Bayesian growth curve model useful for high-dimensional longitudinal data

Traditional inference on the growth curve model (GCM) requires ‘small p large n’ () and cannot be applied in high-dimensional scenarios, where we often encounter singularity. Several methods are proposed to tackle the singularity problem, however there are still limitations and gaps. We consider a Bayesian framework to derive a statistic for testing a linear hypothesis on the GCM. Extensive simulations are performed to investigate performance …