Presenter: Jean-Paul Fox, University of Twente
Bayesian covariance structure modeling (BCSM) is a new approach for modeling clustered data. In this multivariate modeling approach a dependence structure is directly modeled through a structured covariance matrix. The BCSM can be used to model measurement (in)variance, which shows to have many advantages over traditional methods. The (cluster) effects of group-specific item parameters (Verhagen and Fox, 2013) are described by modeling their dependencies on (clustered) item response observations through a structured covariance matrix. The covariance parameters of the structured covariance matrix can be tested with the Bayes factor to test for (uniform and/or non-uniform) measurement invariance.