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:	0.4.4
Depends:	R (≥ 3.6.0), nlme, survival
Imports:	cobs, doParallel, foreach, generics, ggplot2, graphics, lme4 (≥ 1.1-8), MASS, Matrix, mvtnorm, parallel, randtoolbox, Rcpp (≥ 0.12.7), stats, tibble, utils
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	bindrcpp, dplyr, JM, joineR, knitr, rmarkdown, testthat
Published:	2020-04-09
Author:	Graeme L. Hickey [cre, aut], Pete Philipson [aut], Andrea Jorgensen [ctb], Ruwanthi Kolamunnage-Dona [aut], Paula Williamson [ctb], Dimitris Rizopoulos [ctb, dtc] (data/renal.rda, R/hessian.R, R/vcov.R), Alessandro Gasparini [aut], Medical Research Council [fnd] (Grant number: MR/M013227/1)
Maintainer:	Graeme L. Hickey <graemeleehickey at gmail.com>
BugReports:	https://github.com/graemeleehickey/joineRML/issues
License:	GPL-3 | file LICENSE
URL:	https://github.com/petephilipson/joineRML
NeedsCompilation:	yes
Materials:	README NEWS
CRAN checks:	joineRML results

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