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Technical Report
Calibrating the Medical Council of Canada’s Qualifying Examination Part I using an integrated item response theory framework: a comparison of models and designs  
Andre F. De Champlain, Andre-Philippe Boulais, Andrew Dallas
J Educ Eval Health Prof. 2016;13:6.   Published online January 20, 2016
DOI: https://doi.org/10.3352/jeehp.2016.13.6
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AbstractAbstract PDF
Purpose
The aim of this research was to compare different methods of calibrating multiple choice question (MCQ) and clinical decision making (CDM) components for the Medical Council of Canada’s Qualifying Examination Part I (MCCQEI) based on item response theory.
Methods
Our data consisted of test results from 8,213 first time applicants to MCCQEI in spring and fall 2010 and 2011 test administrations. The data set contained several thousand multiple choice items and several hundred CDM cases. Four dichotomous calibrations were run using BILOG-MG 3.0. All 3 mixed item format (dichotomous MCQ responses and polytomous CDM case scores) calibrations were conducted using PARSCALE 4.
Results
The 2-PL model had identical numbers of items with chi-square values at or below a Type I error rate of 0.01 (83/3,499 or 0.02). In all 3 polytomous models, whether the MCQs were either anchored or concurrently run with the CDM cases, results suggest very poor fit. All IRT abilities estimated from dichotomous calibration designs correlated very highly with each other. IRT-based pass-fail rates were extremely similar, not only across calibration designs and methods, but also with regard to the actual reported decision to candidates. The largest difference noted in pass rates was 4.78%, which occurred between the mixed format concurrent 2-PL graded response model (pass rate= 80.43%) and the dichotomous anchored 1-PL calibrations (pass rate= 85.21%).
Conclusion
Simpler calibration designs with dichotomized items should be implemented. The dichotomous calibrations provided better fit of the item response matrix than more complex, polytomous calibrations.

Citations

Citations to this article as recorded by  
  • Plus ça change, plus c’est pareil: Making a continued case for the use of MCQs in medical education
    Debra Pugh, André De Champlain, Claire Touchie
    Medical Teacher.2019; 41(5): 569.     CrossRef
  • Identifying the Essential Portions of the Skill Acquisition Process Using Item Response Theory
    Saseem Poudel, Yusuke Watanabe, Yo Kurashima, Yoichi M. Ito, Yoshihiro Murakami, Kimitaka Tanaka, Hiroshi Kawase, Toshiaki Shichinohe, Satoshi Hirano
    Journal of Surgical Education.2019; 76(4): 1101.     CrossRef
  • FUZZY CLASSIFICATION OF DICHOTOMOUS TEST ITEMS AND SOCIAL INDICATORS DIFFERENTIATION PROPERTY
    Aleksandras Krylovas, Natalja Kosareva, Julija Karaliūnaitė
    Technological and Economic Development of Economy.2018; 24(4): 1755.     CrossRef
  • Analysis of the suitability of the Korean Federation of Science and Technology Societies journal evaluation tool
    Geum‐Hee Jeong, Sun Huh
    Learned Publishing.2016; 29(3): 193.     CrossRef

JEEHP : Journal of Educational Evaluation for Health Professions