Ogasawara Haruhiko
Department of Information and Management Science, Otaru University of Commerce, Japan.
Br J Math Stat Psychol. 2002 Nov;55(Pt 2):213-29. doi: 10.1348/000711002760554552.
Asymptotic standard errors of the estimated asymptotic standard errors for parameter estimates in structural equation modelling are derived using the delta method with the assumption of multivariate normality for observed variables. The derivation covers the cases with and without restrictions on parameters. The result can be used to derive the asymptotic standard error of the z score (a parameter estimate divided by its estimated standard error), which is frequently substantially different from one. The case of standardized observed variables is dealt with as a typical example with restrictions on parameters. For actual covariance (correlation) structure models, the exploratory factor analysis model with factor rotation and the confirmatory factor analysis model are presented with numerical examples. Simulations are performed to assess the accuracy of our method for normally and non-normally distributed variables.
在观测变量服从多元正态分布的假设下,使用德尔塔方法推导结构方程模型中参数估计的渐近标准误差的估计渐近标准误差。该推导涵盖了参数有约束和无约束的情况。该结果可用于推导z分数(参数估计值除以其估计标准误差)的渐近标准误差,其通常与1有很大差异。以标准化观测变量的情况作为参数有约束的典型例子进行处理。对于实际的协方差(相关)结构模型,给出了带有因子旋转的探索性因子分析模型和验证性因子分析模型的数值示例。进行模拟以评估我们的方法对于正态分布和非正态分布变量的准确性。