Structural equation models are a powerful generalization of earlier statistical approaches, such as path analysis, and a widely used tool for causal inference.

Regulators need a method that is versatile, is easy to use and can handle complex path models with latent (not directly observable) variables. In a first application of partial least squares ...

Niyazi Ekici, Huseyin Akdogan, Structural Equation Modeling of Terrorism Perception, Perspectives on Terrorism, Vol. 14, No. 5 (October 2020), pp. 63-76 ...

EQS STRUCTURAL . Developed by one of the world's leading authorities on the subject, Dr. Peter M. Bentler, EQS provides researchers and statisticians with a simple method for conducting the full range ...

Course TopicsStructural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis ...

We propose an empirical framework, spurred by recent developments in the implementation of generalized structural equation modeling (GSEM), which brings to bear a modular and all-inclusive approach to ...

The impact of residential neighborhood type on travel behavior: A structural equations modeling approach. Annals of Regional Science, (362):279–297. doi: 10.1007/s001680200083. Bamberg, S., ...

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...

Using structural equation modeling (SEM), we aimed to assess the direct and indirect impact of geriatric impairments and oncological parameters on mortality in older patients with cancer. Methods: ...