5 ways statistics can fool you—Tips for practicing clinicians

Published literature suggests that many clinicians are not fully equipped to evaluate and apply research reports for the care of their patients. In this article, we introduce and illustrate five basic statistical concepts that can significantly impact the interpretation of the medical literature and its application to the care of patients, drawing examples from the vaccine literature: (i) consider clinical and statistical significance separately, (ii) evaluate absolute risks rather than relative risks, (iii) examine confidence intervals rather than p values, (iv) use caution when considering isolated significant p values in the setting of multiple testing, and (v) keep in mind that statistically nonsignificant results may not exclude clinically important benefits or harms. These tips may help busy clinicians better interpret the increasingly overwhelming amount of medical literature they are faced with in their daily practices. ⺠Consider clinical and statistical significance separately. ⺠Evaluate absolute risks rather than relative risks. ⺠Examine confidence intervals rather than p values. ⺠Use caution when considering isolated significant p values in the setting of multiple testing. ⺠Keep in mind that statistically nonsignificant results may not exclude clinically important benefits or harms.