Modeling of Item Response Functions Under the D -Scoring Method.

This study presents new models for item response functions (IRFs) in the framework of the D -scoring method (DSM) that is gaining attention in the field of educational and psychological measurement and largescale assessments. In a previous work on DSM, the IRFs of binary items were estimated using a...

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Published in:Educational & Psychological Measurement Vol. 80; no. 1; pp. 126 - 145
Main Author: Dimitrov, Dimiter M.
Format: Article
Published: Sage Publications Inc. Feb2020
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Feb2020
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      pub: Sage Publications Inc.
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        141048274
        10.1177/0013164419854176
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        atl: Modeling of Item Response Functions Under the D -Scoring Method.
      aug:
        au: Dimitrov, Dimiter M.
        affil:
          National Center for Assessment, Riyadh, Saudi Arabia
          George Mason University, Fairfax, VA, USA
      su:
        Educational tests & measurements
        Psychometrics
        Scaling (Social sciences)
        High performance computing
        Probability theory
        Research
        Research evaluation
        Statistics
        Logistic regression analysis
        Data analysis
        Research methodology evaluation
        Statistical models
        Differential item functioning (Research bias)
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          Educational tests & measurements
          Psychometrics
          Scaling (Social sciences)
          High performance computing
          Probability theory
          Research
          Research evaluation
          Statistics
          Logistic regression analysis
          Data analysis
          Research methodology evaluation
          Statistical models
          Differential item functioning (Research bias)
      keyword:
        D-scoring method
        item response function
        scaling
        true scores
        D-scoring method
        item response function
        scaling
        true scores
      ab: This study presents new models for item response functions (IRFs) in the framework of the D -scoring method (DSM) that is gaining attention in the field of educational and psychological measurement and largescale assessments. In a previous work on DSM, the IRFs of binary items were estimated using a logistic regression model (LRM). However, the LRM underestimates the item true scores at the top end of the D -scale (ranging from 0 to 1), especially for relatively difficult items. This entails underestimation of true D -scores, inaccuracy in the estimates of their standard errors, and other psychometric issues. The inverse-regression adjustments used to fix this problem are too complicated for regular applications of the DSM and not in line with its simplicity. This issue is resolved with the IRF models proposed in this study, referred to as rational function models (RFMs) with one parameter (RFM1), two parameters (RFM2), and three parameters (RFM3). The proposed RFMs are discussed and illustrated with simulated and real data.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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