We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs…

When cut scores for classifications occur on the total score scale, popular methods for estimating classification accuracy (CA) and classification consistency (CC) require assumptions about a parametric form of the test scores or about a parametric response model, such as item response theory (IRT). This article develops an approach to estimate CA…

A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…

This study compared the classification performance among parametric discriminant analysis, nonparametric discriminant analysis, and logistic regression in a two-group classification application. Field data from an organizational survey were analyzed and bootstrapped for additional exploration. The data were observed to depart from multivariate…

H. H. Chang and W. F. Stout (1993) presented a derivation of the asymptotic posterior normality of the latent trait given examinee responses under nonrestrictive nonparametric assumptions for dichotomous item response (IRT) theory models. This paper presents an extension of their results to polytomous IRT models and defines a global information…

A study of the ability of different models--including the classification techniques of discriminant analysis, logistic regression, and neural networks--to predict the academic success of master's degree students in business administration suggests that prediction is difficult, but that classification and nonparametric techniques may be…

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)

In person-fit analysis, the object is to investigate whether an item score pattern is improbable given the item score patterns of the other persons in the group or given what is expected on the basis of a test model. In this study, several existing group-based statistics to detect such improbable score patterns were investigated, along with the…

Research studies using booklet classification were implemented by the American College Testing Program to investigate the linkage between the National Assessment of Educational Progress (NAEP) Achievement Levels Descriptions and the cutpoints set to represent student performance with respect to the achievement levels. This paper describes the…