ABSTRACT

A handful of studies have been devoted to nonlinear structural equation modeling (SEM) in the literature. However, they generally overlooked the interactions among exogenous and endogenous latent variables and the interactions among endogenous latent variables. In this study, we propose a maximum likelihood approach for a nonlinear SEM model that incorporates such overlooked interactions. We also propose a two-stage pseudo maximum likelihood approach under the assumption of normal mixture, being computational efficient and robust against distributional misspecification. The simulation study shows that both approaches accurately estimate the unknown parameters if the distribution is correctly specified. However, only the pseudo maximum likelihood approach is robust against distributional misspecification.

摘要

一些研究致力于文献中的非线性结构方程建模 (SEM)。然而，他们普遍忽视了外生和内生潜变量之间的相互作用以及内生潜变量之间的相互作用。在这项研究中，我们为非线性 SEM 模型提出了一种最大似然方法，该模型包含了这种被忽视的相互作用。我们还提出了一种在正常混合假设下的两阶段伪最大似然方法，计算效率高且对分布错误指定具有鲁棒性。模拟研究表明，如果正确指定了分布，两种方法都可以准确估计未知参数。然而，只有伪最大似然方法对分布错误指定是鲁棒的。