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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).
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Package details |
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| Author | Graeme L. Hickey [cre, aut] (<https://orcid.org/0000-0002-4989-0054>), Pete Philipson [aut] (<https://orcid.org/0000-0001-7846-0208>), Andrea Jorgensen [ctb] (<https://orcid.org/0000-0002-6977-9337>), Ruwanthi Kolamunnage-Dona [aut] (<https://orcid.org/0000-0003-3886-6208>), Paula Williamson [ctb] (<https://orcid.org/0000-0001-9802-6636>), Dimitris Rizopoulos [ctb, dtc] (data/renal.rda, R/hessian.R, R/vcov.R), Alessandro Gasparini [aut] (<https://orcid.org/0000-0002-8319-7624>), Medical Research Council [fnd] (Grant number: MR/M013227/1) |
| Maintainer | Graeme L. Hickey <graemeleehickey@gmail.com> |
| License | GPL-3 | file LICENSE |
| Version | 0.4.6 |
| URL | https://github.com/graemeleehickey/joineRML |
| Package repository | View on CRAN |
| Installation |
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