Poisson and negative binomial regression models for zero-inflated data: an experimental study

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dc.authorid0000-0003-4582-9018en_US
dc.contributor.authorYıldırım, Gizem
dc.contributor.authorKaçıranlar, Selahattin
dc.contributor.authorYıldırım, Hasan
dc.date.accessioned2022-08-08T06:49:55Z
dc.date.available2022-08-08T06:49:55Z
dc.date.issued2022en_US
dc.departmentKMÜ, Kamil Özdağ Fen Fakültesi, Matematik Bölümüen_US
dc.descriptionWOS:000822397600012en_US
dc.description.abstractCount data regression has been widely used in various disciplines, particularly health area. Classical models like Poisson and negative binomial regression may not provide reasonable performance in the presence of excessive zeros and overdispersion problems. Zero-inflated and Hurdle variants of these models can be a remedy for dealing with these problems. As well as zero-inflated and Hurdle models, alternatives based on some biased estimators like ridge and Liu may improve the performance against to multicollinearity problem except excessive zeros and overdispersion. In this study, ten different regression models including classical Poisson and negative binomial regression with their variants based on zero-inflated, Hurdle, ridge and Liu approaches have been compared by using a health data. Some criteria including Akaike information criterion, log-likelihood value, mean squared error and mean absolute error have been used to investigate the performance of models. The results show that the zero-inflated negative binomial regression model provides the best fit for the data. The final model estimations have been obtained via this model and interpreted in detail. Finally, the experimental results suggested that models except the classical models should be considered as powerful alternatives for modelling count and give better insights to the researchers in applying statistics on working similar data structures.en_US
dc.identifier.citationYıldırım, G. , Kaçıranlar, S. & Yıldırım, H. (2022). Poisson and negative binomial regression models for zero-inflated data: an experimental study . Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics , 71 (2) , 601-615 . DOI: 10.31801/cfsuasmas.988880en_US
dc.identifier.doi10.31801/cfsuasmas.988880
dc.identifier.endpage615en_US
dc.identifier.issue2en_US
dc.identifier.startpage601en_US
dc.identifier.trdizinid1118383
dc.identifier.urihttps://doi.org/10.31801/cfsuasmas.988880
dc.identifier.urihttps://hdl.handle.net/11492/6493
dc.identifier.volume71en_US
dc.identifier.wosWOS:000822397600012
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorYıldırım, Hasan
dc.language.isoen
dc.publisherAnkara Üniversitesien_US
dc.relation.journalCommunications Faculty Of Sciences University Of Ankara-Series A1 Mathematics And Statisticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectPoisson Regressionen_US
dc.subjectNegative Binomial Regressionen_US
dc.subjectZero İnflated Regressionen_US
dc.subjectHurdle Regressionen_US
dc.subjectRidge Regressionen_US
dc.subjectLiu Regressionen_US
dc.titlePoisson and negative binomial regression models for zero-inflated data: an experimental studyen_US
dc.typeArticle

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