Year: 2016
Type: article
Abstract: Mathematics and statistical analyses contribute to the language of science and to every scientific discipline.Clinical trials and epidemiologic studies published in biomedical journals are essentially exercises in mathematic al measurement.1 With the extensive contribution of statisticians to the methodological development of clinical trials and epidemiologic theory, it is not surprising that many statistical concepts have dominated scientific inferential processes, especially in research investigating biomedical cause-and-effect relations.[1][2][3][4][5][6] For example, the comparative point estimate of a risk factor (eg, a risk ratio) is used to mathematically express the strength of the association between the presumed exposure and the outcome of interest.[7][8][9] Mathematics is also used to express random variation inherent around the point estimate as a range that is termed a confidence interval.1 However, despite the greater degree of information provided by point estimates and confidence intervals, the statistic most frequently used in biomedical research for conveying association is the P value.[10][11][12][13][14] In this issue of JAMA, Chavalarias et al 15 describe the evolution of P values reported in biomedical literature over the last 25 years.Based on automated text mining of more than 12 million MEDLINE abstracts and more than 800 000 abstracts and full-text articles in PubMed Central, the authors found that a greater percentage of scientific articles reported P values in the presentation of study findings over time, with the prevalence of P values in abstracts increasing from 7.3% in 1990 to 15.6% in 2014.Among the abstracts and full-text articles with P values, 96% reported at least 1 "statistically significant" result, with strong clustering of reported P values around .05 and .001.In addition, in an in-depth manual review of 796 abstracts and 99 full-text articles from articles reporting empirical data, the authors found that P values were reported in 15.7% and 55%, respectively, whereas confidence intervals were reported in only 2.3% of abstracts and were included for all reported effect sizes in only 4% of the full-text articles.The authors suggested that rather than reporting isolated P values, research articles should focus more on reporting effect sizes (eg, absolute and relative risks) and uncertainty metrics (eg, confidence intervals for the effect estimates).To provide context for the increasing reporting of P values in the biomedical literature over the past 25 years, it is important to consider what a P value really is, some examples of its frequent misconceptions and inappropriate
Source: JAMA
Author: Demetrios N. Kyriacou
Institution: Northwestern University
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W2297448524