Package: pammtools
Title: Piece-Wise Exponential Additive Mixed Modeling Tools for
        Survival Analysis
Version: 0.8.0
Date: 2026-06-17
Authors@R: c(
    person("Andreas", "Bender", , "andreas.bender@stat.uni-muenchen.de", role = c("aut", "cre"), comment=c(ORCID = "0000-0001-5628-8611")),
    person("Fabian", "Scheipl", , "fabian.scheipl@stat.uni-muenchen.de", role = c("aut"), comment = c(ORCID = "0000-0001-8172-3603")),
    person("Johannes", "Piller", , "johannes.piller@lmu.de", role = c("aut"), comment = c(ORCID = "0009-0008-3010-9556")),
    person("Philipp", "Kopper", , "philipp.kopper@stat.uni-muenchen.de", role = c("aut"), comment = c(ORCID="0000-0002-5037-7135")),
    person("Lukas", "Burk", , "burk@leibniz-bips.de", role = c("ctb"), comment = c(ORCID="0000-0001-7528-3795")))
Description: 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.
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, etm, xgboost
Config/Needs/website: carData, coxme, eha, etm, scam, msm, mvna, rjags,
        brms, xgboost, TBFmultinomial
License: MIT + file LICENSE
LazyData: true
URL: https://adibender.github.io/pammtools/
BugReports: https://github.com/adibender/pammtools/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
Config/roxygen2/version: 8.0.0
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev
Repository: https://adibender.r-universe.dev
Date/Publication: 2026-07-03 11:12:05 UTC
RemoteUrl: https://github.com/adibender/pammtools
RemoteRef: HEAD
RemoteSha: 9a588a99a5ac67d5194927dda299b22b5f9e71c8
NeedsCompilation: no
Packaged: 2026-07-03 12:32:15 UTC; root
Author: Andreas Bender [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-5628-8611>),
  Fabian Scheipl [aut] (ORCID: <https://orcid.org/0000-0001-8172-3603>),
  Johannes Piller [aut] (ORCID: <https://orcid.org/0009-0008-3010-9556>),
  Philipp Kopper [aut] (ORCID: <https://orcid.org/0000-0002-5037-7135>),
  Lukas Burk [ctb] (ORCID: <https://orcid.org/0000-0001-7528-3795>)
Maintainer: Andreas Bender <andreas.bender@stat.uni-muenchen.de>