A Simulation Study of Factor Score Indeterminacy
A Simulation Study of Factor Score Indeterminacy
复制标题
因子得分不确定性的模拟研究
DOI：
10.1177/002224378602300203
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发表时间：
1986
影响因子：
6.1
通讯作者：
Ronald D. Anderson
中科院分区：
文献类型：
--
作者：
F. Acito;Ronald D. Anderson
虽然因子分析仍然是最常用的多变量技术之一，但由于因子得分的不确定性，其价值受到质疑。作者回顾了有关因素得分不确定性的文献，并讨论了不确定性对研究实践的影响。通过模拟实验研究了因子分析数据集的特征对因子得分估计准确性的影响。研究发现，不确定性严重依赖于公共性水平，并且通过图像因子分解比主轴或主成分分析更准确地检测到不确定性。
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.