Structural Equation Modeling (SEM): A multivariate analysis technique used to evaluate complex relationships among observed and latent variables. Latent Variables: ...

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 ...

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

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 ...

Information quality, encompassing relevance, clarity, accuracy, and timeliness, emerged as a foundational determinant. The ...

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., ...

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

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 ...

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 ...