Bayesian psychometric scaling

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Abstract

In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item response models received considerable attention to analyze test data and to measure latent variables. Bayesian psychometric modeling allows to include prior information about the assessment in addition to information available in the observed response data. An introduction is given to Bayesian psychometric modeling, and it is shown that this approach is very flexible, provides direct estimates of student proficiencies, and depends less on asymptotic results. Various Bayesian item response models are discussed to provide insight in Bayesian psychometric scaling and the Bayesian way of making psychometric inferences. This is done according to a general multilevel modeling approach, where observations are nested in students and items, and students are nested in schools. Different examples are given to illustrate the influence of prior information, the effects of clustered response data following a PISA study, and Bayesian methods for scale construction.
Original languageEnglish
Title of host publicationHandbook of psychometric testing
EditorsP. Irwing, T. Booth, D. Hughes
PublisherWiley-Blackwell
Pages-
Number of pages27
Publication statusPublished - 2015

Publication series

Name
PublisherWiley-Blackwell

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scaling
psychometrics
student
scale construction
PISA study
measurement method
available information
school

Keywords

  • METIS-299951
  • IR-88443

Cite this

Fox, G. J. A., van den Berg, S. M., & Veldkamp, B. P. (2015). Bayesian psychometric scaling. In P. Irwing, T. Booth, & D. Hughes (Eds.), Handbook of psychometric testing (pp. -). Wiley-Blackwell.
Fox, Gerardus J.A. ; van den Berg, Stéphanie Martine ; Veldkamp, Bernard P. / Bayesian psychometric scaling. Handbook of psychometric testing. editor / P. Irwing ; T. Booth ; D. Hughes. Wiley-Blackwell, 2015. pp. -
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Fox, GJA, van den Berg, SM & Veldkamp, BP 2015, Bayesian psychometric scaling. in P Irwing, T Booth & D Hughes (eds), Handbook of psychometric testing. Wiley-Blackwell, pp. -.

Bayesian psychometric scaling. / Fox, Gerardus J.A.; van den Berg, Stéphanie Martine; Veldkamp, Bernard P.

Handbook of psychometric testing. ed. / P. Irwing; T. Booth; D. Hughes. Wiley-Blackwell, 2015. p. -.

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

TY - CHAP

T1 - Bayesian psychometric scaling

AU - Fox, Gerardus J.A.

AU - van den Berg, Stéphanie Martine

AU - Veldkamp, Bernard P.

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PY - 2015

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N2 - In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item response models received considerable attention to analyze test data and to measure latent variables. Bayesian psychometric modeling allows to include prior information about the assessment in addition to information available in the observed response data. An introduction is given to Bayesian psychometric modeling, and it is shown that this approach is very flexible, provides direct estimates of student proficiencies, and depends less on asymptotic results. Various Bayesian item response models are discussed to provide insight in Bayesian psychometric scaling and the Bayesian way of making psychometric inferences. This is done according to a general multilevel modeling approach, where observations are nested in students and items, and students are nested in schools. Different examples are given to illustrate the influence of prior information, the effects of clustered response data following a PISA study, and Bayesian methods for scale construction.

AB - In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item response models received considerable attention to analyze test data and to measure latent variables. Bayesian psychometric modeling allows to include prior information about the assessment in addition to information available in the observed response data. An introduction is given to Bayesian psychometric modeling, and it is shown that this approach is very flexible, provides direct estimates of student proficiencies, and depends less on asymptotic results. Various Bayesian item response models are discussed to provide insight in Bayesian psychometric scaling and the Bayesian way of making psychometric inferences. This is done according to a general multilevel modeling approach, where observations are nested in students and items, and students are nested in schools. Different examples are given to illustrate the influence of prior information, the effects of clustered response data following a PISA study, and Bayesian methods for scale construction.

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KW - IR-88443

M3 - Chapter

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BT - Handbook of psychometric testing

A2 - Irwing, P.

A2 - Booth, T.

A2 - Hughes, D.

PB - Wiley-Blackwell

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Fox GJA, van den Berg SM, Veldkamp BP. Bayesian psychometric scaling. In Irwing P, Booth T, Hughes D, editors, Handbook of psychometric testing. Wiley-Blackwell. 2015. p. -