The issues of model-based clustering and classification of longitudinal data have received increasing attention in recent years. In this paper, we propose a finite mixture of multivariate t linear ...

This article presents new computational techniques for multivariate longitudinal or clustered data with missing values. Current methodology for linear mixed-effects models can accommodate imbalance or ...

Multivariate linear mixed models (mvLMMs) are powerful tools for testing associations between single-nucleotide polymorphisms and multiple correlated phenotypes while controlling for population ...