A Generalized Diagnostic Classification Modeling Framework Integrating Differential Speediness: Advantages and Illustrations in Psychological and Educational Testing.
Multivariate Behav Res
; 57(6): 940-959, 2022.
Article
in En
| MEDLINE
| ID: mdl-34152873
ABSTRACT
To advance the theoretical foundation of incorporating response times (RTs) into diagnostic classification models (DCMs), this study attempts to further derive, test and illustrate a generalized modeling framework (known as the JVRT-LCDM) that can simultaneously analyze response accuracy and differential speediness based on an existing method (Zhan et al., British Journal of Mathematical and Statistical Psychology, 71(2), 262-286, 2018). The JVRT-LCDM not only provides fine-grained diagnostic feedback without strict model constraints but also clarifies the specific speed trajectory of individuals. Moreover, some existing models from psychometric literatures are included in the JVRT-LCDM as special cases. The feasibility of the JVRT-LCDM is investigated via a Monte Carlo simulation study using a Bayesian estimation scheme, and two empirical datasets are then analyzed to illustrate the applicability of the JVRT-LCDM in practice. The results indicate that (1) as a generalized and flexible model, the JVRT-LCDM realizes high correct classification rates and accurate speed parameter recovery; (2) the JVRT-LCDM outperforms the existing models in terms of model-data fit, diagnostic consistency, and estimation of specific individuals in practical cognitive diagnosis assessments; and (3) the JVRT-LCDM provides reliable evidence for nonconstant speed modeling.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Educational Measurement
Type of study:
Diagnostic_studies
/
Health_economic_evaluation
/
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Multivariate Behav Res
Year:
2022
Document type:
Article
Affiliation country:
China