Maximum Likelihood Estimation of Latent Interaction Effects with the LMS Method
Abstract
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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The research model results were robust across covariance-based SEM (ML), ULS, and LMS estimators.
“A Maximum Likelihood (ML) estimator provided path coefficients for the hypothesized paths that were consistent with those reported here (there were some marginal differences in the significance level of one control variable).”
From Trust, Satisfaction, and Online Repurchase Intention: The Moderating Role of Perceived Effectiveness of E-Commerce Institutional Mechanisms1 (2014) · cites this paper as Klein and Moosbrugger 2000
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- Authors
- Klein, A., & Moosbrugger, H.
- Affiliations
- Goethe University Frankfurt (DE)
- Corresponding author
- Klein, Andreas
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 2000-12
- Volume
- 65
- Issue
- 4
- Pages
- 457-474
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2024507896
- Cited by
- 1,429
- References
- 1
- Citations by year
- 2026: 130 · 2025: 93 · 2024: 82 · 2023: 88 · 2022: 101 · 2021: 112 · 2020: 100 · 2019: 107 · 2018: 84 · 2017: 79 · 2016: 65 · 2015: 64 · 2014: 58 · 2013: 56 · 2012: 48
- FWCI
- 3.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychometrika (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- LMS algorithm, maximum likelihood estimation, expectation-maximization algorithm, finite sample properties, robustness, structural equation modeling
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