Maximum likelihood estimation of latent interaction effects with the LMS method

作     者：Klein, A Moosbrugger, H 

作者机构：Goethe Univ Frankfurt D-6000 Frankfurt Germany 

出 版 物：《PSYCHOMETRIKA》 (心理测量学)

年 卷 期：2000年第65卷第4期

页      面：457-474页

核心收录：

学科分类：0402[教育学-心理学(可授教育学、理学学位）] 04[教育学] 0701[理学-数学] 

基　　金：Deutsche Forschungsgemeinschaft  DFG  (474/1  Mo 474/2) 

主　　题：latent interaction effects mixture distribution ML estimation structural equation modeling (SEM) EM algorithm 

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.