Partially-compensatory multi-dimensional IRT models: Two alternate model forms
Publication Date
2016
Document Type
Article
Abstract
Partially compensatory models may capture the cognitive skills needed to answer test items more realistically than compensatory models, but estimating the model parameters may be a challenge. Data were simulated to follow two different partially compensatory models, a model with an interaction term and a product model. The model parameters were then estimated for both models and for the compensatory model. Either the model used to simulate the data or the compensatory model generally had the best fit, as indexed by information criteria. Interfactor correlations were estimated well by both the correct model and the compensatory model. The predicted response probabilities were most accurate from the model used to simulate the data. Regarding item parameters, root mean square errors seemed reason-able for the interaction model but were quite large for some items for the product model. Thetas were recovered similarly by all models, regardless of the model used to simulate the data.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
DeMars, C. E. (2016). Partially-compensatory multi-dimensional IRT models: Two alternate model forms. Educational and Psychological Measurement, 76, 231-257
