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joineRML  

Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes
View on CRAN: Click here


Download and install joineRML package within the R console
Install from CRAN:
install.packages("joineRML")

Install from Github:
library("remotes")
install_github("cran/joineRML")

Install by package version:
library("remotes")
install_version("joineRML", "0.4.7")



Attach the package and use:
library("joineRML")
Maintained by
Graeme L. Hickey
[Scholar Profile | Author Map]
First Published: 2016-12-27
Latest Update: 2023-01-20
Description:
Fits the joint model proposed by Henderson and colleagues (2000) , 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).
How to cite:
Graeme L. Hickey (2016). joineRML: Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes. R package version 0.4.7, https://cran.r-project.org/web/packages/joineRML. Accessed 19 Feb. 2025.
Previous versions and publish date:
0.1.0 (2016-12-27 13:36), 0.1.1 (2016-12-30 17:17), 0.2.0 (2017-03-27 16:04), 0.2.1 (2017-04-25 23:34), 0.2.2 (2017-05-01 16:42), 0.3.0 (2017-07-23 18:25), 0.4.0 (2017-11-12 01:33), 0.4.1 (2018-01-21 21:11), 0.4.2 (2018-05-29 01:00), 0.4.3 (2020-02-17 12:50), 0.4.4 (2020-04-09 11:30), 0.4.5 (2021-01-05 17:10), 0.4.6 (2023-01-20 05:50)
Other packages that cited joineRML R package
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Complete documentation for joineRML
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