A Review on Joint Models in Biometrical Research

In some fields of biometrical research joint modelling of
longitudinal measures and event time data has become very popular.
This article reviews the work in that area of recent fruitful
research by classifying approaches on joint models in three
categories: approaches with focus on serial trends, approaches with
focus on event time data and approaches with equal focus on both
outcomes. Typically longitudinal measures and event time data are
modelled jointly by introducing shared random effects or by
considering conditional distributions together with marginal
distributions. We present the approaches in an uniform
nomenclature, comment on sub-models applied to longitudinal
measures and event time data outcomes individually and exemplify
applications in biometrical research.