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
KEYWORDS: Conditional independence, dynamic modeling, hidden Markov modeling, item response theory, latent class models, response time modeling
Original language | English |
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Pages (from-to) | 606-626 |
Journal | Multivariate Behavioral Research |
Volume | 51 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2 Sept 2016 |