Randomized Item Response Theory Models

Jean-Paul Fox

Journal of Educational and Behavioral Statistics, 2005, vol. 30, issue 2, 189-212

Abstract: The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR technique links the observed item response with the true item response. Attitudes can be measured without knowing the true individual answers. This approach makes also a hierarchical analysis possible, with explanatory variables, given observed RR data. All model parameters can be estimated simultaneously using Markov chain Monte Carlo. The randomized item response technique was applied in a study on cheating behavior of students at a Dutch University. In this study, it is of interest if students’ cheating behavior differs across studies and if there are indicators that can explain differences in cheating behaviors.

Keywords: analysis of variance; item response theory model; Markov chain Monte Carlo (MCMC); random effects; randomized response (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:30:y:2005:i:2:p:189-212

DOI: 10.3102/10769986030002189

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