如何描述因子与相应因子得分估计值之间的差异

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
A. Beauducel
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引用次数: 14

摘要

摘要由于因子得分的不确定性,因子的理论意义及其相应的得分估计值可能会发生实质性的变化。因此,应该将原始因子模式与与因子得分估计值相对应的回归成分负荷(Schonemann & Steiger, 1976)进行比较,以检测理论意义上可能发生的变化。特别是对于大载荷矩阵,可以用同余系数来确定原始因子模式与分数估计回归分量的相似度。结果表明,这些一致性包含的信息还没有给出的措施因素得分不确定性。两个例子说明了对不同类型的因子得分估计使用回归成分分析。分析表明,当因子解释基于因子模式时,Bartlett-score估计是最合适的,而在验证性因子分析中通常是这样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to Describe the Difference between Factors and Corresponding Factor-Score Estimates
Abstract. Because of factor score indeterminacy, there can be substantial shifts in the theoretical meaning of factors and their corresponding score estimates. Therefore, the original factor pattern should be compared with the regression-component loadings (Schonemann & Steiger, 1976) corresponding to the factor-score estimates in order to detect possible shifts in the theoretical meaning. Especially with large loading matrices the similarity of the original factor pattern and the regression components of the score estimates may be ascertained by means of congruency coefficients. It is shown that these congruencies contain information that is not already given by measures of factor-score indeterminacy. Two examples illustrate the use of regression-component analysis for different types of factor-score estimates. The analyses reveal that the Bartlett-score estimates are most appropriate when factor interpretation is based on the factor pattern, which is usually the case in confirmatory factor analysis.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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