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logistf

Overview

The package logistf provides a comprehensive tool to facilitate the application of Firth’s modified score procedure in logistic regression analysis.

Installation

# Install logistf from CRAN
install.packages("logistf")

# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("georgheinze/logistf")

Usage

The call of the main function of the library follows the structure of the standard functions as lm or glm, requiring a data.frame and a formula for the model specification. The resulting object belongs to the new class logistf, which includes penalized maximum likelihood ('Firth-Logistic'- or 'FL'-type) logistic regression parameters, standard errors, confidence limits, p-values, the value of the maximized penalized log likelihood, the linear predictors, the number of iterations needed to arrive at the maximum and much more. Furthermore, specific methods for the resulting object are supplied. The two modifications of FL: FLIC and FLAC have been implemented. A function to generate and plot profiles of the penalized likelihood function and a function to perform penalized likelihood ratio tests are available.

data(sex2)
lf <- logistf(formula = case ~ age + oc + vic + vicl + vis + dia, data = sex2)
summary(lf)

Acknowledgment

This work was supported by the Austrian Science Fund (FWF) (award I 2276).

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Install

install.packages('logistf')

Monthly Downloads

9,272

Version

1.26.1

License

GPL

Issues

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Stars

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Maintainer

Georg Heinze

Last Published

April 16th, 2025

Functions in logistf (1.26.1)

logistpl.control

Control Parameters for logistf Profile Likelihood Confidence Interval Estimation
profile.logistf

Compute Profile Penalized Likelihood
logistf

Firth's Bias-Reduced Logistic Regression
plot.logistf.profile

plot Method for logistf Likelihood Profiles
logistftest

Penalized likelihood ratio test
sex2

Urinary Tract Infection in American College Students
logistf.mod.control

Controls additional parameters for logistf
logistf.control

Control Parameters for logistf
predict.flic

Predict Method for flic Fits
predict.flac

Predict Method for flac Fits
sexagg

Urinary Tract Infection in American College Students
predict.logistf

Predict Method for logistf Fits
backward

Backward Elimination/Forward Selection of Model Terms in logistf Models
emmeans-logistf

Emmeans support for logistf
flac

FLAC - Firth's logistic regression with added covariate
flic

FLIC - Firth's logistic regression with intercept correction
add1.logistf

Add or Drop All Possible Single Terms to/from a logistf Model
CLIP.confint

Confidence Intervals after Multiple Imputation: Combination of Likelihood Profiles
logistf-package

Firth's Bias-Reduced Logistic Regression
PVR.confint

Pseudo Variance Modification of Rubin's Rule
anova.logistf

Analysis of Penalized Deviance for logistf Models
CLIP.profile

Combine Profile Likelihoods from Imputed-Data Model Fits