Abstract
Person fit procedures conducted at the individual level provide information regarding the trustworthiness of an individual test score. In computer adaptive tests (CAT), these person fit procedures are useful because traditional ways to examine model-data fit are limited due to test-takers receiving different sets of items. This study explores a two-step procedure for examining person fit in CAT. Five thousand person responses to a computer adaptive test were generated under the Rasch model. Then, three person fit statistics, Outfit MSE, Infit MSE, and Between Fit MSE, were used to categorize each person as fitting or misfitting by the Rasch model. Next, expected and empirical person response functions (PRF) were visually inspected for discrepancies between the model-expected patterns and the patterns observed in the data. The PRF and the person fit statistics provided complementary pieces of information about person misfit. This information can help guide practitioners in making judgements regarding person fit, and consequently about the validity of inferences from adaptive test scores.
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