# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "logistf" in publications use:'
type: software
license: GPL-1.0-only
title: 'logistf: Firth''s Bias-Reduced Logistic Regression'
version: 1.26.0
doi: 10.32614/CRAN.package.logistf
abstract: Fit a logistic regression model using Firth's bias reduction method, equivalent
  to penalization of the log-likelihood by the Jeffreys prior. Confidence intervals
  for regression coefficients can be computed by penalized profile likelihood. Firth's
  method was proposed as ideal solution to the problem of separation in logistic regression,
  see Heinze and Schemper (2002) <https://doi.org/10.1002/sim.1047>. If needed, the
  bias reduction can be turned off such that ordinary maximum likelihood logistic
  regression is obtained. Two new modifications of Firth's method, FLIC and FLAC,
  lead to unbiased predictions and are now available in the package as well, see Puhr
  et al (2017) <https://doi.org/10.1002/sim.7273>.
authors:
- family-names: Heinze
  given-names: Georg
  email: georg.heinze@meduniwien.ac.at
- family-names: Ploner
  given-names: Meinhard
- family-names: Jiricka
  given-names: Lena
- family-names: Steiner
  given-names: Gregor
repository: https://staffanbetner.r-universe.dev
repository-code: https://github.com/georgheinze/logistf/issues/
commit: e2213b4764fd6a8d38bbacf46666040bd60ce9fe
url: https://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/firth-correction/
date-released: '2023-08-18'
contact:
- family-names: Heinze
  given-names: Georg
  email: georg.heinze@meduniwien.ac.at