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

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).

Version: 0.1.0
Depends: R (≥ 3.1)
Imports: graphics, MASS, Matrix, nlme, Rcpp (≥ 0.12.7), stats, survival, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: joineR, knitr, rmarkdown, R.rsp
Published: 2016-12-27
Author: Graeme L. Hickey [cre, aut], Pete Philipson [aut], Andrea Jorgensen [aut], Ruwanthi Kolamunnage-Dona [aut], Paula Williamson [ctb]
Maintainer: Graeme L. Hickey <graeme.hickey at>
License: GPL-2 | file LICENSE
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: joineRML results


Reference manual: joineRML.pdf
Vignettes: joineRML
Technical details of joineRML
Package source: joineRML_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
OS X Mavericks binaries: r-release: joineRML_0.1.0.tgz, r-oldrel: not available


Please use the canonical form to link to this page.