summary.logistf

object

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<p>Provides a summary method for <code>logistf</code>  objects.</p>

 regression

 models

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. If needed, the bias reduction can be turned off such that ordinary
maximum likelihood logistic regression is obtained.

Georg Heinze

logistf

Firth's Bias-Reduced Logistic Regression

Meinhard Ploner

Daniela Dunkler

Harry Southworth

summary.logistf function

<code>summary</code> Method for <code>logistf</code> Objects — summary.logistf

<code>summary</code> Method for <code>logistf</code> Objects

summary.logistf: `summary` Method for `logistf` Objects

Description

Usage

Arguments

Value

Examples