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| The accuracy and consistency of mastery for each content domain using the Rasch and deterministic inputs, noisy “and” gate diagnostic classification models: a simulation study and a real-world analysis using data from the Korean Medical Licensing Examination |
| Dong Gi Seo, Jae Kum Kim |
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J Educ Eval Health Prof. 2021;18:15 Published online July 5, 2021 DOI: https://doi.org/10.3352/jeehp.2021.18.15 |
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The accuracy and consistency of mastery for each content domain using the Rasch and deterministic inputs, noisy “and” gate diagnostic classification models: a simulation study and a real-world analysis using data from the Korean Medical Licensing Examination Journal of Educational Evaluation for Health Professions. 2021;18:15  Estimation of item parameters and examinees’ mastery probability in each domain of the Korean Medical Licensing Examination using a deterministic inputs, noisy “and” gate (DINA) model Journal of Educational Evaluation for Health Professions. 2020;17:35 Using the iterative latent-class analysis approach to improve attribute accuracy in diagnostic classification models Behavior Research Methods. 2019;51(3):1075-1084 Deterministic models for rumor transmission Nonlinear Analysis: Real World Applications. 2008;9(5):1989-2028 Measures of Agreement: Reliability, Classification Accuracy, and Classification Consistency Methodology of Educational Measurement and Assessment. 2019;359-377 Proceed with Caution When Using Real World Data and Real World Evidence Journal of Korean Medical Science. 2019;34(4): Analysis of First Clinical Skills Examination in the Korean Medical Licensing Examination: Focus on Examinees' Experience in a Medical School Korean Journal of Medical Education. 2011;23(3):203-207 A Simulation Study for the Identification of Missing Data Mechanisms Using Visualisation Studies in Classification, Data Analysis, and Knowledge Organization. 2021;205-213 Using Case-Study Simulation to Improve Critical Thinking and Content Mastery in Undergraduate Nursing Students Clinical Simulation in Nursing. 2010;6(3):e116 Improving classification accuracy of acoustic real-world urban data using sensors physical redundancy 2021 IEEE Symposium on Computers and Communications (ISCC). 2021; |
