cover image: An Investigation of the Robustness of a Partial Credit Model-Based Computerized Adaptive Test to Misfitting Items.

An Investigation of the Robustness of a Partial Credit Model-Based Computerized Adaptive Test to Misfitting Items.

The robustness of a partial credit (PC) model-based computerized adaptive test's (CAT's) ability estimation to items that did not fit the PC model was investigated. A CAT program was written based on the PC model. The program used maximum likelihood estimation of ability. Item selection was on the basis of information. The simulation terminated when a maximum of 30 items was reached or when a predetermined standard error of estimate (SEE) was obtained. SEE termination criteria of 0.20, 0.25, and 0.30 were used. Responses to 150 5-alternative items generated according to a linear factor analytic model were simulated for 1,000 examinees. Results indicate that reasonably accurate ability estimation could be obtained despite the adaptive tests, which, on the average, contained up to 45% misfitting items. The inclusion of the misfitting items did not appear to increase the PC CAT test lengths. The benefits of polytomous model-based CATs were discussed. Three data tables, five figures, and a 30-item list of references are included. (SLD)

Authors

De Ayala, R. J., And Others

Peer Reviewed
F
Publication Type
['Reports - Evaluative', 'Speeches/Meeting Papers']
Published in
United States of America

Table of Contents