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使用潜在均值的验证性测量模型比较

Confirmatory Measurement Model Comparisons Using Latent Means.

作者信息

Millsap R E, Everson H

出版信息

Multivariate Behav Res. 1991 Jul 1;26(3):479-97. doi: 10.1207/s15327906mbr2603_6.

Abstract

Confirmatory factor analysis (CFA) is often used to verify measurement models derived from classical test theory: the parallel, tau-equivalent, and congeneric test models. In this application, CFA is traditionally applied to the observed covariance or correlation matrix, ignoring the observed mean structure. But CFA is easily extended to allow nonzero observed and latent means. The use of CFA with nonzero latent means in testing six measurement models derived from classical test theory is discussed. Three of these models have not been addressed previously in the context of CFA. The implications of the six models for observed mean and covariance structures are fully described. Three examples of the use of CFA in testing these models are presented. Some advantages and limitations in using CFA with nonzero latent means to verify classical measurement models are discussed.

摘要

验证性因素分析(CFA)常用于验证源自经典测试理论的测量模型:平行测试模型、τ 等价测试模型和同属测试模型。在这种应用中,传统上 CFA 应用于观测协方差或相关矩阵,而忽略观测均值结构。但 CFA 很容易扩展以允许非零的观测均值和潜在均值。本文讨论了在测试源自经典测试理论的六个测量模型时使用具有非零潜在均值的 CFA。其中三个模型此前在 CFA 的背景下未被探讨过。充分描述了这六个模型对观测均值和协方差结构的影响。给出了使用 CFA 测试这些模型的三个示例。讨论了使用具有非零潜在均值的 CFA 来验证经典测量模型的一些优点和局限性。

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