An Investigation of Goodness of Model Data Fit

IRT models have many advantages over CTT. However, the model-data fit should be verified as a prerequisite to use IRT models. Therefore, in this study it is aimed to investigate which IRT model will provide the best fit to the data obtained from SBS 2009 science subtest. For goodness-of-fit analysis, first the model assumptions and then the expected model features were tested. The model assumptions unidimensionality and local independence were investigated. In the expected model features part the invariance of ability parameter estimates and invariance of item parameter estimates were analyzed. To determine the best model, the results of the chi-square statistics of -2 log likelihood values of models were compared. The results suggested that three parameter logistic model is the most appropriate model for data fit.