Home / Journals American Journal of Statistics and Probability / Structural Equation Modeling and It's Applications
Structural Equation Modeling and It's Applications
Submission Deadline: Jun. 30, 2017
Lead Guest Editor
Thanoon Y. Thanoon
Department of Business Management Techniques, Technical College of Management, Northern Technical University, Mosul, Iraq
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Introduction
Structural equation modeling is a statistical method which is used to study the relationships between the latent variables and the observed variables. There are two different types of parameter's estimation methods which can be use to estimate the parameters in structural equation models. The first method is classical methods which include weighted least square method (WLS) and maximum likelihood method (ML) and robust maximum likelihood (MLR). The second methods are Bayesian methods which include Gibbs sampling method and Metropolis- Hasting algorithm. Structural equation models are used in many applications such as social, behavior and medical sciences.

Aims and Scope:
Structural Equation Modeling
Conirmatory Factor Analysis
Exploratory Factor Analysis
Path Analysis
Bayesian Methods
Classical Methods
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