5 ways statistics can fool you-Tips for practicing clinicians

Colin P. West; Denise M. Dupras

doi:10.1016/j.vaccine.2012.11.086

5 ways statistics can fool you-Tips for practicing clinicians

Colin P. West, Denise M. Dupras

Research output: Contribution to journal › Comment/debate › peer-review

5 Scopus citations

Abstract

Published literature suggests that many clinicians are not fully equipped to evaluate and apply researchreports for the care of their patients. In this article, we introduce and illustrate five basic statistical conceptsthat can significantly impact the interpretation of the medical literature and its application to thecare of patients, drawing examples from the vaccine literature: (i) consider clinical and statistical significanceseparately, (ii) evaluate absolute risks rather than relative risks, (iii) examine confidence intervalsrather than p values, (iv) use caution when considering isolated significant p values in the setting ofmultiple testing, and (v) keep in mind that statistically nonsignificant results may not exclude clinicallyimportant benefits or harms. These tips may help busy clinicians better interpret the increasinglyoverwhelming amount of medical literature they are faced with in their daily practices.

Original language	English (US)
Pages (from-to)	1550-1552
Number of pages	3
Journal	Vaccine
Volume	31
Issue number	12
DOIs	https://doi.org/10.1016/j.vaccine.2012.11.086
State	Published - Mar 15 2013

ASJC Scopus subject areas

Molecular Medicine
Immunology and Microbiology(all)
veterinary(all)
Public Health, Environmental and Occupational Health
Infectious Diseases

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abstract = "Published literature suggests that many clinicians are not fully equipped to evaluate and apply researchreports for the care of their patients. In this article, we introduce and illustrate five basic statistical conceptsthat can significantly impact the interpretation of the medical literature and its application to thecare of patients, drawing examples from the vaccine literature: (i) consider clinical and statistical significanceseparately, (ii) evaluate absolute risks rather than relative risks, (iii) examine confidence intervalsrather than p values, (iv) use caution when considering isolated significant p values in the setting ofmultiple testing, and (v) keep in mind that statistically nonsignificant results may not exclude clinicallyimportant benefits or harms. These tips may help busy clinicians better interpret the increasinglyoverwhelming amount of medical literature they are faced with in their daily practices.",

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5 ways statistics can fool you-Tips for practicing clinicians

Abstract

ASJC Scopus subject areas

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