Larisa N Soldatova, Andrey Rzhetsky, Kurt De Grave, Ross D King
Representation of probabilistic scientific knowledge
Journal of biomedical semantics
well known statistical analyses healthscience medical journals frequently misleading even wrong despite many decades reform efforts hundreds scientists statisticians attempts fix problem avoiding obvious error encouraging good practice altered basic situation statistical teaching reporting remain mired damaging yet editorially enforced jargon significance confidence imbalanced focus null noeffect nil hypotheses leading flawed attempts simplify descriptions results ordinary terms positive development amidst introduction interval estimates alongside place significance tests pvalues intervals beset similar misinterpretations attempts remedy situation calling replacement traditional statistics competitors purelikelihood bayesian methods little impact thus rather ban replace pvalues confidence intervals propose replace traditional jargon accurate modest ordinarylanguage labels describe statistics measures compatibility data hypotheses models long use statistical modeling literature descriptions emphasize full range possibilities compatible observations additionally simple transform pvalue called surprisal svalue provides sense much little information data supply possibilities illustrate reforms using examples highly charged topic trials ivermectin treatment covid19