Statistical Guidance to Authors at Top-Ranked Journals across Scientific Disciplines

Abstract Scientific journals may counter the misuse, misreporting, and misinterpretation of statistics by providing guidance to authors. We described the nature and prevalence of statistical guidance at 15 journals (top-ranked by Impact Factor) in each of 22 scientific disciplines across five high-level domains (N = 330 journals). The frequency of statistical guidance varied across domains (Health & Life Sciences: 122/165 journals, 74%; Multidisciplinary: 9/15 journals, 60%; Social Sciences: 8/30 journals, 27%; Physical Sciences: 21/90 journals, 23%; Formal Sciences: 0/30 journals, 0%). In one discipline (Clinical Medicine), statistical guidance was provided by all examined journals and in two disciplines (Mathematics and Computer Science) no examined journals provided statistical guidance. Of the 160 journals providing statistical guidance, 93 had a dedicated statistics section in their author instructions. The most frequently mentioned topics were confidence intervals (90 journals) and p-values (88 journals). For six “hotly debated” topics (statistical significance, p-values, Bayesian statistics, effect sizes, confidence intervals, and sample size planning/justification) journals typically offered implicit or explicit endorsement and rarely provided opposition. The heterogeneity of statistical guidance provided by top-ranked journals within and between disciplines highlights a need for further research and debate about the role journals can play in improving statistical practice.