Using SymPy (Symbolic Python) for Understanding Structural Equation Modeling

Structural Equation Modeling (SEM) continues to grow in popularity with numerous articles, books, courses, and workshops available to help researchers become proficient with SEM quickly. However, few resources are available to help users gain a deep understanding of the analytic steps involved in SE...

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Veröffentlicht in:Structural equation modeling Jg. 31; H. 6; S. 1104 - 1115
Hauptverfasser: Steele, Joel S., Grimm, Kevin J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Routledge 01.11.2024
Psychology Press
Schlagworte:
Estimation
Open-source software
Optimization
Popularity
Python
RAM
SEM
Specification
Structural equation modeling
Structural Equation Models
symbolic math
Syntax
Workshops
ISSN:1070-5511, 1532-8007
Online-Zugang:Volltext
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Zusammenfassung:Structural Equation Modeling (SEM) continues to grow in popularity with numerous articles, books, courses, and workshops available to help researchers become proficient with SEM quickly. However, few resources are available to help users gain a deep understanding of the analytic steps involved in SEM, with even fewer providing reproducible syntax for those learning the technique. This work builds off of the original work by Ferron and Hess to provide computer syntax, written in python, for the specification, estimation, and numerical optimization steps necessary for SEM. The goal is to provide readers with many of the numerical and analytic details of SEM that may not be regularly taught in workshops and courses. This work extends the original demonstration by Ferron and Hess to incorporate the reticular action model notation for specification as well as the estimation of variable means. All of the code listed is provided in the appendix.
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ISSN:1070-5511
1532-8007
DOI:10.1080/10705511.2024.2325122