Abstract
KEYWORDS: Conditional independence, dynamic modeling, hidden Markov modeling, item response theory, latent class models, response time modeling
| Original language | English |
|---|---|
| Pages (from-to) | 606-626 |
| Journal | Multivariate Behavioral Research |
| Volume | 51 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2 Sep 2016 |
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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 journal › Article › Scientific › peer-review
TY - JOUR
T1 - Hidden Markov item response theory models for responses and response times
AU - Molenaar, Dylan
AU - Oberski, D.L.
AU - Vermunt, J.K.
AU - De Boeck, Paul
PY - 2016/9/2
Y1 - 2016/9/2
N2 - 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
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
U2 - 10.1080/00273171.2016.1192983
DO - 10.1080/00273171.2016.1192983
M3 - Article
VL - 51
SP - 606
EP - 626
JO - Multivariate Behavioral Research
JF - Multivariate Behavioral Research
SN - 0027-3171
IS - 5
ER -