Complex latent variable modeling in educational assessment

J.-P. Fox, M. Marsman, J. Mulder, J.A. Verhagen

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Bayesian item response theory models have been widely used in different research fields. They support measuring constructs and modeling relationships between constructs, while accounting for complex test situations (e.g., complex sampling designs, missing data, heterogenous population). Advantages of this flexible modeling framework together with powerful simulation-based estimation techniques are discussed. Furthermore, it is shown how the Bayes factor can be used to test relevant hypotheses in assessment using the College Basic Academic Subjects Examination (CBASE) data.
Original languageEnglish
Pages (from-to)1499-1510
JournalCommunications in Statistics: Part B: Simulation and Computation
Volume45
Issue number5
DOIs
Publication statusPublished - 2016

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Complex Variables
Latent Variables
Sampling
Bayes Factor
Sampling Design
Hypothesis Test
Model Theory
Missing Data
Modeling
Simulation
Education
Framework
Relationships

Cite this

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Complex latent variable modeling in educational assessment. / Fox, J.-P.; Marsman, M.; Mulder, J.; Verhagen, J.A.

In: Communications in Statistics: Part B: Simulation and Computation, Vol. 45, No. 5, 2016, p. 1499-1510.

Research output: Contribution to journalArticleScientificpeer-review

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T1 - Complex latent variable modeling in educational assessment

AU - Fox, J.-P.

AU - Marsman, M.

AU - Mulder, J.

AU - Verhagen, J.A.

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AB - Bayesian item response theory models have been widely used in different research fields. They support measuring constructs and modeling relationships between constructs, while accounting for complex test situations (e.g., complex sampling designs, missing data, heterogenous population). Advantages of this flexible modeling framework together with powerful simulation-based estimation techniques are discussed. Furthermore, it is shown how the Bayes factor can be used to test relevant hypotheses in assessment using the College Basic Academic Subjects Examination (CBASE) data.

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DO - 10.1080/03610918.2014.939518

M3 - Article

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SP - 1499

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JO - Communications in Statistics: Part B: Simulation and Computation

JF - Communications in Statistics: Part B: Simulation and Computation

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ER -