CrossRef Text and Data Mining
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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
J Educ Eval Health Prof. 2021;18:15  Published online July 5, 2021

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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   Crossref logo
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Using the iterative latent-class analysis approach to improve attribute accuracy in diagnostic classification models
Behavior Research Methods. 2019;51(3):1075-1084   Crossref logo
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Consistency ofℓ1recovery from noisy deterministic measurements
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Deterministic models for rumor transmission
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Measures of Agreement: Reliability, Classification Accuracy, and Classification Consistency
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Proceed with Caution When Using Real World Data and Real World Evidence
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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   Crossref logo
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A Simulation Study for the Identification of Missing Data Mechanisms Using Visualisation
Studies in Classification, Data Analysis, and Knowledge Organization. 2021;205-213   Crossref logo

Using Case-Study Simulation to Improve Critical Thinking and Content Mastery in Undergraduate Nursing Students
Clinical Simulation in Nursing. 2010;6(3):e116   Crossref logo
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Recognising Cello Performers Using Timbre Models
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