  In the context of confirmatory factor analysis, the independent clusters
model has been found to be overly restrictive in several research contexts.
Therefore, a less restrictive criterion for parsimony of non-salient loadings
in confirmatory factor analysis was proposed. The criterion is based on
'buffered scales', which have been introduced by Cattell and Tsujioka (1964) as
optimal indicators of corresponding factors. Variables with positive and
negative 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 here
to specify a balance of positive and negative secondary loadings by means of
model constraints in order to achieve parsimony of loading patterns. The
specification of buffered simple structure by means of model constraints was
illustrated by means of a simulation study and an empirical example.

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