In order to identify aberrant response-time patterns on educational and psychological tests, it is important to be able to separate the speed at which the test taker operates from the time the items require. A lognormal model for response times with this feature was used to derive a Bayesian procedure for detecting aberrant response times. Besides, a combination of the response-time model with a regular response model in an hierarchical framework was used in an alternative procedure for the detection of aberrant response times, in which collateral information on the test takers' speed is derived from their response vectors. The procedures are illustrated using a data set for the Graduate Management Admission Test[R] (GMAT[R]). In addition, a power study was conducted using simulated cheating behavior on an adaptive test.