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Chapter 3 - Item Response Theory

Published online by Cambridge University Press:  13 May 2021

Craig S. Wells
Affiliation:
University of Massachusetts, Amherst
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Summary

IRT is a powerful scaling technique that provides a collection of latent variable models that describe performance at the item level relative to an examinee’s latent variable. IRT models have several attractive features that make them appealing for test developers and researchers to use to construct educational and psychological tests (Lord, 1980). The models can be applied to educational achievement tests such as TIMSS, as well as to psychological latent variables such as depression or anxiety measures. IRT is the driving force for the development and widespread use of computerized adaptive testing. The purpose of this chapter is to introduce IRT and its fundamental principles and applications so that the reader who is unfamiliar with IRT will have sufficient knowledge to apply the IRT DIF methods described in Chapter 4.

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Publisher: Cambridge University Press
Print publication year: 2021

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  • Item Response Theory
  • Craig S. Wells, University of Massachusetts, Amherst
  • Book: Assessing Measurement Invariance for Applied Research
  • Online publication: 13 May 2021
  • Chapter DOI: https://doi.org/10.1017/9781108750561.004
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  • Item Response Theory
  • Craig S. Wells, University of Massachusetts, Amherst
  • Book: Assessing Measurement Invariance for Applied Research
  • Online publication: 13 May 2021
  • Chapter DOI: https://doi.org/10.1017/9781108750561.004
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Item Response Theory
  • Craig S. Wells, University of Massachusetts, Amherst
  • Book: Assessing Measurement Invariance for Applied Research
  • Online publication: 13 May 2021
  • Chapter DOI: https://doi.org/10.1017/9781108750561.004
Available formats
×