Maximum Likelihood Estimation of Latent Interaction Effects with the LMS Method

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 E...

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Bibliographic Details
Published inPsychometrika Vol. 65; no. 4; pp. 457 - 474
Main Authors Klein, Andreas, Moosbrugger, Helfried
Format Journal Article
LanguageEnglish
Published Heidelberg Springer 01.12.2000
Psychometric Society, etc
Subjects
Biological and medical sciences
Fundamental and applied biological sciences. Psychology
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics. Statistics. Methodology
Statistics. Mathematics
Statistical method
Parameter estimation
Structural equation modeling
Statistical interaction
Latent variable model
Maximum likelihood
EM algorithm
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ISSN0033-3123
1860-0980
DOI10.1007/BF02296338

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Summary: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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ISSN:0033-3123
1860-0980
DOI:10.1007/BF02296338