On the performance of maximum likelihood versus means and variance adjusted weighted least squares estimation in CFA
On the performance of maximum likelihood versus means and variance adjusted weighted least squares estimation in CFA
复制标题
DOI：
10.1207/s15328007sem1302_2
复制
发表时间：
2006-01-01
影响因子：
6
通讯作者：
Herzberg, PY
中科院分区：
文献类型：
--
作者：
Beauducel, A;Herzberg, PY
本模拟研究比较了最大似然（ML）估计与加权最小二乘均值和方差调整（WLSMV）估计。本研究基于验证性因子分析，包括1、2、4和8个因素，基于250、500、750和1000个病例，以及5、10、20和40个变量，包括2、3、4、5和6个类别。没有模型规格错误。最重要的结果是，根据α水平，对于2和3类，WLSMV卡方检验的拒绝率更符合预期的拒绝率。0.05比ML卡方检验的拒绝率高。当变量只有2个或3个类别时，通过WLSMV可以更准确地估计负载的大小。WLSMV估计的样本量不需要大于ML估计的样本量。
This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no model misspecification. The most important results were that with 2 and 3 categories the rejection rates of the WLSMV chi-square test corresponded much more to the expected rejection rates according to an alpha level of .05 than the rejection rates of the ML chi-square test. The magnitude of the loadings was more precisely estimated by means of WLSMV when the variables had only 2 or 3 categories. The sample size for WLSMV estimation needed not to be larger than the sample size for ML estimation.