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Ma, Wenchao; de la Torre, Jimmy – Educational Measurement: Issues and Practice, 2019
In this ITEMS module, we introduce the generalized deterministic inputs, noisy "and" gate (G-DINA) model, which is a general framework for specifying, estimating, and evaluating a wide variety of cognitive diagnosis models. The module contains a nontechnical introduction to diagnostic measurement, an introductory overview of the G-DINA…
Descriptors: Models, Classification, Measurement, Identification
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Ketabi, Somaye; Alavi, Seyyed Mohammed; Ravand, Hamdollah – International Journal of Language Testing, 2021
Although Diagnostic Classification Models (DCMs) were introduced to education system decades ago, it seems that these models were not employed for the original aims upon which they had been designed. Using DCMs has been mostly common in analyzing large-scale non-diagnostic tests and these models have been rarely used in developing Cognitive…
Descriptors: Diagnostic Tests, Test Construction, Goodness of Fit, Classification
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Liu, Ren – Educational and Psychological Measurement, 2018
Attribute structure is an explicit way of presenting the relationship between attributes in diagnostic measurement. The specification of attribute structures directly affects the classification accuracy resulted from psychometric modeling. This study provides a conceptual framework for understanding misspecifications of attribute structures. Under…
Descriptors: Diagnostic Tests, Classification, Test Construction, Relationship
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Choi, Youn-Jeng; Asilkalkan, Abdullah – Measurement: Interdisciplinary Research and Perspectives, 2019
About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications…
Descriptors: Item Response Theory, Data Analysis, Computer Software, Test Bias
McDermott, Paul A.; Watkins, Marley W. – 1979
A computer program named Program STANDARD is presented and demonstrated. This program calculates the statistical significance of the overall agreement of the categorical assignments. The program is based on Light's statistic, G, for describing the conjoint agreement of many observers with correct or standard set of classifications on nominal…
Descriptors: Classification, Computer Programs, Goodness of Fit, Nonparametric Statistics