Person-fit Analysis

Person-fit analysis is a technique for determining if the person's results on a given test are valid.

The purpose of a person-fit analysis is to detect item-score vectors that are unlikely given a hypothesized test theory model such as item response theory, or unlikely compared with the majority of item-score vectors in the sample. An item-score vector is a list of "scores" that a person gets on the items of a test, where "1" is often correct and "0" is incorrect. For example, if a person took a 10-item quiz and only got the first five correct, the vector would be {1111100000}.

In individual decision-making in education, psychology, and personnel selection, it is critically important that test users can have confidence in the test scores used. The validity of individual test scores may be threatened when the examinee's answers are governed by factors other than the psychological trait of interest - factors that can range from something as benign as the examinee dozing off to concerted fraud efforts. Person-fit methods are used to detect item-score vectors where such external factors may be relevant, and as a result, indicate invalid measurement.

Unfortunately, person-fit statistics only tell if the set of responses is likely or unlikely, and cannot prove anything. The results of the analysis might look like an examinee cheated, but there is no way to go back to when the test was administered and prove it. This limits its practical applicability on an individual scale. However, it might be useful on a larger scale; if most examinees at a certain test site or with a certain proctor have unlikely responses, an investigation might be warranted.