Software release demonstrates automated evaluation of structural complexity in multidimensional psychometric scales, highlighting enhanced assessment of cross-factor loadings.
facomplex R package implements procedures for estimating complexity and simplicity derived from factor-analytic results of multidimensional scales. In this type of analysis, factor loadings are estimated to represent the relationship between the items and their latent factors or constructs, as well as with the other factors in the model where cross-factor loadings are estimated. An evaluation of these cross-factorial loadings helps determine whether the result is factorially simple or complex. There are indicators for assessing the complexity and simplicity of factorial results, and facomplex calculates all known indicators from various approaches focused on the direct estimation of factorial simplicity and complexity at the item, dimension, and total scale levels: the loading simplicity index, the factor simplicity index, Hofmann’s complexity coefficient (for items and factors), the Bentler Simplicity Index, and the proportion of explained variance derived from the squared sum of target versus non-target factor loadings.
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Merino‐Soto et al. (2026) studied this question.
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