Premium
Assessing Goodness of Fit of Item Response Theory Models: A Comparison of Traditional and Alternative Procedures
Author(s) -
Stone Clement A.,
Zhang Bo
Publication year - 2003
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.2003.tb01150.x
Subject(s) - item response theory , goodness of fit , type i and type ii errors , sample size determination , econometrics , computer science , statistics , empirical research , sample (material) , data mining , mathematics , machine learning , psychometrics , chemistry , chromatography
Testing the goodness of fit of item response theory (IRT) models is relevant to validating IRT models, and new procedures have been proposed. These alternatives compare observed and expected response frequencies conditional on observed total scores, and use posterior probabilities for responses across θ levels rather than cross‐classifying examinees using point estimates of θ and score responses. This research compared these alternatives with regard to their methods, properties (Type 1 error rates and empirical power), available research, and practical issues (computational demands, treatment of missing data, effects of sample size and sparse data, and available computer programs). Different advantages and disadvantages related to these characteristics are discussed. A simulation study provided additional information about empirical power and Type 1 error rates.