logistf 1.23

Firth's Bias-Reduced Logistic Regression

Released Jul 19, 2018 by Georg Heinze

This package cannot yet be used with Renjin it depends on other packages which are not available: mice 3.4.0 An older version of this package is more compatible with Renjin.


mice 3.4.0 mgcv 1.8-27

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.