joineR: Joint modelling of repeated measurements and time-to-event data

Pete Philipson, Peter Diggle, Ines Sousa, Ruwanthi Kolamunnage-Dona, Paula Williamson, Robin Henderson

Research output: Other contribution

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Abstract

The joineR package implements methods for analysing data from longitudinal studies in which the response from each subject consists of a time-sequence of repeated measurements and a possibly censored time-toevent outcome. The modelling framework for the repeated measurements is the linear model with random effects and/or correlated error structure. The model for the time-to-event outcome is a Cox proportional hazards model with log-Gaussian frailty. Stochastic dependence is captured by allowing the Gaussian random effects of the linear model to be correlated with the frailty term of the Cox proportional hazards model.
Original languageEnglish
PublisherComprehensive R Archive Network
Place of PublicationUnited Kingdom
Publication statusPublished - 30 Mar 2012

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