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The long-standing controversy in the human counseling professions over how predictions should be made whether by clinical or statistical methods is examined in light of the emerging Bayesian orientation in statistics. The Bayesian framework yields predictions based upon a synthesis of the best features of methods often though incompatible: the judgment of the clinician and the statistician's procedures for learning from experience. The Bayesian approach with examples from the clinical-statistical literature, and a new case study demonstrates how the synthesis may be accomplished. The circumstances under which clinical and statistical methods may be difficult to synthesize is described. (15 ref.)

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Parkan and Warren [2] analyze the optimal reneging decision of a customer joining a G/M/l queue with imperfect information about parameters of the system. Their Bayesian approach to the problem is incomplete and overstates the probability that the customer will renege, which is potentially costly to the server as well as to the customer.