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Item Estimates Under Low-Stakes Conditions: How Should Omits Be Treated?, Christine E. Demars
Item Estimates Under Low-Stakes Conditions: How Should Omits Be Treated?, Christine E. Demars
Department of Graduate Psychology - Faculty Scholarship
Using data from a pilot test of science and math, item difficulties were estimated with a one-parameter model (partial-credit model for the multi-point items). Some items were multiple-choice items, and others were constructed-response items (open-ended). Four sets of estimates were obtained: estimates for males and females, and treating omitted items as incorrect and treating omitted items as not-presented (not-reached). Then, using data from an operational test (high-stakes, for diploma endorsement), the fit of these item estimates was assessed. In science, the fit was quite good under all conditions. In math, the fit was better for girls than for boys, the …