  Introduction: Oblique Target-rotation in the context of exploratory factor
analysis is a relevant method for the investigation of the oblique independent
clusters model. It was argued that minimizing single cross-loadings by means of
target rotation may lead to large effects of sampling error on the target
rotated factor solutions. Method: In order to minimize effects of sampling
error on results of Target-rotation we propose to compute the mean
cross-loadings for each block of salient loadings of the independent clusters
model and to perform target rotation for the block-wise mean cross-loadings.
The resulting transformation-matrix is than applied to the complete unrotated
loading matrix in order to produce mean Target-rotated factors. Results: A
simulation study based on correlated independent factor models revealed that
mean oblique Target-rotation resulted in smaller negative bias of factor
inter-correlations than conventional Target-rotation based on single loadings,
especially when sample size was small and when the number of factors was large.
An empirical example revealed that the similarity of Target-rotated factors
computed for small subsamples with Target-rotated factors of the total sample
was more pronounced for mean Target-rotation than for conventional
Target-rotation. Discussion: Mean Target-rotation can be recommended in the
context of oblique independent factor models, especially for small samples. An
R-script and an SPSS-script for this form of Target-rotation are provided in
the Appendix.
