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Estimating Local Structural Equation Models

Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt. In previous studies, LSEM was fitted as a sequence of mode...

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Detalles Bibliográficos
Autor principal: Robitzsch, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532278/
https://www.ncbi.nlm.nih.gov/pubmed/37754904
http://dx.doi.org/10.3390/jintelligence11090175
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author Robitzsch, Alexander
author_facet Robitzsch, Alexander
author_sort Robitzsch, Alexander
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description Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt. In previous studies, LSEM was fitted as a sequence of models separately evaluated as each value of the moderator variables. In this article, a joint estimation approach is proposed that is a simultaneous estimation method across all moderator values and also allows some model parameters to be invariant with respect to the moderator. Moreover, sufficient details on the main estimation functions in the R package sirt are provided. The practical implementation of LSEM is demonstrated using illustrative datasets and an empirical example. Moreover, two simulation studies investigate the statistical properties of parameter estimation and significance testing in LSEM.
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spelling pubmed-105322782023-09-28 Estimating Local Structural Equation Models Robitzsch, Alexander J Intell Article Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt. In previous studies, LSEM was fitted as a sequence of models separately evaluated as each value of the moderator variables. In this article, a joint estimation approach is proposed that is a simultaneous estimation method across all moderator values and also allows some model parameters to be invariant with respect to the moderator. Moreover, sufficient details on the main estimation functions in the R package sirt are provided. The practical implementation of LSEM is demonstrated using illustrative datasets and an empirical example. Moreover, two simulation studies investigate the statistical properties of parameter estimation and significance testing in LSEM. MDPI 2023-09-01 /pmc/articles/PMC10532278/ /pubmed/37754904 http://dx.doi.org/10.3390/jintelligence11090175 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Robitzsch, Alexander
Estimating Local Structural Equation Models
title Estimating Local Structural Equation Models
title_full Estimating Local Structural Equation Models
title_fullStr Estimating Local Structural Equation Models
title_full_unstemmed Estimating Local Structural Equation Models
title_short Estimating Local Structural Equation Models
title_sort estimating local structural equation models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532278/
https://www.ncbi.nlm.nih.gov/pubmed/37754904
http://dx.doi.org/10.3390/jintelligence11090175
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