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Hidden Markov Item Response Theory Models for Responses and Response Times
Authors:Dylan Molenaar  Daniel Oberski  Jeroen Vermunt  Paul De Boeck
Affiliation:1. University of Amsterdam;2. Tilburg University;3. Ohio State University
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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