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In defense of clinical judgment … and mechanical prediction
Author(s) -
Dana Jason,
Thomas Rick
Publication year - 2006
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.537
Subject(s) - multivariate statistics , epistemology , computer science , clinical judgment , point (geometry) , regression , psychology , artificial intelligence , data science , cognitive psychology , machine learning , mathematics , philosophy , physics , geometry , psychoanalysis , medical physics
Abstract Despite over 50 years of one‐sided research favoring formal prediction rules over human judgment, the “clinical‐statistical controversy,” as it has come to be known, remains something of a hot‐button issue. Surveying the objections to the formal approach, it seems the strongest point of disagreement is that clinical expertise can be replaced by statistics. We review and expand upon an unfortunately obscured part of Meehl's book to try to reconcile the issue. Building on Meehl, we argue that the clinician provides information that cannot be captured in, or outperformed by, mere frequency tables. However, that information is still best harnessed by a mechanical prediction rule that makes the ultimate decision. Two original studies support our arguments. The first study shows that multivariate prediction models using no data other than clinical speculations can perform well against statistical regression models. Study 2, however, showed that holistic predictions were less accurate than predictions made by mechanically combining smaller judgments without input from the judge at the combination stage. While we agree that clinical expertise cannot be replaced or neglected, we see no ethical reason to resist using explicit, mechanical rules for socially important decisions. Copyright © 2006 John Wiley & Sons, Ltd.