稳健性(进化)
潜变量
结构方程建模
应用数学
数学
最大似然
期望最大化算法
潜在类模型
背景(考古学)
潜变量模型
混合模型
计算机科学
联立方程模型
数学优化
统计
生物化学
生物
基因
古生物学
化学
作者
Andreas Klein,Helfried Moosbrugger
出处
期刊:Psychometrika
[Springer Nature]
日期:2000-12-01
卷期号:65 (4): 457-474
被引量:1290
摘要
In the context of structural equation modeling, a general interaction model with multiple latent interaction effects is introduced. A stochastic analysis represents the nonnormal distribution of the joint indicator vector as a finite mixture of normal distributions. The Latent Moderated Structural Equations (LMS) approach is a new method developed for the analysis of the general interaction model that utilizes the mixture distribution and provides a ML estimation of model parameters by adapting the EM algorithm. The finite sample properties and the robustness of LMS are discussed. Finally, the applicability of the new method is illustrated by an empirical example.
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