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 trade-off 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 simul-taneously using an MCMC estimation approach. A R-package for the MCMC algorithm is presented and explained.
Keywords
Markov chain Monte CarloItem response theoryStatisticsComputer sciencePopulationCorrelationResponse timeTest (biology)Log-normal distributionMathematicsEconometricsMonte Carlo method
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Publication Info
- Year
- 2007
- Type
- article
- Volume
- 20
- Issue
- 7
- Citations
- 127
- Access
- Closed
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Cite This
Jean‐Paul Fox,
Rinke Klein Entink,
Wim van der Linden
(2007).
Modeling of Responses and Response Times with the Package<b>cirt</b>.
Journal of Statistical Software
, 20
(7)
.
https://doi.org/10.18637/jss.v020.i07
Identifiers
- DOI
- 10.18637/jss.v020.i07