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 was funded by the Medical Research Council (Grant number MR/M013227/1).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.4.7 |
2026-04-09 windows/windows R-4.5 | joineRML_0.4.7.zip |
2.5 MiB |