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Reporting Subscores Using R: A Software Review

Author

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  • Shenghai Dai
  • Dubravka Svetina
  • Xiaolin Wang

Abstract

There is an increasing interest in reporting test subscores for diagnostic purposes. In this article, we review nine popular R packages (subscore, mirt, TAM, sirt, CDM, NPCD, lavaan, sem, and OpenMX) that are capable of implementing subscore-reporting methods within one or more frameworks including classical test theory, multidimensional item response theory, cognitive diagnostic models, and factor analysis. A real data example is used to illustrate how to examine whether subscores should be reported and how to obtain subscores. We also briefly compare the features of selected packages for reporting subscores.

Suggested Citation

  • Shenghai Dai & Dubravka Svetina & Xiaolin Wang, 2017. "Reporting Subscores Using R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 42(5), pages 617-638, October.
    • Handle: RePEc:sae:jedbes:v:42:y:2017:i:5:p:617-638
    DOI: 10.3102/1076998617716462
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    References listed on IDEAS

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    1. Shelby Haberman & Sandip Sinharay, 2010. "Reporting of Subscores Using Multidimensional Item Response Theory," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 209-227, June.
    2. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    3. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    4. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    Full references (including those not matched with items on IDEAS)

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