01292nas a2200145   4500008004100000245007300041210006900114300001200183490000700195520080400202100001701006700001501023700001101038856009701049       1998                        eng d00aBayesian identification of outliers in computerized adaptive testing0 aBayesian identification of outliers in computerized adaptive tes  a910-9190 v933 aWe consider the problem of identifying examinees with aberrant response patterns in a computerized adaptive test (CAT). The vec-tor of responses yi of person i from the CAT comprise a multivariate response vector. Multivariate observations may be outlying in manydi erent directions and we characterize speci c directions as corre- sponding to outliers with different interpretations. We develop a class of outlier statistics to identify different types of outliers based on a con-trol chart type methodology. The outlier methodology is adaptable to general longitudinal discrete data structures. We consider several procedures to judge how extreme a particular outlier is. Data from the National Council Licensure EXamination (NCLEX) motivates our development and is used to illustrate the results.1 aBradlow, E T1 aWeiss, R E1 aCho, M  uhttp://mail.iacat.org/content/bayesian-identification-outliers-computerized-adaptive-testing