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 ...

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 ...

Although the methodology for handling ordinal and dichotomous observed variables in structural equation models (SEMs) is developing rapidly, several important issues are unresolved. One of these is ...

Meta-Analytic Structural Equation Modeling (MASEM) represents a powerful and integrative statistical framework that combines the rigour of meta-analysis with the complexity of structural equation ...

Abstract: A structural regression model has been developed to explore the relationship among key factors in the explanation of utilitarian walking. The model examines the relationship between and ...

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 ...