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: 0.2.0
Depends: R (≥ 3.1.1), nlme, survival
Imports: ggplot2, graphics, lme4 (≥ 1.1-8), MASS, Matrix, Rcpp (≥ 0.12.7), stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: JM, joineR, knitr, rmarkdown, R.rsp, testthat
Published: 2017-03-27
Author: Graeme L. Hickey [cre, aut], Pete Philipson [aut], Andrea Jorgensen [aut], Ruwanthi Kolamunnage-Dona [aut], Paula Williamson [ctb], Dimitris Rizopoulos [ctb, dtc] (data/renal.rda, R/hessian.R, R/vcov.R)
Maintainer: Graeme L. Hickey <graeme.hickey at liverpool.ac.uk>
BugReports: https://github.com/graemeleehickey/joineRML/issues
License: GPL-3 | file LICENSE
URL: https://github.com/graemeleehickey/joineRML/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: joineRML results

Downloads:

Reference manual: joineRML.pdf
Vignettes: joineRML
Technical details of joineRML
Package source: joineRML_0.2.0.tar.gz
Windows binaries: r-devel: joineRML_0.2.0.zip, r-release: joineRML_0.2.0.zip, r-oldrel: joineRML_0.2.0.zip
OS X El Capitan binaries: r-release: joineRML_0.2.0.tgz
OS X Mavericks binaries: r-oldrel: joineRML_0.2.0.tgz
Old sources: joineRML archive

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