CRAN/E | joineRML

joineRML

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

Installation

About

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 was funded by the Medical Research Council (Grant number MR/M013227/1).

Citation joineRML citation info
github.com/graemeleehickey/joineRML
Bug report File report

Key Metrics

Version 0.4.6
R ≥ 3.6.0
Published 2023-01-20 433 days ago
Needs compilation? yes
License GPL-3
License File
CRAN checks joineRML results

Downloads

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Maintainer

Maintainer

Graeme L. Hickey

graemeleehickey@gmail.com

Authors

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)

Material

README
NEWS
Reference manual
Package source

In Views

Survival

Vignettes

joineRML and the broom package
joineRML
Technical details of joineRML

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

joineRML archive

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

Suggests

bindrcpp
dplyr
JM
joineR
knitr
rmarkdown
testthat

LinkingTo

Rcpp
RcppArmadillo

Reverse Suggests

BCClong
broom