Altındağ, İlkayGenç, Aşır2021-02-022021-02-022015Altindag, I., Genc, A. (2015). Bayesian Nonlinear Structural Equation Modeling. Journal of Selcuk University Natural and Applied Science, 4, (1), 174-192.2147-3781https://hdl.handle.net/20.500.12395/41219Structural Equation Modeling (SEM) is a multivariate method that incorporates ideas from regression, path analysis and factor analysis. SEM has been widely applied in examine inter-relationships among latent and observed variables in social, psychological, and medical research. Generally linear relationships between observed and latent variables are modeled in SEM. Also, modeling of nonlinear relationship in SEM have attracted great attention in the literature. A Bayesian approach to SEM may enable models that reflect hypotheses based on complex theory. The Bayesian approach analyses a general structural equation model that accommodates the general nonlinear terms of latent variables and covariates. In this study, we apply Bayesian SEM for Self-Esteem Scale.trinfo:eu-repo/semantics/openAccessStructural Equation ModelingBayesian ApproachLatent VariablesArticle41174192