This software specialises in three areas: models with responses at several levels of a data hierarchy, multilevel structural equation models, and measurement error ...

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 ...

This course consists of two sections: Section 1 demonstrates linear regression to model the linear relationship between a response and predictor(s) when both the response and predictors are continuous ...

Bayesian methods in Structural Equation Modeling (SEM) represent a paradigm shift in statistical analysis, integrating prior beliefs with empirical data to derive robust parameter estimates. This ...

Latent factors are variables that cannot be observed directly but can be inferred from a set of observable variables. For example, in psychology, bad conduct (latent factor) can be measured by how ...