In many domains (marketing, social sciences, etc.) the variables of interest are often not directly observable. Complex causal relationships between such latent variables may be modeled by means of Structural Equation Models (SEM). Two different methodologies exist for the estimation of such models: SEM-ML (Maximum Likelihood Approach to Structural Equation Models), also known as LISREL (Linear...

conclusions path analysis of occupational injuries based on the sem reveals that individual and organizational factors and their indicator variables are very influential on the severity of traumatic occupational injuries. so, these should be considered to reduce occupational accidents’ severity in large construction industries. materials and methods the present cross-sectional analytical study ...

this study designed a structural model taking into account the views of staff on human resource management systems, human resources, job satisfaction and organizational loyalty pays yeast industry in iran. this study used structural equation modeling (sem). by using cluster sampling and cochran's formula, 288 patients were selected. the structural equation analysis and factor analysis were...

Concepts of health are often multivariate or multidimensional. Structural equation modelling (SEM) is a multivariate method that incorporates ideas from regression, path-analysis and factor analysis. A Bayesian approach to SEM may enable models that reflect hypotheses based on complex theory. The development and application of Bayesian approaches to SEM has, however, been relatively slow but wi...

In prior research we have shown how linear structural equation models and computer programs (e.g., LISREL) may be simply and directly used to provide alternatives for the traditional biometric twin design. We use structural equations and path models to define biometric group differences, we write traditional common-factor models in the same way, and then we take a detailed look at some alternat...