This special issue is devoted to person-fit analysis, which is also referred to as appropriateness measurement. An introduction to person-fit research is given. Several types of aberrant response behavior on a test are discussed; and whether person-fit statistics can be used to detect dominant score patterns is explored. (SLD)

Methods for detecting item score patterns that are unlikely, given that a parametric item response theory model gives an adequate description of the data or given the responses of other persons in the group, are discussed. The use of person-fit statistics in empirical data analysis is briefly discussed. (SLD)

Several existing group-based statistics to detect improbable item score patterns are discussed, along with the cut scores proposed in the literature to classify an item score pattern as aberrant. A simulation study and an empirical study are used to compare the statistics and their use and to investigate the practical use of cut scores. (SLD)