Literature DB >> 21356064

Significance testing as perverse probabilistic reasoning.

M Brandon Westover1, Kenneth D Westover, Matt T Bianchi.   

Abstract

Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by means of a simple quiz which we administered to 246 physicians at two major academic hospitals, on which the proportion of incorrect responses exceeded 90%. A solid understanding of the fundamental concepts of probability theory is becoming essential to the rational interpretation of medical information. This essay provides a technically sound review of these concepts that is accessible to a medical audience. We also briefly review the debate in the cognitive sciences regarding physicians' aptitude for probabilistic inference.

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Year:  2011        PMID: 21356064      PMCID: PMC3058025          DOI: 10.1186/1741-7015-9-20

Source DB:  PubMed          Journal:  BMC Med        ISSN: 1741-7015            Impact factor:   8.775


  61 in total

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Journal:  Behav Brain Sci       Date:  2009-02       Impact factor: 12.579

9.  Pretest probability estimates: a pitfall to the clinical utility of evidence-based medicine?

Authors:  Molly A Phelps; M Andrew Levitt
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Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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  6 in total

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Authors:  H M Higgins; J N Huxley; W Wapenaar; M J Green
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2.  Revising the "Rule of Three" for inferring seizure freedom.

Authors:  M Brandon Westover; Justine Cormier; Matt T Bianchi; Mouhsin Shafi; Ronan Kilbride; Andrew J Cole; Sydney S Cash
Journal:  Epilepsia       Date:  2011-12-22       Impact factor: 5.864

3.  Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification.

Authors:  Igor O Korolev; Laura L Symonds; Andrea C Bozoki
Journal:  PLoS One       Date:  2016-02-22       Impact factor: 3.240

4.  Big data in sleep medicine: prospects and pitfalls in phenotyping.

Authors:  Matt T Bianchi; Kathryn Russo; Harriett Gabbidon; Tiaundra Smith; Balaji Goparaju; M Brandon Westover
Journal:  Nat Sci Sleep       Date:  2017-02-16

5.  Severely malnourished children with a low weight-for-height have a higher mortality than those with a low mid-upper-arm-circumference: I. Empirical data demonstrates Simpson's paradox.

Authors:  Emmanuel Grellety; Michael H Golden
Journal:  Nutr J       Date:  2018-09-15       Impact factor: 3.271

6.  From P-Values to Objective Probabilities in Assessing Medical Treatments.

Authors:  David Kault; Sam Kault
Journal:  PLoS One       Date:  2015-11-24       Impact factor: 3.240

  6 in total

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