TY  - JOUR
TI  - Retrofitting of Polytomous Cognitive Diagnosis and Multidimensional Item Response Theory Models
AB  - In this study, person parameter recoveries are investigated by retrofitting polytomous attribute cognitivediagnosis and multidimensional item response theory (MIRT) models. The data are generated using twocognitive diagnosis models (i.e., pG-DINA: the polytomous generalized deterministic inputs, noisy “and” gateand fA-M: the fully-additive model) and one MIRT model (i.e., the compensatory two-parameter logistic model).Twenty-five replications are used for each of the 54 conditions resulting from varying the item discriminationindex, ratio of simple to complex items, test length, and correlations between skills. The findings are obtainedby comparing the person parameter estimates of all three models to the actual parameters used in the datageneration. According to the findings, the most accurate estimates are obtained when the fitted modelscorrespond to the generating models. Comparable results are obtained when the fA-M is retrofitted to other dataor when the MIRT model is retrofitted to fA-M data. However, the results are poor when the pG-DINA isretrofitted to other data or the MIRT is retrofitted to pG-DINA data. Among the conditions used in the study,test length and item discrimination have the greatest influence on the person parameter estimation accuracy.Variation in the simple to complex item ratio has a notable influence when the MIRT model is used. Althoughthe impact on the person parameter estimation accuracy of the correlation between skills is limited, its effect onMIRT data is more significant.
AU  - YAKAR, LEVENT
AU  - de la Torre, Jimmy
AU  - DOĞAN, NURİ
DO  - 10.21031/epod.778861
PY  - 2021
JO  - Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi
VL  - 12
IS  - 2
SN  - 1309-6575
SP  - 97
EP  - 111
DB  - TRDizin
UR  - http://search/yayin/detay/460816
ER  -