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JointFPM: A Parametric Model for Estimating the Mean Number of Events

Implementation of a parametric joint model for modelling recurrent and competing event processes using generalised survival models. The joint model can subsequently be used to predict the mean number of events in the presence of competing risks at different time points. Comparisons of the mean number of event functions, e.g. the differences in mean number of events between two exposure groups, are also available.

Version: 1.2.1
Depends: R (≥ 4.0)
Imports: rstpm2 (≥ 1.5.2), survival (≥ 3.2-13), data.table (≥ 1.14.2), rlang (≥ 1.1.0), lifecycle, rmutil, cli, matrixStats, statmod
Suggests: testthat (≥ 3.0.0)
Published: 2024-06-19
DOI: 10.32614/CRAN.package.JointFPM
Author: Joshua P. Entrop ORCID iD [aut, cre, cph], Alessandro Gasparini [ctb], Mark Clements [ctb]
Maintainer: Joshua P. Entrop <joshuaentrop at posteo.de>
BugReports: https://github.com/entjos/JointFPM/issues
License: CC BY 4.0
URL: https://github.com/entjos/JointFPM, https://entjos.github.io/JointFPM/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: JointFPM results

Documentation:

Reference manual: JointFPM.pdf

Downloads:

Package source: JointFPM_1.2.1.tar.gz
Windows binaries: r-devel: JointFPM_1.2.1.zip, r-release: JointFPM_1.2.1.zip, r-oldrel: JointFPM_1.2.1.zip
macOS binaries: r-release (arm64): JointFPM_1.2.1.tgz, r-oldrel (arm64): JointFPM_1.2.1.tgz, r-release (x86_64): JointFPM_1.2.1.tgz, r-oldrel (x86_64): JointFPM_1.2.1.tgz
Old sources: JointFPM archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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