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 modelling (SEM) provides a holistic theoretical framework that assesses both the relationship between observed variables and a latent factor, and also relationships between ...

Structural equation modeling (SEM) is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with intercorrelated ...

Partial least squares structural equation modeling (PLS-SEM) has become a key method in international marketing research. Users of PLS-SEM have, however, largely overlooked the issue of endogeneity, ...

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 ...

A new research paper was published in Volume 12 of Oncoscience on July 31, 2025, titled “Burnout among oncology nurses and technicians in Morocco: Prevalence, risk factors, and structural equation ...

Nextatlas, the data-driven research platform, used social media data and structural equation models to find consumption drivers in CPG in the US.

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 ...