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)

Recently, nonparametric methods have been proposed that provide a dimensionally based description of test structure for tests with dichotomous items. Because such methods are based on different notions of dimensionality than are assumed when using a psychometric model, it remains unclear whether these procedures might lead to a different…

Empirical data analysis using the Mokken models of monotone homogeneity and double monotonicity is discussed. Results from the Mokken approach with 3 data sets (for a total of 425 elementary school students) pertaining to transitive interference items are compared to Rasch analysis. (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)