Bayesian Approach to the Nonlinear Structural Equation Model

Bayesci İstatistik

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Bayesian Approach, Gibbs Sampler, Structural Equation Model


Recent studies have found that adding nonlinear relationships of latent variables to the model is very useful for better causality. Nonlinear relationships allow the questioning of many hypotheses in the social and behavioral sciences, as well as providing solid theories in this field. Studies for nonlinear model types and their estimation techniques focus on the use of the Bayesian approach. However, this approach cannot be used through commonly used programs. For this reason, there is very little practical application in this field. The aim of this study is to popularize the use of the Bayesian approach for nonlinear models. In order to achieve this aim, three main headings have been established. In the first title, nonlinear model types and their estimation techniques are given. In the second title, the sources of motivation for the approach are mentioned together with the literature findings suggesting the reason for using the Bayesian approach. In the third title, there is how the Bayesian approach works with a principle.


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How to Cite

Yıldırım, M., & Kartal, M. (2023). Bayesian Approach to the Nonlinear Structural Equation Model: Bayesci İstatistik. Journal of Academic Opinion, 3(1), 16–26.