Modeling of Responses and Response Times with the Package CIRT

Research output: Contribution to journalArticleAcademic

41 Citations (Scopus)
74 Downloads (Pure)

Abstract

In computerized testing, the test takers' responses as well as their response times on the items are recorded. The relationship between response times and response accuracies is complex and varies over levels of observation. For example, it takes the form of a tradeoff between speed and accuracy at the level of a fixed person but may become a positive correlation for a population of test takers. In order to explore such relationships and test hypotheses about them, a conjoint model is proposed. Item responses are modeled by a two-parameter normal-ogive IRT model and response times by a lognormal model. The two models are combined using a hierarchical framework based on the fact that response times and responses are nested within individuals. All parameters can be estimated simultaneously using an MCMC estimation approach. A R-package for the MCMC algorithm is presented and explained.
Original languageUndefined
Pages (from-to)1-14
JournalJournal of statistical software
Volume20
Issue number7
Publication statusPublished - 2007

Keywords

  • FORTRAN
  • response times
  • Hierarchical IRT model
  • IR-59665
  • MCMC

Cite this

@article{c6c5c2dd15ea4c0480623255ae4c8970,
title = "Modeling of Responses and Response Times with the Package CIRT",
abstract = "In computerized testing, the test takers' responses as well as their response times on the items are recorded. The relationship between response times and response accuracies is complex and varies over levels of observation. For example, it takes the form of a tradeoff between speed and accuracy at the level of a fixed person but may become a positive correlation for a population of test takers. In order to explore such relationships and test hypotheses about them, a conjoint model is proposed. Item responses are modeled by a two-parameter normal-ogive IRT model and response times by a lognormal model. The two models are combined using a hierarchical framework based on the fact that response times and responses are nested within individuals. All parameters can be estimated simultaneously using an MCMC estimation approach. A R-package for the MCMC algorithm is presented and explained.",
keywords = "FORTRAN, response times, Hierarchical IRT model, IR-59665, MCMC",
author = "Fox, {Gerardus J.A.} and {Klein Entink}, R.H. and {van der Linden}, {Willem J.}",
note = "Supplements at: http://www.jstatsoft.org/v20/i07",
year = "2007",
language = "Undefined",
volume = "20",
pages = "1--14",
journal = "Journal of statistical software",
issn = "1548-7660",
publisher = "University of California at Los Angeles",
number = "7",

}

Modeling of Responses and Response Times with the Package CIRT. / Fox, Gerardus J.A.; Klein Entink, R.H.; van der Linden, Willem J.

In: Journal of statistical software, Vol. 20, No. 7, 2007, p. 1-14.

Research output: Contribution to journalArticleAcademic

TY - JOUR

T1 - Modeling of Responses and Response Times with the Package CIRT

AU - Fox, Gerardus J.A.

AU - Klein Entink, R.H.

AU - van der Linden, Willem J.

N1 - Supplements at: http://www.jstatsoft.org/v20/i07

PY - 2007

Y1 - 2007

N2 - In computerized testing, the test takers' responses as well as their response times on the items are recorded. The relationship between response times and response accuracies is complex and varies over levels of observation. For example, it takes the form of a tradeoff between speed and accuracy at the level of a fixed person but may become a positive correlation for a population of test takers. In order to explore such relationships and test hypotheses about them, a conjoint model is proposed. Item responses are modeled by a two-parameter normal-ogive IRT model and response times by a lognormal model. The two models are combined using a hierarchical framework based on the fact that response times and responses are nested within individuals. All parameters can be estimated simultaneously using an MCMC estimation approach. A R-package for the MCMC algorithm is presented and explained.

AB - In computerized testing, the test takers' responses as well as their response times on the items are recorded. The relationship between response times and response accuracies is complex and varies over levels of observation. For example, it takes the form of a tradeoff between speed and accuracy at the level of a fixed person but may become a positive correlation for a population of test takers. In order to explore such relationships and test hypotheses about them, a conjoint model is proposed. Item responses are modeled by a two-parameter normal-ogive IRT model and response times by a lognormal model. The two models are combined using a hierarchical framework based on the fact that response times and responses are nested within individuals. All parameters can be estimated simultaneously using an MCMC estimation approach. A R-package for the MCMC algorithm is presented and explained.

KW - FORTRAN

KW - response times

KW - Hierarchical IRT model

KW - IR-59665

KW - MCMC

M3 - Article

VL - 20

SP - 1

EP - 14

JO - Journal of statistical software

JF - Journal of statistical software

SN - 1548-7660

IS - 7

ER -