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.

翻译：摘要：引言：在探索性因子分析中，斜交目标旋转是研究斜交独立簇模型的重要方法。有研究指出，通过目标旋转最小化单一交叉载荷可能导致抽样误差对旋转因子解产生较大影响。方法：为最小化抽样误差对目标旋转结果的影响，我们提出计算独立簇模型中各显著载荷区块的交叉载荷均值，并对区块均值交叉载荷进行目标旋转。所得转换矩阵随后应用于完整的未旋转载荷矩阵，以生成均值目标旋转因子。结果：基于相关独立因子模型的模拟研究表明，相较于基于单一载荷的传统目标旋转，均值斜交目标旋转产生的因子间相关负向偏差更小，尤其在小样本和多因子条件下更为显著。实证案例显示，基于小子样本计算的均值目标旋转因子与总样本目标旋转因子的相似度优于传统目标旋转。讨论：在斜交独立因子模型的情境下，尤其是面对小样本时，推荐采用均值目标旋转法。附录中提供了该旋转方法的R脚本和SPSS脚本。