Penalized logistic regression for small or sparse data: interval estimators revisited

Risultato della ricerca: Otherpeer review

Abstract

This paper focuses on interval estimation in logistic regression modelsfitted through the Firth penalized log-likelihood. In this context, many authorshave claimed superiority of the Likelihood ratio statistic with respect to the(wrong) Wald statistic via simulation evidence. We re-assess such findings bydetailing the inferential tools also including in the comparisons the (right) Waldstatistic and other statistics neglected in previous literature. In particular, weassess performances of the CIs estimators by simulation and compare them in areal data set. Differently from previous findings, the Likelihood ratio statistic doesnot appear to be the best inferential device in Firth penalized logistic regression.
Lingua originaleEnglish
Numero di pagine4
Stato di pubblicazionePublished - 2015

Fingerprint

Entra nei temi di ricerca di 'Penalized logistic regression for small or sparse data: interval estimators revisited'. Insieme formano una fingerprint unica.

Cita questo