Performance of prior and weighting bias correction methods for rare event logistic regression under the influence of sampling bias

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dc.authoridAlpay, Olcay/0000-0003-1446-0801
dc.contributor.authorAlpay, Olcay
dc.contributor.authorCankaya, Emel
dc.date.accessioned2025-03-23T19:35:16Z
dc.date.available2025-03-23T19:35:16Z
dc.date.issued2023
dc.departmentSinop Üniversitesi
dc.description.abstractThe problem of classifying events to binary classes has been popularly addressed by Logistic Regression Analysis. However, there may be situations where the most interested class of event is rare such as an infectious disease, earthquake, financial crisis etc. The model of such events tends to focus on the majority class, resulting in the underestimation of probabilities for the rare class. Additionally, the model may incorporate sampling bias if the rare class of the sample is not representative of its population. It is therefore important to investigate whether such rareness is genuine or caused by an improperly drawn sample. We conducted a simulation study by creating three populations with different rarity levels and drawing samples from each of those which are either compatible or incompatible with the actual rare classes of the population. Then, the effect of sampling bias is discussed under the two correction methods of bias due to rareness as suggested by King and Zeng.
dc.identifier.doi10.1080/03610918.2021.1872629
dc.identifier.endpage1014
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85100040375
dc.identifier.scopusqualityQ2
dc.identifier.startpage993
dc.identifier.urihttps://doi.org/10.1080/03610918.2021.1872629
dc.identifier.urihttps://hdl.handle.net/11486/5827
dc.identifier.volume52
dc.identifier.wosWOS:000612456200001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Inc
dc.relation.ispartofCommunications in Statistics-Simulation and Computation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectLogistic regression
dc.subjectPrior bias correction
dc.subjectRare event
dc.subjectSampling bias
dc.subjectWeighting bias correction
dc.titlePerformance of prior and weighting bias correction methods for rare event logistic regression under the influence of sampling bias
dc.typeArticle

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