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  • Eğitimde ve Psikolojide Ölçme Değerlendirme Dergisi
  • Volume:13 Issue:1
  • Gender-based Differential Item Functioning Analysis of the Medical Specialization Education Entrance...

Gender-based Differential Item Functioning Analysis of the Medical Specialization Education Entrance Examination

Authors : Dilara BAKAN KALAYCIOĞLU
Pages : 1-14
Doi:10.21031/epod.998592
View : 71 | Download : 15
Publication Date : 2022-03-29
Article Type : Research Paper
Abstract :The Medical Specialization Education Entrance Examination is a national high-stake test for the placement of medical graduates in medical specialization training in Turkey. The purpose of this study is to determine whether the Medical Specialization Education Entrance Examination items display gender-related differential item functioning (DIF) by using Mantel-Haenszel and logistic regression methods. To determine the presence of item bias, content experts reviewed items. The analyzes were conducted on the answers of 11,530 physicians to the Basic Medical Sciences and Clinical Medical Sciences tests of the 2017 Medical Specialization Education Entrance Examination spring term. According to the Mantel-Haenszel method, there were eleven out of 234 items identified as showing B level gender-related DIF. While six of the items functioned in favor of male physicians, five of them were in favor of female physicians. Since the number of items in favor of each gender is close, DIF cancellation occurs. According to content areas, one histology and embryology, one internal medicine, and three gynecology and obstetrics items were in favor of female physicians, one physiology, two medical pharmacology, one pediatrics, and two surgical items were in favor of male physicians. To the experts’ reviews, there are no biased items. The medical specialty preferences of the physicians and content area of the displaying differential item functioning items overlapped.
Keywords : medical specialization education entrance examination, residency, differential item functioning, logistic regression, Mantel Haenszel

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