Comparison of penalized logistic regression models for rare event case

DOI10.1080/03610918.2019.1676438OpenAlexW2980714219WikidataQ127093818 ScholiaQ127093818MaRDI QIDQ5082917

Ezgi Nazman, Semra Oral Erbas, Hülya Olmuş

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1676438

zbMATH Keywords

rare eventFLACFLICfirth LRpredicted probability bias

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• aplore3

Cites Work

• Unnamed Item
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• Applied Logistic Regression
• Inferences from logistic regression models in the presence of small samples, rare events, nonlinearity, and multicollinearity with observational data
• On the bias of various estimators of the logit and its variance with application to quantal bioassay

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