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 data as well as competing risks, recurrent events and multi-state settings. 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: | 0.7.4 |
| Depends: | R (≥ 4.1.0) |
| 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), scam |
| Suggests: | testthat, mstate, broom |
| Published: | 2026-02-16 |
| DOI: | 10.32614/CRAN.package.pammtools |
| Author: | Andreas Bender |
| 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 |
| Reference manual: | pammtools.html , pammtools.pdf |
| Package source: | pammtools_0.7.4.tar.gz |
| Windows binaries: | r-devel: pammtools_0.7.4.zip, r-release: pammtools_0.7.4.zip, r-oldrel: pammtools_0.7.4.zip |
| macOS binaries: | r-release (arm64): pammtools_0.7.4.tgz, r-oldrel (arm64): pammtools_0.7.4.tgz, r-release (x86_64): pammtools_0.7.4.tgz, r-oldrel (x86_64): pammtools_0.7.4.tgz |
| Old sources: | pammtools archive |
| Reverse imports: | autoReg, KMunicate, relsurv, robber |
| Reverse suggests: | adjustedCurves, contsurvplot, weightedsurv |
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