Diagnosing item score patterns on a test using item response theory-based person-fit statistics.
Person-fit statistics have been proposed to investigate the fit of an item score pattern to an item response theory (IRT) model. The author investigated how these statistics can be used to detect different types of misfit. Intelligence test data were analyzed using person-fit statistics in the context of the G. Rasch (1960) model and R. J. Mokken's (1971, 1997) IRT models. The effect of the choice of an IRT model to detect misfitting item score patterns and the usefulness of person-fit statisticsfor diagnosis of misfit are discussed. Results showed that different types of person-fit statistics can be used to detect different kinds of person misfit. Parametric person-fit statistics had more power than nonparametric person-fit statistics.
Meijer
Rob R
RR
Faculty of Behavioural Sciences, Department of Measurement and Data Analysis, University of Twente, Enschede, the Netherlands. meijer@edte.utwente.nl
D000328:Adult; D001077:Aptitude Tests / Q000706:statistics & numerical data*; D015982:Bias; D003627:Data Interpretation, Statistical; D006801:Humans; D007361:Intelligence Tests / Q000706:statistics & numerical data*; D008432:Mathematical Computing; D015233:Models, Statistical; D010560:Personnel Selection / Q000706:statistics & numerical data; D011336:Probability; D011594:Psychometrics / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012984:Software