Power and sensitivity of alternative fit indices in tests of measurement invariance
Power and sensitivity of alternative fit indices in tests of measurement invariance
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DOI：
10.1037/0021-9010.93.3.568
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发表时间：
2008-05-01
影响因子：
9.9
通讯作者：
Braddy, Phillip W.
中科院分区：
文献类型：
--
作者：
Meade, Adam W.;Johnson, Emily C.;Braddy, Phillip W.
基于卡方统计量的测量不变性验证性因子分析检验对样本量高度敏感。为此，G.W.Cheung和R.B.Rensvold(2002)建议在MI调查中使用替代拟合指数(AFI)。在这篇文章中，作者研究了模拟数据不是不变的情况下自动指纹识别系统的性能。结果表明，与基于卡方检验的MI相比，AFI对样本大小的敏感性要低得多，而对缺乏不变性的敏感性更高。作者建议报告比较匹配指数(CFI)和R.P.McDonald‘s(1989)非中心性指数(NCI)的差异来评估MI是否存在。虽然CFI的一般变化值(0.002)似乎在分析中表现良好，但麦当劳NCI值的特定条件变化表现出比麦当劳NCI值的单一变化更好的表现。提供了这些值的表格，以及MI测试中最佳实践的建议。
Confirmatory factor analytic tests of measurement invariance (MI) based on the chi-square statistic are known to be highly sensitive to sample size. For this reason, G. W. Cheung and R. B. Rensvold (2002) recommended using alternative fit indices (AFIs) in MI investigations. In this article, the authors investigated the performance of AFIs with simulated data known to not be invariant. The results indicate that AFIs are much less sensitive to sample size and are more sensitive to a lack of invariance than chi-square-based tests of MI. The authors suggest reporting differences in comparative fit index (CFI) and R. P. McDonald's (1989) noncentrality index (NCI) to evaluate whether MI exists. Although a general value of change in CFI (.002) seemed to perform well in the analyses, condition specific change in McDonald's NCI values exhibited better performance than a single change in McDonald's NCI value. Tables of these values are provided as are recommendations for best practices in MI testing.