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logistf

Firth's Bias-Reduced Logistic Regression

v1.26.1 · Apr 16, 2025 · GPL

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>.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Reverse Dependencies (19)

depends

Dependency Network

Dependencies Reverse dependencies mice mgcv formula.tools Matrix mDAG AUtests BiVariAn Surrogate emcAdr iPRSue multisite.accuracy pogit EHR WeightIt clarify ggeffects insight jointest marginaleffects +4 more reverse deps logistf

Version History

new 1.26.1 Mar 10, 2026