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Diagnostic Classification Models for Testlets: Methods and Theory
PsychometrikaDiagnostic classification models (DCMs) have seen wide applications in educational and psychological measurement, especially in formative assessment. DCMs in the presence of testlets have been studied in recent literature. A key ingredient in the statistical modeling and analysis of testlet-based DCMs is the superposition of two latent structures, the ...
Xin Xu +4 more
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Diagnostic Classification Modeling with flexMIRT
2019In this chapter, we will focus on the use of flexMIRT® (Cai L, flexMIRT® version 3.5: Flexible multilevel multidimensional item analysis and test scoring [Computer software]. Vector Psychometric Group, LLC, Chapel Hill, 2017) for estimating certain core diagnostic models that have seen practical application, as well as to illustrate the specialized ...
Li Cai, Carrie R. Houts
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Variational Bayes Inference Algorithm for the Saturated Diagnostic Classification Model
Psychometrika, 2020Saturated diagnostic classification models (DCM) can flexibly accommodate various relationships among attributes to diagnose individual attribute mastery, and include various important DCMs as sub-models. However, the existing formulations of the saturated DCM are not better suited for deriving conditionally conjugate priors of model parameters ...
Kazuhiro Yamaguchi, Kensuke Okada
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A DIAGNOSTIC CLASSIFICATION MODEL FOR DOCUMENT PROCESSING SKILLS
ETS Research Report Series, 1993ABSTRACTThis paper introduces a modification to the Rule Space diagnostic classification procedure which allows for processing of response vectors containing missing data. Rule Space is an approach to diagnostic classification which involves characterizing examinees' performances in terms of an underlying cognitive model of generalized problem‐solving ...
Kathleen Sheehan +2 more
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Evidentiary Reasoning in Diagnostic Classification Models
Measurement: Interdisciplinary Research and Perspectives, 2009In Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art, Rupp and Templin (2008 hereafter RT) undertake the ambitious task of providing...
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Medical diagnostic testing models for multifactorial disease classifications
Statistics in Medicine, 2005In this note we extend the logistic regression receiver operating characteristic (ROC) analysis framework to diagnosing disease that can be classified in a 2 x 2 factorial setting. Similar to the standard ROC curve analysis these new models accommodate prediction of cross-classifications for treatment success and diagnosis of disease.
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Equivalent Diagnostic Classification Models
Measurement: Interdisciplinary Research & Perspective, 2009Maris, G., Bechger, T.
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Differential Item Functioning in Diagnostic Classification Models
2019Assessment of differential item functioning (DIF) in diagnostic classification models (DCMs) has begun to attract research attention. In previous studies, authors found that DIF detection in DCMs appeared to be very powerful even when most or all the items on the studied test had DIF and no scale purification was necessary.
Qiu, Xue-Lan +2 more
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Classification Model for Estimation of Risk Factors in Cardiological Diagnostics
2008The proposed classification model for risk factor estimation makes semi-automatic data analysis based on advanced machine-learning methods. The objective is to provide intelligent computer-based support for medical diagnostics. The developed fuzzy boundary classification determines risk factors importance and adjusts the threshold. Experimental results
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