Hidden Markov item response theory models for responses and response times
Molenaar,Dylan Oberski,D.L. Vermunt,J.K. De Boeck,Paul
Molenaar,Dylan
Oberski,D.L.
Vermunt,J.K.
De Boeck,Paul
Abstract
Current approaches to model responses and response times to psychometric tests solely focus on between-subject differences in speed and ability. Within subjects, speed and ability are assumed to be constants. Violations of this assumption are generally absorbed in the residual of the model. As a result, within-subject departures from the between-subject speed and ability level remain undetected. These departures may be of interest to the researcher as they reflect differences in the response processes adopted on the items of a test. In this article, we propose a dynamic approach for responses and response times based on hidden Markov modeling to account for within-subject differences in responses and response times. A simulation study is conducted to demonstrate acceptable parameter recovery and acceptable performance of various fit indices in distinguishing between different models. In addition, both a confirmatory and an exploratory application are presented to demonstrate the practical value of the modeling approach. KEYWORDS: Conditional independence, dynamic modeling, hidden Markov modeling, item response theory, latent class models, response time modeling
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Date
2016-09-02
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Research Projects
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Molenaar, D, Oberski, D L, Vermunt, J K & De Boeck, P 2016, 'Hidden Markov item response theory models for responses and response times', Multivariate Behavioral Research, vol. 51, no. 5, pp. 606-626. https://doi.org/10.1080/00273171.2016.1192983
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info:eu-repo/semantics/openAccess