Using multilabel classification neural network to detect intersectional DIF with small sample sizes
Abstract This study introduces InterDIFNet, a multilabel classification neural network for detecting intersectional differential item functioning (DIF) in educational and psychological assessments, with a focus on small sample sizes. Unlike traditional marginal DIF methods, which often fail to capture the effects of intersecting identities and require ...
Yale Quan, Chun Wang
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Reducing misdiagnoses and cognitive errors using virtual patients and automated feedback in a clinical reasoning curriculum. [PDF]
Waechter J +6 more
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Criticality and Magnetic Phases of Ising Shastry-Sutherland Candidate Holmium Tetraboride. [PDF]
Khundzakishvili G +9 more
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The promise of cardiomyocyte computational models for drug safety. [PDF]
Wang L, Rodriguez B.
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Statistical Characteristics of Strong Earthquake Sequence in Northeastern Tibetan Plateau. [PDF]
Wang Y +7 more
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Stability through plasticity: Finding robust memories through representational drift. [PDF]
Natrajan M, Fitzgerald JE.
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Sulfur Speciation in Li-S Batteries Determined by Operando Laboratory X-ray Emission Spectroscopy. [PDF]
Rajh A +4 more
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