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

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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.

Keywords: EM algorithm; competing risks; repeated measurements; score test; surrogate

Document Type: Research Article

Affiliations: Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Miaoli 350, Taiwan, Republic of China

Publication date: 03 October 2014

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