@article {40,
	title = {Bayesian identification of outliers in computerized adaptive testing},
	journal = {Journal of the American Statistical Association},
	volume = {93},
	number = {443},
	year = {1998},
	pages = {910-919},
	abstract = {We 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.},
	author = {Bradlow, E. T. and Weiss, R. E. and Cho, M.}
}
