A note on extending Steiger's (1998) multiple sample RMSEA adjustment to other noncentrality parameter-based statistics
A note on extending Steiger's (1998) multiple sample RMSEA adjustment to other noncentrality parameter-based statistics
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DOI：
10.1207/s15328007sem1103_1
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发表时间：
2004-01-01
影响因子：
6
通讯作者：
Dudgeon, P
中科院分区：
文献类型：
--
作者：
Dudgeon, P
本文考虑了Steiger（1998）多样本调整对近似均方根误差（RMSEA）测量的其他非中心性参数统计的影响。当一个结构方程模型同时拟合在一个以上的样本，它示出的非中心性参数的计算中使用的近似拟合和其他非中心拟合统计量（除了预期的交叉验证指数）的点和区间估计的测试也需要一个志同道合的调整。此外，它表明，调整是需要在多个样本模型中正确计算MacCallum，Browne，Sugawara（1996）的方法，功率分析。这些建议的准确性进行了研究，并证明在一个小的Monte Carlo研究中，特别注意使用适当构造的协方差矩阵，给出指定的非零人口差异值下的最大似然估计。
This article considers the implications for other noncentrality parameter-based statistics from Steiger's (1998) multiple sample adjustment to the root mean square error of approximation (RMSEA) measure. When a structural equation model is fitted simultaneously in more than 1 sample, it is shown that the calculation of the noncentrality parameter used in tests of approximate fit and in point and interval estimators of other noncentral fit statistics (except the expected cross-validation index) also requires a likeminded adjustment. Furthermore, it is shown that an adjustment is needed in multiple sample models for correctly calculating MacCallum, Browne, and Sugawara's (1996) approach to power analysis. The accuracy of these proposals is investigated and demonstrated in a small Monte Carlo study in which particular attention is paid to using appropriately constructed covariance matrices that give specified nonzero population discrepancy values under maximum likelihood estimation.