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

Graeme Hickey, Pete Philipson, Andrea Jorgensen, Ruwanthi Kolamunnage-Dona

Research output: Other contribution

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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).
Original languageEnglish
PublisherCRAN R project
Place of PublicationCRAN repository for R software packages
Publication statusPublished - 27 Dec 2016

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