Comparing Performances of Multiple Comparison Methods in Commonly Used 2 x C Contingency Tables

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dc.contributor.authorCangür, Şengül
dc.contributor.authorAnkaralı, Handan
dc.contributor.authorPasin, Özge
dc.date.accessioned2020-04-30T22:41:10Z
dc.date.available2020-04-30T22:41:10Z
dc.date.issued2016
dc.departmentDÜ, Tıp Fakültesi, Temel Tıp Bilimleri Bölümüen_US
dc.descriptionAnkarali, Handan Camdeviren/0000-0002-3613-0523en_US
dc.descriptionWOS: 000387850700002en_US
dc.descriptionPubMed: 26454649en_US
dc.description.abstractThis study aims at mentioning briefly multiple comparison methods such as Bonferroni, Holm-Bonferroni, Hochberg, Hommel, Marascuilo, Tukey, Benjamini-Hochberg and Gavrilov-Benjamini-Sarkar for contingency tables, through the data obtained from a medical research and examining their performances by simulation study which was constructed as the total 36 scenarios to 2 x 4 contingency table. As results of simulation, it was observed that when the sample size is more than 100, the methods which can preserve the nominal alpha level are Gavrilov-Benjamini-Sarkar, Holm-Bonferroni and Bonferroni. Marascuilo method was found to be a more conservative than Bonferroni. It was found that Type I error rate for Hommel method is around 2 % in all scenarios. Moreover, when the proportions of the three populations are equal and the proportion value of the fourth population is far at a level of +/- 3 standard deviation from the other populations, the power value for Unadjusted All-Pairwise Comparison approach is at least a bit higher than the ones obtained by Gavrilov-Benjamini-Sarkar, Holm-Bonferroni and Bonferroni. Consequently, Gavrilov-Benjamini-Sarkar and Holm-Bonferroni methods have the best performance according to simulation. Hommel and Marascuilo methods are not recommended to be used because they have medium or lower performance. In addition, we have written a Minitab macro about multiple comparisons for use in scientific research.en_US
dc.identifier.doi10.1007/s12539-015-0128-5en_US
dc.identifier.endpage345en_US
dc.identifier.issn1913-2751
dc.identifier.issn1867-1462
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage337en_US
dc.identifier.urihttps://doi.org/10.1007/s12539-015-0128-5
dc.identifier.urihttps://hdl.handle.net/20.500.12684/3137
dc.identifier.volume8en_US
dc.identifier.wosWOS:000387850700002en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakPubMeden_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofInterdisciplinary Sciences-Computational Life Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectContingency tableen_US
dc.subjectMultiple comparisonen_US
dc.subjectGavrilov-Benjamini-Sarkaren_US
dc.subjectHolm-Bonferronien_US
dc.subjectMarascuiloen_US
dc.subjectHommelen_US
dc.titleComparing Performances of Multiple Comparison Methods in Commonly Used 2 x C Contingency Tablesen_US
dc.typeArticleen_US

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