2022
DOI: 10.20944/preprints202112.0235.v2
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Why and How We Should Join the Shift From Significance Testing to Estimation

Abstract: A paradigm shift away from null hypothesis significance testing seems in progress. Based on simulations, we illustrate some of the underlying motivations. First, P-values vary strongly from study to study, hence dichotomous inference using significance thresholds is usually unjustified. Second, statistically significant results have overestimated effect sizes, a bias declining with increasing statistical power. Third, statistically non-significant results have underestimated effect sizes, and this bias gets st… Show more

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Cited by 5 publications
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“…But more importantly, publishing new methodologies will help accelerate research by making new tools accessible, and stimulate discussion of best practice. Our inaugural article by Berner and Amrhein (2022) is an excellent example of the latter, arguing in favour of parameter estimation as opposed to hypothesis testing in statistical analysis.…”
mentioning
confidence: 99%
“…But more importantly, publishing new methodologies will help accelerate research by making new tools accessible, and stimulate discussion of best practice. Our inaugural article by Berner and Amrhein (2022) is an excellent example of the latter, arguing in favour of parameter estimation as opposed to hypothesis testing in statistical analysis.…”
mentioning
confidence: 99%