“…">For the bifactor CFA and bifactor ESEM models, we calculated: (a) model‐based composite reliabilities for the total scale and each subscale using omega (ω) coefficients, an estimate of the proportion of observed total or subscale variance due to all sources of common variance (McDonald, ); (b) omega hierarchical (ω H ), an estimate of the proportion of observed total variance due to the GF after accounting for all specific factors; (c) omega hierarchical subscale (ω HS ), an estimate of the proportion of observed subscale variance due to its specific factor after accounting for the GF; (d) explained common variance for the general factor (ECVg), an estimate of the proportion of total common variance explained by the GF; (e) explained common variance for each subscale (ECVs), an estimate of the proportion of each subscale common variance explained by its specific factor; (f) percent of uncontaminated correlations (PUC), a measure related to the structure of the instrument, becoming larger when there are many items and many small group factors. PUC in conjunction with ECVg and ω H , hence called “general factor strength indices,” determine the parameter bias in considering a bifactor model as essentially unidimensional (Bonifay, Reise, Scheines, & Meijer, ; Reise, Scheines, Widaman, & Haviland, ; Rodriguez, Reise, & Haviland, , ). For example, when PUC > 0.8, ECVg values become less important in predicting parameter bias; if PUC < 0.8, then ECVg > 0.6 and ω H > .7 suggest that the instrument can be considered as unidimensional despite the presence of some multidimensionality (Reise et al, ). …”