Bayesian Quantile Bent-Cable Growth Models for Longitudinal Data with Skewness and Detection Limit

Abstract

This paper presents a Bayesian quantile bent-cable growth model for modeling data with multi-phasic trajectories of response variables measured in longitudinal studies. Estimating and identifying such possible multiple phasic change points may be of substantial interest since it provides a general life-course view of the developmental trajectories and also when the directions of the trajectories are disrupted. For getting a complete picture of such developmental trajectories, quantile growth models, at different parts (quantiles) of the response variables, are better than the commonly used conditional mean models. For each quantile, we develop bent-cable models to assess multi-phasic patterns of trajectories of longitudinal HIV/AIDS data with left-censoring and skewness. The proposed procedures are illustrated using real data from an AIDS clinical study.