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A general cognitive diagnosis model for expert-defined polytomous attributes created by Jinsong Chen, Jimmy de la Torre

By: Contributor(s): Material type: TextTextSeries: ; Volume , number ,China : Sage; 2013Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
Subject(s): Online resources: Summary: Polytomous attributes, particularly those defined as part of the test development process, can provide additional diagnostic information. The present research proposes the polytomous generalized deterministic inputs, noisy, “and” gate (pG-DINA) model to accommodate such attributes. The pG-DINA model allows input from substantive experts to specify attribute levels and is a general model that subsumes various reduced models. In addition to model formulation, the authors evaluate the viability of the proposed model by examining how well the model parameters can be estimated under various conditions, and compare its classification accuracy against that of the conventional G-DINA model with a modified classification rule. A real-data example is used to illustrate the application of the model in practice.
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Item type Current library Call number Vol info Copy number Status Notes Date due Barcode
Journal Article Journal Article Main Library - Special Collections BF39 APP (Browse shelf(Opens below)) Vol. 37, No. 6 pages 419-437 SP17170 Not for loan For in-house use only

Polytomous attributes, particularly those defined as part of the test development process, can provide additional diagnostic information. The present research proposes the polytomous generalized deterministic inputs, noisy, “and” gate (pG-DINA) model to accommodate such attributes. The pG-DINA model allows input from substantive experts to specify attribute levels and is a general model that subsumes various reduced models. In addition to model formulation, the authors evaluate the viability of the proposed model by examining how well the model parameters can be estimated under various conditions, and compare its classification accuracy against that of the conventional G-DINA model with a modified classification rule. A real-data example is used to illustrate the application of the model in practice.

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