Modelling the distribution of health-related quality of life of advanced melanoma patients in a longitudinal multi-centre clinical trial using M-quantile random effects regression

Riccardo Borgoni, Paola Del Bianco, Nicola Salvati, Timo Schmid, Nikos Tzavidis

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)549-563
Number of pages14
JournalStatistical Methods in Medical Research
Volume27
Issue number2
DOIs
Publication statusE-pub ahead of print - Mar 17 2016

Keywords

  • Journal Article

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