We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and (...) criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. (shrink)

In the present work we investigated distinct sources of construct-relevant psychometric multidimensionality in two sport-specific measures of coaches’ need-supportive (ISS-C) and controlling interpersonal (CCBS) styles. A recently proposed bifactor exploratory structural equation modeling (ESEM) framework was employed to achieve this aim. In Study 1, using a sample of floorball players, the results indicated that the ISS-C can be considered as a unidimensional measure, with one global factor explaining most of the variance in the items. In Study 2, using a sample (...) of male ice hockey players, the results indicated that the items in the CCBS are represented by both a general factor and specific factors, but the subscales differ with regard to the amount of variance in the items accounted for by the general and specific factors. These results add further insight into the psychometric properties of these two measures and the dimensionality of these two constructs. (shrink)