A Simulation Study of Factor Score Indeterminacy
通过模拟实验考察因子分析数据特征对因子得分估计准确性的影响，发现不确定性关键取决于共同度水平，且影像因子法比主轴法或主成分分析能更准确检测不确定性。
Though factor analysis continues to be one of the most frequently used multivariate techniques, its value has been questioned because of the indeterminacy of factor scores. The authors review the literature on factor score indeterminacy and discuss the implications of indeterminacy for research practice. A simulation experiment is used to investigate the effects of characteristics of the factor analytic data set on the accuracy of factor score estimation. Indeterminacy is found to depend critically on the level of communality and to be detected more accurately via image factoring than by principal axis or principal component analysis.