CRAN

joineR 1.2.4

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

Released May 17, 2018 by Pete Philipson

This package can be loaded by Renjin but 6 out 19 tests failed.

Dependencies

MASS 7.3-50 lattice 0.20-35 nlme 3.1-137 survival 2.42-3 statmod 1.4.30

Analysis of repeated measurements and time-to-event data via random effects joint models. Fits the joint models proposed by Henderson and colleagues (single event time) and by Williamson and colleagues (2008) (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).

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>joineR</artifactId>
    <version>1.2.4-b2</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

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Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:joineR')

Test Results

This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.

Source

R

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Release History