Improving the Interpretability of the Variances of Latent Variables by Uniform and Factor-Specific Standardizations of Loadings
Abstract
The variances of latent variables are presented as statistics that support the evaluation of a model in confirmatory factor analysis. Appropriate standardization even improves the benefit of investigating variances. The variances integrate the information concerning the individual loadings and are associated with an error probability. The estimation of the variances of latent variables requires the estimation of the loadings in the first step and their replacement by constraints according to the estimates in the second step. Uniform or factor-specific standardization is necessary for achieving comparability of the variances. The usefulness of standardization is demonstrated in models from optimism research. Three ways of standardization were considered: uniform standardization, factor-specific standardization, and standardization by setting one loading equal to one. Generally valid results were achieved by uniform standardization. If some loadings were set equal to zero, factor-specific standardization even yielded better results. The results of the remaining way were very specific.
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