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Four factor pattern coefficients cross-loaded on the two factors (>.30) in the 2-factor solution, model fit was not deemed satisfactory, and we considered the 3-factor solution.
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To determine the final solution several model fit indicators were used [ 23].
Multilevel CFA models revealed that the correlated eight-factor solution provided better model fit than the two-factor solution at both the between-person and within-person levels.
The 2-factor solution was preferred over the 1-factor solution based on model fit indices.
The 2-factor solution provided the best model fit.
Using principal component analysis with direct oblimin rotation, and applying Kaiser's "Eigen values greater than one" rule, factors were retained that gave the most interpretable solution and best overall model fit.
A confirmatory factor analysis resulted in a revised three-factor solution with a satisfactory overall model fit.
Confirmatory factor analysis modelling of the exploratory solution also yielded a good model fit with item correlated errors.
This resulted in a 10-item solution demonstrating a good Rasch model fit for individual items (see online supplementary material) and the 10 items in aggregate (Chi-squared 16.2, p=0.7).
The solution to the model fitting problems associated with the reduced variance of EBV and the inconsistent regression of EBV on genotype according to reliability can both be addressed by inflating the EBV.
The main criteria for factor extraction were factor solutions based on eigenvalues > 1.0, model fit indices, and conceptual usefulness.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com