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In the context of confirmatory factor analysis, the independent clustersmodel has been found to be overly restrictive in several research contexts.Therefore, a less restrictive criterion for parsimony of non-salient loadingsin confirmatory factor analysis was proposed. The criterion is based on'buffered scales', which have been introduced by Cattell and Tsujioka (1964) asoptimal indicators of corresponding factors. Variables with positive andnegative loadings on an unwanted factor are balanced out in a buffered scale,so that the variance of the unwanted factor is at minimum. It is proposed hereto specify a balance of positive and negative secondary loadings by means ofmodel constraints in order to achieve parsimony of loading patterns. Thespecification of buffered simple structure by means of model constraints wasillustrated by means of a simulation study and an empirical example.

Constraints for non-zero secondary loadings in confirmatory factor analysis