Modelling the distribution of health related quality of life of advancedmelanoma patients in a longitudinal multi-centre clinical trial using M-quantile random effects regression
Health-related quality of life assessment is important in the clinical
evaluation of patients with metastatic disease that may offer useful
information in understanding the clinical effectiveness of a treatment. To
assess if a set of explicative variables impacts on the health-related quality
of life, regression models are routinely adopted. However, the interest of
researchers may be focussed on modelling other parts (e.g. quantiles) of this
conditional distribution. In this paper, we present an approach based on
quantile and M-quantile regression to achieve this goal. We applied the
methodologies to a prospective, randomized, multi-centre clinical trial. In
order to take into account the hierarchical nature of the data we extended the
M-quantile regression model to a three-level random effects specification and
estimated it by maximum likelihood
