doi:10.1002/bimj.70038>. 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.">

JointFPM: A Parametric Model for Estimating the Mean Number of Events (original) (raw)

Implementation of a parametric joint model for modelling recurrent and competing event processes using generalised survival models as described in Entrop et al., (2005) <doi:10.1002/bimj.70038>. 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: 1.2.2
Depends: R (≥ 4.1.0)
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: 2025-02-20
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
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
Citation: JointFPM citation info
Materials: README NEWS
CRAN checks: JointFPM results

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