CRAN
multistate 0.2
Fitting Multistate Models
Released Aug 3, 2017 by Yohann Foucher
Dependencies
relsurv 2.1-2 date 1.2-38 survival 2.42-3 statmod 1.4.30
Medical researchers are often interested in investigating the relationship between explicative variables and multiple times-to-event. Time-inhomogeneous Markov models consist of modelling the probabilities of transitions according to the chronological times (times since the baseline of the study). Semi-Markov (SM) models consist of modelling the probabilities of transitions according to the times spent in states. In this package, we propose functions implementing such 3-state and 4-state multivariable and multistate models. The user can introduce multiple covariates to estimate conditional (subject-specific) effects. We also propose to adjust for possible confounding factors by using the Inverse Probability Weighting (IPW). When a state is patient death, the user can consider to take into account the mortality of the general population (relative survival approach). Finally, in the particular situation of one initial transient state and two competing and absorbing states, this package allows for estimating mixture models.
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>multistate</artifactId>
<version>0.2-b18</version>
</dependency>
</dependencies>
<repositories>
<repository>
<id>bedatadriven</id>
<name>bedatadriven public repo</name>
<url>https://nexus.bedatadriven.com/content/groups/public/</url>
</repository>
</repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:multistate')
Test Results
This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.