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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "rstpm2" in publications use:'
type: software
license:
- GPL-2.0-only
- GPL-3.0-only
title: 'rstpm2: Smooth Survival Models, Including Generalized Survival Models'
version: 1.6.5
identifiers:
- type: doi
  value: 10.32614/CRAN.package.rstpm2
abstract: R implementation of generalized survival models (GSMs), smooth accelerated
  failure time (AFT) models and Markov multi-state models. For the GSMs, g(S(t|x))=eta(t,x)
  for a link function g, survival S at time t with covariates x and a linear predictor
  eta(t,x). The main assumption is that the time effect(s) are smooth <https://doi.org/10.1177/0962280216664760>.
  For fully parametric models with natural splines, this re-implements Stata's 'stpm2'
  function, which are flexible parametric survival models developed by Royston and
  colleagues. We have extended the parametric models to include any smooth parametric
  smoothers for time. We have also extended the model to include any smooth penalized
  smoothers from the 'mgcv' package, using penalized likelihood. These models include
  left truncation, right censoring, interval censoring, gamma frailties and normal
  random effects <https://doi.org/10.1002/sim.7451>, and copulas. For the smooth AFTs,
  S(t|x) = S_0(t*eta(t,x)), where the baseline survival function S_0(t)=exp(-exp(eta_0(t)))
  is modelled for natural splines for eta_0, and the time-dependent cumulative acceleration
  factor eta(t,x)=\int_0^t exp(eta_1(u,x)) du for log acceleration factor eta_1(u,x).
  The Markov multi-state models allow for a range of models with smooth transitions
  to predict transition probabilities, length of stay, utilities and costs, with differences,
  ratios and standardisation.
authors:
- family-names: Clements
  given-names: Mark
  email: mark.clements@ki.se
- family-names: Liu
  given-names: Xing-Rong
  email: xingrong.liu@ki.se
- family-names: Christoffersen
  given-names: Benjamin
  email: benjamin.christoffersen@ki.se
preferred-citation:
  type: article
  title: Parametric and penalized generalized survival models
  authors:
  - name: X.-R. Liu
  - name: Y. Pawitan
  - name: M. Clements
  year: '2018'
  volume: '27'
  issue: '5'
  journal: Statistical Methods in Medical Research
  start: 1531-1546
repository: https://CRAN.R-project.org/package=rstpm2
repository-code: https://github.com/mclements/rstpm2
url: https://github.com/mclements/rstpm2
date-released: '2024-08-20'
contact:
- family-names: Clements
  given-names: Mark
  email: mark.clements@ki.se
references:
- type: article
  title: Generalized survival models for correlated time-to-event data
  authors:
  - name: X.-R. Liu
  - name: Y. Pawitan
  - name: M. S. Clements
  year: '2017'
  volume: '39'
  issue: '29'
  journal: Statistics in Medicine
  start: 4743-4762
- type: article
  title: Generalized parametric cure models for relative survival
  authors:
  - name: L. H. Jakobsen
  - name: M. Bøgsted
  - name: M. Clements
  year: '2020'
  journal: Biometrical Journal
- type: thesis
  title: Generalized survival models applied to interval censored data
  authors:
  - name: A. N. Printz
  year: '2018'
  institution:
    name: Stockholm University
  url: https://kurser.math.su.se/pluginfile.php/20130/mod_folder/content/0/Kandidat/2018/2018_10_report.pdf
  thesis-type: Master's Thesis
- type: article
  title: 'Leukocyte telomere length and all-cause mortality: A between-within twin
    study with time-dependent effects using generalized survival models'
  authors:
  - name: Y. Zhan
  - name: X.-R. Liu
  - name: C. A. Reynolds
  - name: N. L. Pedersen
  - name: S. Hägg
  - name: M. S. Clements
  year: '2018'
  journal: American Journal of Epidemiology
  volume: '187'
  issue: '10'
  start: 2186-2191