Moving to a World Beyond “p < 0.05”

By R. Wasserstein, A. Schirm, Nicole A. Lazar. American Statistician, 2019

2,622 citations recorded by the source corpus.

Some of you exploring this special issue of The American Statistician might be wondering if it’s a scolding from pedantic statisticians lecturing you about what not to do with p-values, without offering any real ideas of what to do about the very hard problem of separating signal from noise in data and making decisions under uncertainty. Fear not. In this issue, thanks to 43 innovative and thought-provoking papers from forward-looking statisticians, help is on the way.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8dc6179861acca80fc8f76efeabbce73c81c8cfb

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Citations in the corpus

Coup de Grâce for a Tough Old Bull: “Statistically Significant” Expires (2019, positive): “We conclude, based on our review of the articles in this special issue and the broader literature, that it is time to stop using the term ‘statistically significant’ entirely” (Wasserstein et al. 2019).”
Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments (2019, methodology): “Finally, we contribute to the literature on the pitfalls of focusing on statistical significance in applied work (e.g., Brodeur et al., 2016; Wasserstein & Lazar, 2016; Amrhein et al., 2019; Wasserstein et al., 2019; Brodeur et al., 2020).”
To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation (2021, background): “Wasserstein et al. (2019) give recommendations for a better use of statistical signiﬁcance testing.”
Enhancing Rigor in Quantitative Entrepreneurship Research (2019, methodology): “When discussing the statistical significance of the hypothesis tests, the reporting of the exact p values and interpreting them in the focal context is recommended instead of focusing on some particular cut- offs (Betensky, 2019; Wasserstein et al., 2019).”
Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series (2020, background): “Although the MK test is relatively effective and robust, it still has a basic requirement that the data should be independent (Wasserstein et al., 2019).”
Microplastics Effects on Reproduction and Body Length of the Soil-Dwelling Nematode Caenorhabditis elegans (2020, background): “Following the recommendation of Wasserstein et al. (2019), we did not define a significance level and deliberately omitted the term “statistically significant.””
There are natural scores: Full comment on Shafer,"Testing by betting: A strategy for statistical and scientific communication" (2021, background): “Shafer offers a betting perspective on statistical testing which may be useful for foundational debates, given that disputes over such testing continue to be intense (e.g., see the special issues of TAS introduced by Wasserstein and Lazar 2016 and Wasserstein et al. 2019).”
The significance filter, the winner's curse and the need to shrink (2020, background): “priate amount of shrinkage can lead to misleading inferences. 1 Introduction The long-standing debate about the role of statistical signicance in research [17], [15] has recently intensied [19],[3],[20],[14],[1] and [11]. Looking back to the beginning, we nd that Ronald Fisher wrote in 1926 [6]: \Pe”