
Issues in Estimating Interpretable Lower Order Factors in Second-Order Hierarchical Models: Commentary on Clark et al. (2021)
Author(s) -
Tyler M. Moore,
Benjamin B. Lahey
Publication year - 2021
Publication title -
clinical psychological science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.74
H-Index - 47
eISSN - 2167-7034
pISSN - 2167-7026
DOI - 10.1177/21677026211035114
Subject(s) - psychology , order (exchange) , econometrics , factor analysis , structural equation modeling , statistical physics , statistics , mathematics , physics , finance , economics
Clark and colleagues asserted that lower-order factors in second-order models are comparable to specific factors in bifactor models when residualized on the general factor (Clark et al., 2021). Modeling simulated data demonstrated that residualized lower-order factors are correlated with bifactor specific factors only to the extent that factor loadings are proportional. Modeling actual data with violations of proportionality showed that specific and residualized lower-order factors are not always highly correlated and have differential correlations with criterion variables, even when both models fit acceptably. Because proportionality constraints limit only second-order models, bifactor models should be the first option for hierarchical modeling.