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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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Version

Install

install.packages('logistf')

Monthly Downloads

7,981

Version

1.26.0

License

GPL

Maintainer

Last Published

August 18th, 2023

Functions in logistf (1.26.0)

logistf.mod.control

Controls additional parameters for logistf
logistf.control

Control Parameters for logistf
profile.logistf

Compute Profile Penalized Likelihood
logistpl.control

Control Parameters for logistf Profile Likelihood Confidence Interval Estimation
predict.flac

Predict Method for flac Fits
plot.logistf.profile

plot Method for logistf Likelihood Profiles
predict.logistf

Predict Method for logistf Fits
logistf

Firth's Bias-Reduced Logistic Regression
logistftest

Penalized likelihood ratio test
sex2

Urinary Tract Infection in American College Students
predict.flic

Predict Method for flic Fits
sexagg

Urinary Tract Infection in American College Students
anova.logistf

Analysis of Penalized Deviance for logistf Models
logistf-package

Firth's Bias-Reduced Logistic Regression
flic

FLIC - Firth's logistic regression with intercept correction
emmeans-logistf

Emmeans support for logistf
backward

Backward Elimination/Forward Selection of Model Terms in logistf Models
flac

FLAC - Firth's logistic regression with added covariate
CLIP.confint

Confidence Intervals after Multiple Imputation: Combination of Likelihood Profiles
CLIP.profile

Combine Profile Likelihoods from Imputed-Data Model Fits
PVR.confint

Pseudo Variance Modification of Rubin's Rule
add1.logistf

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