The ASA Statement on p-Values: Context, Process, and Purpose

By R. Wasserstein, Nicole A. Lazar. 2016

5,934 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

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Citations in the corpus

Comparing Code Explanations Created by Students and Large Language Models (2023, methodology): “Following the guidelines of [45] and the broader discussion in [35], we use 𝑝 values as only one source of evidence and outline supporting statistics including two effect sizes – Rank-Biserial (RBC) Correlation [19] and Common-Language Effect Size (CLES) [28] – when presenting the results of the…”
Indices of Effect Existence and Significance in the Bayesian Framework (2019, background): “The p-value represents the probability that for a given statistical model, when the null hypothesis is true, the effect would be greater than or equal to the observed coefficient (Wasserstein and Lazar, 2016).”
A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results (2018, background): “See Wicherts et al. (2016) for an attempt to enumerate a complete list.”
Determinants of 21st-Century Skills and 21st-Century Digital Skills for Workers: A Systematic Literature Review (2020, background): “Critics call for a broader approach because p -values are commonly misused and misinterpreted (Wasserstein & Lazar, 2016).”
The natural selection of bad science (2016, background): “In March 2016, the American Statistical Association published a set of corrective guidelines about the use and misuse of p-values [2].”
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).”
A Statistical Significance Test for Necessary Condition Analysis (2020, methodology): “Just like any other statistical method that uses the p value for statistical inference, the proposed approximate permutation test has all the limitations of the p value (Wasserstein & Lazar, 2016).”
Contemporary Guidance for Stated Preference Studies (2017, background): “One comment is particularly relevant to econometric analyses of SP data: “P-values can indicate how incompatible the data are with a specified statistical model” (Wasserstein and Lazar 2016, 131).”
Transcendental values and the valuation and management of ecosystem services (2016, methodology): “Thus, to avoid Type II errors we deemed that it was more appropriate to judge the significance of changes based on effect sizes, rather than on hypothesis testing and p-values (see Wasserstein and Lazar, 2016).”
The p-Value Requires Context, Not a Threshold (2019, methodology): “This understanding expands on the ASA statement (Wasserstein and Lazar 2016), which enumerates truisms about the p-value, but does not provide guidance regarding best uses of the p-value, and provides nuance to the simple stringent threshold suggested by Benjamin et al. (2018).”