Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the loglikelihood 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, Heinze, Nold, Lusa and Geroldinger (2017) <doi:10.1002/sim.7273>.
Package details 


Author  Georg Heinze [aut, cre], Meinhard Ploner [aut], Daniela Dunkler [ctb], Harry Southworth [ctb], Lena Jiricka [aut] 
Maintainer  Georg Heinze <georg.heinze@meduniwien.ac.at> 
License  GPL 
Version  1.24 
URL  https://cemsiis.meduniwien.ac.at/en/kb/scienceresearch/software/statisticalsoftware/fllogistf/ 
Package repository  View on CRAN 
Installation 
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