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Zhehan Jiang
Institute of Medical Education, Peking University, Beijing, China;
National Center for Health Professions Education Development, Peking University, Beijing, China
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Yuting Han
Institute of Medical Education, Peking University, Beijing, China;
National Center for Health Professions Education Development, Peking University, Beijing, China
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Jihong Zhang
College of Education and Health Professions, University of Arkansas, Fayetteville, AR, USA
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Lingling Xu
Institute of Medical Education, Peking University, Beijing, China;
National Center for Health Professions Education Development, Peking University, Beijing, China
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Dexin Shi
Department of Psychology, University of South Carolina, Columbia, SC, USA
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Haiying Liang
Institute of Education, University College London, London, United Kingdom
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Jinying Ouyang
Institute of Medical Education, Peking University, Beijing, China;
National Center for Health Professions Education Development, Peking University, Beijing, China
Abstract
This study proposes an empirical ensemble equating (3E) approach that collectively selects, adopts, weighs, and combines outputs from different sources to take and combine advantage of equating techniques in various score intervals. The ensemble idea was demonstrated and tailored to the Non-Equivalent groups with Anchor Test (NEAT) equating. A simulation study based on several published settings was conducted. Three outcome measures – average bias, its absolute value, and root mean square difference – were used to evaluate the selected methods’ performance. The 3E approach outperformed other counterparts in most given conditions, while the cautions, such as tuning weights and assuming possible scenarios for using the proposed approach were also addressed.
