Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes

Hickey, Graeme, Philipson, Pete, Jorgensen, Andrea and Kolamunnage-Dona, Ruwanthi (2016) Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes. CRAN R project, CRAN repository for R software packages.

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Abstract

Fits the joint model proposed by Henderson and colleagues (2000) (doi:10.1093/biostatistics/1.4.465), but extended to the case of multiple continuous longitudinal measures. The time-to-event data is modelled using a Cox proportional hazards regression model with time-varying covariates. The multiple longitudinal outcomes are modelled using a multivariate version of the Laird and Ware linear mixed model. The association is captured by a multivariate latent Gaussian process. The model is estimated using a Monte Carlo Expectation Maximization algorithm. This project is funded by the Medical Research Council (Grant number MR/M013227/1).

Item Type: Other
Subjects: A300 Clinical Medicine
G300 Statistics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Pete Philipson
Date Deposited: 10 Oct 2017 13:49
Last Modified: 18 May 2018 10:55
URI: http://nrl.northumbria.ac.uk/id/eprint/32308

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