Identification of longitudinal biomarkers for survival by a score test derived from a joint model of longitudinal and competing risks data

Feng-Shou Ko

Journal of Applied Statistics, 2014, vol. 41, issue 10, 2270-2281

Abstract: In this paper, we consider joint modelling of repeated measurements and competing risks failure time data. For competing risks time data, a semiparametric mixture model in which proportional hazards model are specified for failure time models conditional on cause and a multinomial model for the marginal distribution of cause conditional on covariates. We also derive a score test based on joint modelling of repeated measurements and competing risks failure time data to identify longitudinal biomarkers or surrogates for a time to event outcome in competing risks data.

Date: 2014
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DOI: 10.1080/02664763.2014.909789

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