Bayesian adaptive testing with polytomous items

Hao Ren; Seung W. Choi; Wim J. van der Linden

doi:10.1007/s41237-020-00114-8

Bayesian adaptive testing with polytomous items

Hao Ren, Seung W. Choi, Wim J. van der Linden^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

7 Citations (Scopus)

93 Downloads (Pure)

Abstract

An extremely efficient MCMC method for Bayesian adaptive testing with polytomous items is explained both conceptually and in mathematical detail. Results from extensive simulation studies with different item pools, polytomous response models, calibration sample sizes, and test lengths are presented. In addition, the case of adaptive testing from pools with a mixture of dichotomous and polytomous items is addressed.

Original language	English
Pages (from-to)	427-449
Number of pages	23
Journal	Behaviormetrika
Volume	47
Issue number	2
Early online date	21 May 2020
DOIs	https://doi.org/10.1007/s41237-020-00114-8
Publication status	Published - 1 Jul 2020

Keywords

UT-Hybrid-D
Bayesian optimality
Item calibration
MCMC algorithm
Polytomous response models
Adaptive testing

Access to Document

10.1007/s41237-020-00114-8Licence: CC BY

ArticleFinal published version, 2.45 MBLicence: CC BY

Cite this

@article{727baa2f5e584e17ba9d9b612e4ce019,

title = "Bayesian adaptive testing with polytomous items",

abstract = "An extremely efficient MCMC method for Bayesian adaptive testing with polytomous items is explained both conceptually and in mathematical detail. Results from extensive simulation studies with different item pools, polytomous response models, calibration sample sizes, and test lengths are presented. In addition, the case of adaptive testing from pools with a mixture of dichotomous and polytomous items is addressed.",

keywords = "UT-Hybrid-D, Bayesian optimality, Item calibration, MCMC algorithm, Polytomous response models, Adaptive testing",

author = "Hao Ren and Choi, {Seung W.} and {van der Linden}, {Wim J.}",

note = "Springer deal",

year = "2020",

month = jul,

day = "1",

doi = "10.1007/s41237-020-00114-8",

language = "English",

volume = "47",

pages = "427--449",

journal = "Behaviormetrika",

issn = "0385-7417",

publisher = "Behaviormetric Society of Japan",

number = "2",

}

TY - JOUR

T1 - Bayesian adaptive testing with polytomous items

AU - Ren, Hao

AU - Choi, Seung W.

AU - van der Linden, Wim J.

N1 - Springer deal

PY - 2020/7/1

Y1 - 2020/7/1

N2 - An extremely efficient MCMC method for Bayesian adaptive testing with polytomous items is explained both conceptually and in mathematical detail. Results from extensive simulation studies with different item pools, polytomous response models, calibration sample sizes, and test lengths are presented. In addition, the case of adaptive testing from pools with a mixture of dichotomous and polytomous items is addressed.

AB - An extremely efficient MCMC method for Bayesian adaptive testing with polytomous items is explained both conceptually and in mathematical detail. Results from extensive simulation studies with different item pools, polytomous response models, calibration sample sizes, and test lengths are presented. In addition, the case of adaptive testing from pools with a mixture of dichotomous and polytomous items is addressed.

KW - UT-Hybrid-D

KW - Bayesian optimality

KW - Item calibration

KW - MCMC algorithm

KW - Polytomous response models

KW - Adaptive testing

UR - http://www.scopus.com/inward/record.url?scp=85085160481&partnerID=8YFLogxK

U2 - 10.1007/s41237-020-00114-8

DO - 10.1007/s41237-020-00114-8

M3 - Article

AN - SCOPUS:85085160481

SN - 0385-7417

VL - 47

SP - 427

EP - 449

JO - Behaviormetrika

JF - Behaviormetrika

IS - 2

ER -

Bayesian adaptive testing with polytomous items

Abstract

Keywords

Access to Document

Other files and links

Cite this