How Different Indicator-Dimension Ratios in Assessment Center Ratings Affect Evidence for Dimension Factors - Buckett, Anne; Becker, Jürgen Reiner; Melchers, Klaus G.; Roodt, Gert (Frontiers in Psychology, 2020)
Previous research on the construct validity of assessment center (AC) ratings has usually struggled to find support for dimension factors as an underlying source of variance of these ratings. Confirmatory factor analysis (CFA) remains the most widely used method to specify and validate the internal structure of AC ratings. However, the research support for dimension effects in AC ratings remains mixed. In addition, competing CFA models (e.g., correlated dimensions-correlated exercises models) are often plagued by non-convergence and estimation problems. Recently it has been proposed that increasing the number of indicators per dimension and exercise combination might help to find support for dimension factors, in addition to exercise factors, in CFAs of AC ratings. Furthermore, it was also suggested that the increased ratio of indicators to dimensions may also solve some of the methodological problems associated with CFA models used to model AC ratings. However, in this research it remained unclear whether the support for dimension factors was solely due to the use of a larger indicator-dimension ratio or due to parceling that combines several behavioral indicators per dimension and exercise combination into more reliable measures of the targeted dimension. These are important empirical questions that have been left unanswered in the literature but can be potentially meaningful in seeking more balanced support for dimension effects in AC research. Using data from N = 213 participants from a one-day AC, we aimed to investigate the impact of using different indicator-dimension ratios when specifying CFA models of AC ratings. Therefore, we investigated the impact of using different indicator-dimension ratios in the form of item parcels with data from an operational AC. On average, using three parcels eventually led to support for dimension factors in CFAs. However, exercise-based CFA models still performed better than dimension-based models. Thus, the present results point out potential limits concerning the generalizability of recent results that provided support for dimension factors in ACs.