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joineR

Joint Modelling of Repeated Measurements and Time-to-Event Data

Analysis of repeated measurements and time-to-event data via random effects joint models. Fits the joint models proposed by Henderson and colleagues <doi:10.1093/biostatistics/1.4.465> (single event time) and by Williamson and colleagues (2008) <doi:10.1002/sim.3451> (competing risks events time) to a single continuous repeated measure. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-varying covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by a latent Gaussian process. The model is estimated using am Expectation Maximization algorithm. Some plotting functions and the variogram are also included. This project is funded by the Medical Research Council (Grant numbers G0400615 and MR/M013227/1).

Functions (25)

UniqueVariables

Extracts the unique non-time dependent variables per patient, from an unbalanced data set

aids

AIDS drug trial data

epileptic

Dose calibration of anti-epileptic drugs data

heart.valve

Aortic valve replacement surgery data

joineR

joineR

joint

Fit joint model for survival and longitudinal data measured with error

joint.object

Fitted joint object

jointSE

Standard errors via bootstrap for a joint model fit

jointdata

Creates an object of class jointdata

jointplot

Joint plot of longitudinal and survival data

lines.jointdata

Add lines to an existing jointdata plot

liver

Liver cirrhosis drug trial data

mental

Mental health trial data

plot.jointdata

Plot longitudinal data

plot.vargm

Plots the empirical variogram for longitudinal data

points.jointdata

Add points to an existing jointdata plot

sample.jointdata

Sample from a jointdata x

simjoint

Simulate data from a joint model

subset.jointdata

Subsetting object of class jointdata

summary.joint

Summarise a random effects joint model fit

summary.jointdata

Summarise a jointdata object

summarybal

Summary of a balanced longitudinal data set

to.balanced

Transform data to the longitudinal balanced format

to.unbalanced

Transform data to the longitudinal unbalanced format

variogram

Empirical variogram for longitudinal data

joineR

Joint Modelling of Repeated Measurements and Time-to-Event Data

v1.2.5

GPL-3 | file LICENSE

Authors

Pete Philipson [aut, cre] (<https://orcid.org/0000-0001-7846-0208>), Ines Sousa [aut] (<https://orcid.org/0000-0002-2712-1713>), Peter J. Diggle [aut] (<https://orcid.org/0000-0003-3521-5020>), Paula Williamson [aut] (<https://orcid.org/0000-0001-9802-6636>), Ruwanthi Kolamunnage-Dona [aut] (<https://orcid.org/0000-0003-3886-6208>), Robin Henderson [aut], Graeme L. Hickey [aut] (<https://orcid.org/0000-0002-4989-0054>), Maria Sudell [ctb], Medical Research Council [fnd] (Grant numbers: G0400615 and MR/M013227/1)

Initial release

joineR

Functions (25)

joineR

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