pammtools: Piece-Wise Exponential Additive Mixed Modeling Tools for Survival Analysis

The Piece-wise exponential (Additive Mixed) Model (PAMM; Bender and others (2018) <doi:10.1177/1471082X17748083>) is a powerful model class for the analysis of survival (or time-to-event) data, based on Generalized Additive (Mixed) Models (GA(M)Ms). It offers intuitive specification and robust estimation of complex survival models with stratified baseline hazards, random effects, time-varying effects, time-dependent covariates and cumulative effects (Bender and others (2019)), as well as support for left-truncated, competing risks and recurrent events data. pammtools provides tidy workflow for survival analysis with PAMMs, including data simulation, transformation and other functions for data preprocessing and model post-processing as well as visualization.

Version: 0.5.8
Depends: R (≥ 3.5.0)
Imports: mgcv, survival (≥ 2.39-5), checkmate, magrittr, rlang, tidyr (≥ 1.0.0), ggplot2 (≥ 3.2.2), dplyr (≥ 1.0.0), purrr (≥ 0.2.3), tibble, lazyeval, Formula, mvtnorm, pec, vctrs (≥ 0.3.0)
Suggests: testthat
Published: 2022-01-09
Author: Andreas Bender ORCID iD [aut, cre], Fabian Scheipl ORCID iD [aut], Philipp Kopper ORCID iD [aut], Lukas Burk ORCID iD [ctb]
Maintainer: Andreas Bender <andreas.bender at stat.uni-muenchen.de>
BugReports: https://github.com/adibender/pammtools/issues
License: MIT + file LICENSE
URL: https://adibender.github.io/pammtools/
NeedsCompilation: no
Citation: pammtools citation info
Materials: README NEWS
CRAN checks: pammtools results

Documentation:

Reference manual: pammtools.pdf

Downloads:

Package source: pammtools_0.5.8.tar.gz
Windows binaries: r-devel: pammtools_0.5.8.zip, r-release: pammtools_0.5.8.zip, r-oldrel: pammtools_0.5.8.zip
macOS binaries: r-release (arm64): pammtools_0.5.8.tgz, r-oldrel (arm64): pammtools_0.5.8.tgz, r-release (x86_64): pammtools_0.5.8.tgz, r-oldrel (x86_64): pammtools_0.5.8.tgz
Old sources: pammtools archive

Reverse dependencies:

Reverse imports: autoReg, KMunicate, relsurv, robber
Reverse suggests: contsurvplot

Linking:

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