Draft:Clinical Versus Statistical Prediction


Clinical and statistical prediction are two distinct methods used to integrate multiple data points for decision-making across various domains.[1][2] Clinical prediction relies on human judgment, expertise, and experience to mentally integrate information, while statistical prediction employs mathematical formulas, algorithms, or models to systematically combine quantitative data. These approaches emerged as formal concepts in the mid-20th century, though their underlying principles have been practiced much longer.

These prediction methods have applications across fields including medicine, psychology, criminal justice, business forecasting, personnel selection, and education. In practice, clinical prediction remains the dominant approach in most of these fields. For example, clinicians typically rely on their professional judgment when combining symptom data, test results, and patient history to reach diagnoses or treatment decisions, rather than using statistical formulas. Similarly, in criminal justice, while statistical tools exist for assessing recidivism risk, many consequential decisions about sentencing and parole continue to be made primarily through clinical judgment.

The comparative accuracy of these approaches has been extensively studied since the 1950s, with Paul Meehl's 1954 publication "Clinical versus Statistical Prediction" serving as a landmark contribution to this field.[3][4] Meta-analyses have consistently demonstrated that statistical methods typically match or exceed the accuracy of clinical prediction.[5]

Multiple studies have shown that even simple statistical models with equally weighted or randomly weighted variables often outperform expert clinical judgment in specific predictive tasks.[6][7] Despite this substantial body of evidence supporting the efficacy of statistical approaches, clinical prediction continues to dominate professional practice in many fields.

  1. ^ Grove, W. M., & Lloyd, M. (2006). Meehl’s contribution to clinical versus statistical prediction. Journal of Abnormal Psychology, 115(2), 192–194. https://doi.org/10.1037/0021-843X.115.2.192
  2. ^ Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
  3. ^ Kahneman, D., Sibony, O., & Sunstein, C. R. (2021). Noise: A Flaw in Human Judgment. William Collins.
  4. ^ L.A. Times Archives. (2003, February 20). Paul E. Meehl, 83; Psychologist Linked Schizophrenia to Genes. Los Angeles Times. https://www.latimes.com/archives/la-xpm-2003-feb-20-me-meehl20-story.html
  5. ^ Kahneman, D., Sibony, O., & Sunstein, C. R. (2021). Noise: A Flaw in Human Judgment. William Collins.
  6. ^ Kahneman, D., Sibony, O., & Sunstein, C. R. (2021). Noise: A Flaw in Human Judgment. William Collins.
  7. ^ Camerer, C. F., & Johnson, E. J. (1991). The process-performance paradox in expert judgment: How can experts know so much and predict so badly? In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 195–217). Cambridge University Press.

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