Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical–statistical controversy.

By W. Grove, P. Meehl. 1996

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Citations in the corpus

Interpretable classification models for recidivism prediction (2015, background): “Her observations are in line with longstanding work on clinical versus actuarial judgment, which shows that humans, on their own, are not as good at risk assessment as statistical tools (Dawes et al. 1989, Grove and Meehl 1996).”
Protective Factors in Forensic Mental Health: A New Frontier (2011, unknown): “The actuarial judgment method is mechanical and algorithmic (Grove & Meehl, 1996 ) and has a strong empirical basis.”
Principles of forecasting : a handbook for researchers and practitioners (2001, unknown): “Grove and Meehl (1996) completed an extensive review of the empirical evidence on econometric models and concluded that they are equal to or more accurate than unaided judgment in most settings.”
Stubborn Reliance on Intuition and Subjectivity in Employee Selection (2008, background): “The notion that analysis outperforms intuition in the prediction of human behavior is among the most well-established findings in the behavioral sciences (Grove & Meehl, 1994; Grove, Zald, Lebow, Snitz, & Nelson, 2000).2 Why, therefore, does the intuitive 2.”
Assessing the Impact of First-Time Imprisonment on Offenders’ Subsequent Criminal Career Development: A Matched Samples Comparison (2009, methodology): “Research has overwhelmingly demonstrated the superiority of actuarial methods (Grove and Meehl 1996; Aegisdottir et al. 2006; Swets et al. 2000).”
Transforming a flawed policy: A call to revive psychology and science in domestic violence research and practice (2006, background): “There is a substantial literature on the problems with clinical judgments (Grove & Meehl, 1996; Kahneman, Slovic, & Tversky, 1982), the essence of which is that actuarial judgments outperform clinical judgments consistently.”
A Classification Tree Approach to the Development of Actuarial Violence Risk Assessment Tools (2000, background): “Given the persistent finding that actuarial predictions are almost always more accurate than unstructured clinical ones (Grove & Meehl, 1996), the fact that formal violence risk assessment tools have not met with greater clinical acceptance is puzzling.”
The Superiority of Simple Alternatives to Regression for Social Science Predictions (2004, background): “Research has repeatedly demonstrated the superiority of statistical prediction rules over informal “clinical” judgment in forecasts involving human outcomes (see Grove & Meehl, 1996).”
A Comparison of Logistic Regression, Classification and Regression Tree, and Neural Networks Models in Predicting Violent Re-Offending (2011, background): “Structured risk assessment instruments are increasingly used to achieve this goal as they are considered more accurate in the prediction of future violent and sexual behavior than subjective clinical judgment (Dawes et al. 1989; Grove and Meehl 1996).”
Illusions in Regression Analysis (2012, background): “Ord (2012) deplores the fact that few regression packages aid in such analyses.”
Imprisonment and Reoffending (2009, methodology): “Research has overwhelmingly demonstrated the superiority of actuarial 142 Daniel S. Nagin, Francis T. Cullen, and Cheryl Lero Jonson methods (Grove and Meehl 1996; Swets, Dawes, and Monahan 2000; Æegisdóttir et al. 2006).”