Multigroup confirmatory factor analysis: Locating the invariant referent sets
Multigroup confirmatory factor analysis: Locating the invariant referent sets
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DOI：
10.1080/10705510701758349
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发表时间：
2008-01-01
影响因子：
6
通讯作者：
Finch, W. Holmes
中科院分区：
文献类型：
--
作者：
French, Brian F.;Finch, W. Holmes
多组验证性因素分析（MCFA）是检验测量不变性，特别是因素不变性的常用方法。最近的研究已经开始关注使用MCFA来检测测试项目的不变性。MCFA需要某些参数（例如，因子载荷）被约束以用于模型识别，其被假设为跨组不变，并且充当参考变量。当这个不变性假设被违反时，在组之间实际上不同的参数的位置变得困难。因子比检验和逐步分割过程相结合的方法来定位不变的参考，并表现出良好的真实的数据的例子。然而，这些程序还没有通过模拟进行评估，其中缺乏不变性的程度和幅度是已知的。本模拟研究在准确性方面检查了这些方法（即，真阳性率和假阳性率）识别不变的所指变量。
Multigroup confirmatory factor analysis (MCFA) is a popular method for the examination of measurement invariance and specifically, factor invariance. Recent research has begun to focus on using MCFA to detect invariance for test items. MCFA requires certain parameters (e.g., factor loadings) to be constrained for model identification, which are assumed to be invariant across groups, and act as referent variables. When this invariance assumption is violated, location of the parameters that actually differ across groups becomes difficult. The factor ratio test and the stepwise partitioning procedure in combination have been suggested as methods to locate invariant referents, and appear to perform favorably with real data examples. However, the procedures have not been evaluated through simulations where the extent and magnitude of a lack of invariance is known. This simulation study examines these methods in terms of accuracy (i.e., true positive and false positive rates) of identifying invariant referent variables.