cirt

Modeling of responses and response times with the package cirt. 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 simultaneously using an MCMC estimation approach. A R-package for the MCMC algorithm is presented and explained.

This software is also peer reviewed by journal JSS.


References in zbMATH (referenced in 11 articles , 1 standard article )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Jean-Paul Fox, Konrad Klotzke, Rinke Klein Entink: LNIRT: An R Package for Joint Modeling of Response Accuracy and Times (2021) arXiv
  2. Klotzke, Konrad; Fox, Jean-Paul: Modeling dependence structures for response times in a Bayesian framework (2019)
  3. Marsman, M.; Sigurdardóttir, H.; Bolsinova, M.; Maris, G.: Characterizing the manifest probability distributions of three latent trait models for accuracy and response time (2019)
  4. Bolsinova, Maria; Tijmstra, Jesper: Improving precision of ability estimation: getting more from response times (2018)
  5. Molenaar, Dylan; de Boeck, Paul: Response mixture modeling: accounting for heterogeneity in item characteristics across response times (2018)
  6. Culpepper, Steven Andrew; Balamuta, James Joseph: A hierarchical model for accuracy and choice on standardized tests (2017)
  7. Fox, Jean-Paul: Multivariate zero-inflated modeling with latent predictors: modeling feedback behavior (2013)
  8. Fox, Jean Paul: Bayesian item response modeling. Theory and applications. (2010)
  9. van der Linden, Wim J.; Glas, Cees A. W.: Statistical tests of conditional independence between responses and/or response times on test items (2010)
  10. Jan de Leeuw; Patrick Mair: An Introduction to the Special Volume on ”Psychometrics in R” (2007) not zbMATH
  11. Jean-Paul Fox; Rinke Entink; Wilm van der Linden: Modeling of Responses and Response Times with the Package cirt (2007) not zbMATH