Robust Logistic and Probit Methods for Binary and Multinomial Regression

In this paper we introduce new robust estimators for the logistic and probit regressions for binary, multinomial, nominal and ordinal data and apply these models to estimate the parameters when outliers or inluential observations are present. Maximum likelihood estimates don't behave well when...

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Bibliographic Details
Published in:	J Biom Biostat
Main Authors:	Tabatabai, MA, Li, H, Eby, WM, Kengwoung-Keumo, JJ, Manne, U, Bae, S, Fouad, M, Singh, KP
Format:	Artigo
Language:	Inglês
Published:	2014
Subjects:	Article
Online Access:	https://ncbi.nlm.nih.gov/pmc/articles/PMC4464778/ https://ncbi.nlm.nih.gov/pubmed/26078914 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4172/2155-6180.1000202
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Robust Logistic and Probit Methods for Binary and Multinomial Regression

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