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 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 ...

R is a powerful open source programming environment primarily known for its statistical capabilities. In this course we will cover some advanced applications of R: distributed computing using the ...

introduction to basic concepts, principles, and applications of structural equation modeling including path analysis, confirmatory latent variable models, multiple-group modeling, and latent growth ...

Statistical model infrastructures at financial institutions are often developed using a piecemeal approach to model building, in which different components of complex interrelated statistical models ...

This is a preview. Log in through your library . Abstract Appropriate enablers are essential for management of intellectual capital. Through the use of structural equation modeling, we investigate ...