Our website is made possible by displaying online advertisements to our visitors.
Please consider supporting us by disabling your ad blocker.

Responsive image


Draft:Clinical Versus Statistical Prediction


Clinical and statistical prediction are two distinct methods used to combine information for decision-making across various domains.[1][2] These approaches are employed when multiple data points need to be integrated to make informed decisions. For instance, a medical professional combining symptom data, test results, and patient history to reach a diagnosis. Clinical prediction relies on human judgment to combine this information, whereas statistical prediction utilizes mathematical models and algorithms to do so. While early work on clinical prediction focused on mental health decisions, its application extends to other areas, including in the prediction of criminal recidivism,[3] marital satisfaction, business failures, and magazine advertising sales.[4]

  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. ^ Wormith, J. S., Hogg, S., & Guzzo, L. (2012). The Predictive Validity of a General Risk/Needs Assessment Inventory on Sexual Offender Recidivism and an Exploration of the Professional Override. Criminal Justice and Behavior, 39(12), 1511–1538. https://doi.org/10.1177/0093854812455741
  4. ^ Grove, W. M., Zald, D. H., Lebow, B. S., Snitz, B. E., & Nelson, C. (2000). Clinical versus mechanical prediction: A meta-analysis. Psychological Assessment, 12(1), 19–30. https://doi.org/10.1037/1040-3590.12.1.19

Previous Page Next Page








Responsive image

Responsive image