title: Frequent mistakes in the statistical inference of biomedical data.
abstract: Although there is a plethora of books, reviews and articles defining the meaning of the p value, many investigators make errors when reaching conclusions from their work based on this p value. Most report their data using rigid sentences such as "the results are not statistically significant, p > 0.05", frequently misunderstood by the authors and the readers. Many professionals are not aware of their limitations in this field rendering the problem even more complicated. In this article we include advice from experts against mistakes frequently made by investigators, such as the plea made by Rothman that a correct interpretation of the data should not be replaced by sentences such as "statistically significant" or "statistically non-significant". Detailed comments on the more frequent mistakes as well as the reasons for their appearance and persistence during the decades are presented. Finally, a comprehensive explanation of the p value is included, to emphasize that to avoid these mistakes there is no need to learn the mathematical basis of tests but that logic alone would suffice.
authors.affiliation: Cardiology Department, Hospital Universitario Gregorio Marañón, Madrid, Spain. mmselles@navegalia.com
authors.forename: Manuel
authors.initials: M
authors.lastname: Martínez-Sellés
authors.forename: Luis
authors.initials: L
authors.lastname: Prieto
authors.forename: Inmaculada
authors.initials: I
authors.lastname: Herranz
mesh_terms: D035843:Biomedical Research / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D011336:Probability