Package: logistf
Version: 1.26.1
Date: 2025-04-16
Title: Firth's Bias-Reduced Logistic Regression
Authors@R: c(person("Georg", "Heinze", role=c("aut", "cre"), email="georg.heinze@meduniwien.ac.at"),
			 person("Meinhard", "Ploner", role=c("aut")),
			 person("Daniela","Dunkler", role=c("ctb")),
			 person("Harry", "Southworth", role=c("ctb")), 
			 person("Lena", "Jiricka", role=c("aut")),
			 person("Gregor", "Steiner", role=c("aut")))
Depends: R (>= 3.0.0)
Imports: mice, mgcv, formula.tools, Matrix
Suggests: emmeans (>= 1.4), estimability
Description: 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) <doi: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) <doi:10.1002/sim.7273>.
License: GPL
URL: https://github.com/georgheinze/logistf
LazyLoad: yes
NeedsCompilation: yes
RoxygenNote: 7.3.2
LazyData: true
BugReports: https://github.com/georgheinze/logistf/issues/
Packaged: 2025-04-16 15:04:23 UTC; Georg
Author: Georg Heinze [aut, cre],
  Meinhard Ploner [aut],
  Daniela Dunkler [ctb],
  Harry Southworth [ctb],
  Lena Jiricka [aut],
  Gregor Steiner [aut]
Maintainer: Georg Heinze <georg.heinze@meduniwien.ac.at>
Repository: CRAN
Date/Publication: 2025-04-16 15:50:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-30 18:45:58 UTC; unix
Archs: logistf.so.dSYM
