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A Classical and Bayesian Approach for Parameter Estimation in Structural Equation Models
ISSN: 2149 - 1402
Publisher: author
A Classical and Bayesian Approach for Parameter Estimation in Structural Equation Models
Indexed in
Science General
ARTICLE-FACTOR
1.3
Article Basics Score: 3
Article Transparency Score: 2
Article Operation Score: 2
Article Articles Score: 2
Article Accessibility Score: 3
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International Category Code (ICC):
ICC-1402
Publisher: Journal Of New Theory Naim Çağman
International Journal Address (IAA):
IAA.ZONE/214974811402
eISSN
:
2149 - 1402
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Abstract
Structural Equation Models (SEMs) with latent variables provide a general framework for modelling relationships in multivariate data. Although SEMs are most commonly used in studies involving intrinsically latent variables, such as happiness, quality of life, or stress, they also provide a parsimonious framework for covariance structure modelling. For this reason, they have become increasingly used outside of traditional social science applications. Frequentist inferences are based on point estimates and hypothesis tests for the measurement and latent variable parameters. Although most of the literature on SEMs is frequentist, Bayesian approaches have been proposed in the last years. This study aims to provide an easily accessible overview of a Classic and a Bayesian approach to SEMs. Due to the flexibility of the Bayesian approach, it is straightforward to apply the method in a comprehensive class of SEM-type modelling frameworks, al...
