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检查因子得分分布以确定潜在空间的性质。

Examining Factor Score Distributions to Determine the Nature of Latent Spaces.

机构信息

a University of Missouri-Columbia.

b University of Illinois , Urbana-Champaign.

出版信息

Multivariate Behav Res. 2007 Jan-Mar;42(1):133-56. doi: 10.1080/00273170701341217.

Abstract

Similarities between latent class models with K classes and linear factor models with K - 1 factors are investigated. Specifically, the mathematical equivalence between the covariance structure of the two models is discussed, and a Monte Carlo simulation is performed using generated data that represents both latent factors and latent classes with known amounts of overlap. It is shown that, under certain conditions, the distribution of factor scores can be related to the continuity of the latent space via tests of multimodality as suggested by McDonald (1967) .

摘要

研究了具有 K 个类别的潜在类别模型和具有 K-1 个因子的线性因子模型之间的相似性。具体来说,讨论了这两种模型的协方差结构的数学等价性,并使用代表具有已知重叠量的潜在因子和潜在类别的生成数据进行了蒙特卡罗模拟。结果表明,在某些条件下,因子得分的分布可以通过 McDonald(1967)提出的多峰性检验与潜在空间的连续性相关。

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