The relationship between variables in structural equation modeling (SEM) forms a model. This model can be explained through equations, such as regression analysis. describes the prediction of latent (exogenous) independent variable on (endogenous) dependent variable. Researchers who use analysis with models need to know whether built empirical data has unique value or not so that estimated. If ...

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 with modern technology and the Gibbs sampler, is now possible. Th...

Cost performance is the basic criteria for measuring success of any project. Since construction projects are highly dependable on resources, construction cost is significantly affected by various resource related factors. Compared to traditional methods of data analysis, Structural Equation Model (SEM) is the graphical equivalent of a mathematical representation to study relationship between de...

Multigroup structural equation modelling (SEM) is a technique frequently used to evaluate measurement invariance in social and behavioural science research. Before version 9.2, SAS was incapable of handling multigroup SEM. However, this limitation is resolved in PROC TCALIS in SAS 9.2. For the purpose of illustration, this paper provides a step-by-step guide to programming the tests of measurem...