Hidden Markov item response theory models for responses and response times

Dylan Molenaar, D.L. Oberski, J.K. Vermunt, Paul De Boeck

Research output: Contribution to journalArticleScientificpeer-review

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
Original languageEnglish
Pages (from-to)606-626
JournalMultivariate Behavioral Research
Volume51
Issue number5
DOIs
Publication statusPublished - 2 Sep 2016

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Model Theory
Response Time
Modeling
Latent Class Model
Conditional Independence
Psychometrics
Dynamic Modeling
Demonstrate
Recovery
Item Response Theory
Simulation Study
Model
Departure

Cite this

Molenaar, Dylan ; Oberski, D.L. ; Vermunt, J.K. ; De Boeck, Paul. / Hidden Markov item response theory models for responses and response times. In: Multivariate Behavioral Research. 2016 ; Vol. 51, No. 5. pp. 606-626.
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Hidden Markov item response theory models for responses and response times. / Molenaar, Dylan; Oberski, D.L.; Vermunt, J.K.; De Boeck, Paul.

In: Multivariate Behavioral Research, Vol. 51, No. 5, 02.09.2016, p. 606-626.

Research output: Contribution to journalArticleScientificpeer-review

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AB - 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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