The Meta-Analysis of Clinical Judgment Project: Fifty-Six Years of Accumulated Research on Clinical Versus Statistical Prediction

By Stefanía Ægisdóttir, M. White, P. Spengler, Alan S. Maugherman, L. A. Anderson, R. S. Cook, C. N. Nichols, G. Lampropoulos, B. S. Walker, G. Cohen and 1 more. 2006

688 citations recorded by the source corpus.

Subfields: Applied Psychology, Clinical Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/0cf8ec5222307c47f94868e0c4639d0fc7b2d075

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Psychology

1. J. Bonta
2. Robert J. Williams
3. M. White
4. Demetra Andrews
5. M. Lambert
6. B. Duncan

In Clinical Psychology

1. M. Rice
2. Grant T. Harris
3. J. Bonta
4. N. Hilton
5. Demetra Andrews
6. R. Volberg
7. D. Smart
8. Kenichi Shimokawa

In Experimental and Cognitive Psychology

1. Carlos Castillo
2. M. Lambert
3. Stefanía Ægisdóttir

Citations in the corpus

• The classification accuracy of four problem gambling assessment instruments in population research (2014, background): “…advantage only manifests itself in superior diagnostic accuracy when clinicians are required to follow explicit and rigorous assessment procedures that minimize subjectivity and require attention to all relevant information (Dawes, Faust, & Meehl, 1989; Gambrill, 2006; Ægisdóttir et al., 2006).”
• Rehabilitating criminal justice policy and practice. (2010, background): “The evidence clearly shows that actuarial approaches provide better predictive accuracy than unstructured clinical judgment in general (Ægisdóttir et al., 2006; Grove, Zald, Lebow, Snitz, & Nelson, 2000) and this conclusion holds equally in the assessment of offender risk for further crime (Andrews,”
• Why Machine Learning May Lead to Unfairness: Evidence from Risk Assessment for Juvenile Justice in Catalonia (2019, background): “Moreover, meta-studies show that structured assessments outperform individual experts in the prediction of criminal behavior [1].”
• Sixty-Six Years of Research on the Clinical Versus Actuarial Prediction of Violence (2006, methodology): “Ægisdóttir et al. (2006) have cogently summarized the controversy, and a complete treatment of all objections is beyond our scope here.”
• Simple rules to guide expert classifications (2020, background): “Subsequently, large meta-analyses have consistently demonstrated that actuarial methods outperform clinical approaches, including in the context of predicting criminal activity (Ægisdóttir et al., 2006), and even for judgments by themost experienced professionals.”
• Enhancing treatment outcome of patients at risk of treatment failure: meta-analytic and mega-analytic review of a psychotherapy quality assurance system. (2010, background): “As has been repeatedly demonstrated in clinical research, any prediction relying on statistical or actuarial methods tends to fare better than clinical judgment alone (Ægisdóttir et al., 2006; Grove, 2005).”
• Algorithms in practice: Comparing web journalism and criminal justice (2017, background): “Big Data evangelists often argue that accountability is not only possible but also easier than ever to achieve through automatic and computerized procedures (see for instance Ægisdottir et al., 2006; Castro, 2016; Milgram, 2013).”
• The Meta-Analysis of Clinical Judgment Project (2009, methodology): “to calculate effect sizes, and (c) for each specialized meta-analysis, coding additional study characteristics for questions specific to that meta-analysis (e.g., clinical vs. statistical prediction; Ægisdóttir et al., 2006).”