Data of a science knowledge test: Simulation of item preknowledge

In order to simulate how data would look like if some test takers possessed item preknowledge we compromised two original datasets: Responses to a predetermined set of items were set to correct for 10% of test takers, randomly selected. In reruns, the proportion was varied to be 5%, 2.5%, and 1%. Item difficulty, item discrimination, item fit, and local dependence were computed using an IRT 2PL model.

Then changes in these item properties from the non-compromised to the compromised dataset were scrutinized for their sensitivity to item preknowledge. Data In each file the responses to a test with 80 items are given (0 = not correct / 1= correct). The compromised datasets (that contain simulated test takers with item preknowledge) are flagged with the suffix _pX, where X desribes the prevalence of item preknowledge.