DETECTION OF ABERRANT ITEM SCORE PATTERNS - A REVIEW OF RECENT DEVELOPMENTS

Methods for detecting item score patterns that are unlikely, given tha t a parametric item response theory (IRT) model gives an adequate desc ription of the data or given the responses of the other persons in the group are discussed. The emphasis here is on the latter group of stat istics. These statistics can be applied when a nonparametric model is used to fit the data or when the data are described in the absence of an IRT model. After the discussion of the literature on person-fit met hods, the use of person-fit statistics in empirical data analysis is b riefly discussed.