Statistics Myth Busters: Dispelling Common Misperceptions Held by Readers of the Biomedical Literature

Proficiency in research design and statistical analysis is crucial to the success of a clinical pharmacist. However, new pharmacy graduates and residents may not have received adequate training and education in these areas. During the authors' tenure as clinical pharmacists, several statistical "myths" were consistently maintained by residents and new clinical practitioners. The purpose of this narrative review is to discuss and dispel several of these statistical fallacies. The myths discussed involve 3 common areas of consideration when evaluating any clinical study: assessing the risk of bias from confounding (propensity score analysis and multivariable modeling), interpretation of the main study findings ( P values and hypothesis testing), and secondary evaluations (subgroup analyses). Literature examples are used to illustrate each of the topics. The authors hope that the discussion will augment each pharmacist's knowledge of medical literature interpretation leading to improvements in patient care, education of future residents, and personal research endeavors.