The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index; none of the 1 sources its claims cite is checked for support yet.
The ASA Statement on p -Values: Context, Process, and Purpose
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24 Own interpretation · 2 No basis given · 1 No full text of the sources
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The widespread use of”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Statistical significance is not equivalent to scientific, human, or economic significance.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, a p-value near 0.05 taken by itself offers only weak evidence against the null hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, identical estimated effects will have different p-values if the precision of the estimates differs.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A p-value provides one approach to summarizing the incompatibility between a particular set of data and a proposed model for the data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Conducting multiple analyses of the data and reporting only those with certain p-values (typically those passing a significance threshold) renders the reported p-values essentially uninterpretable.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Whenever a researcher chooses what to present based on statistical results, valid interpretation of those results is severely compromised if the reader is not informed of the choice and its basis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The smaller the p-value, the greater the statistical incompatibility of the data with the null hypothesis, if the underlying assumptions used to calculate the p-value hold.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Valid scientific conclusions based on p-values and related statistics cannot be drawn without at least knowing how many and which analyses were conducted, and how those analyses (including p-values) were selected for reporting.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 10
- It may state two separate claims as one. 10
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This has led to some scientific journals discouraging the use of p-values, and some scientists and statisticians recommending their abandonment, with some arguments essentially unchanged since p-values were first introduced.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The statistical community has been deeply concerned about issues of reproducibility and replicability of scientific conclusions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While the p-value can be a useful statistical measure, it is commonly misused and misinterpreted.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A conclusion does not immediately become”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All these measures and approaches rely on further assumptions, but they may more directly address the size of an effect (and its associated uncertainty) or whether the hypothesis is correct.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The validity of scientific conclusions, including their reproducibility, depends on more than the statistical methods themselves.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is a statement about data in relation to a specified hypothetical explanation, and is not a statement about the explanation itself.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Researchers should recognize that a p-value without context or other evidence provides limited information.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Likewise, a relatively large p-value does not imply evidence in favor of the null hypothesis; many other hypotheses may be equally or more consistent with the observed data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This incompatibility can be interpreted as casting doubt on or providing evidence against the null hypothesis or the underlying assumptions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Appropriately chosen techniques, properly conducted analyses and correct interpretation of statistical results also play a key role in ensuring that conclusions are sound and that uncertainty surrounding them is represented properly.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Misunderstanding or misuse of statistical inference is only one cause of the”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
What the sources say
- Not checked — no full text of the sourcecites Peng 2015 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Smaller p-values do not necessarily imply the presence of larger or more important effects, and larger p-values do not imply a lack of importance or even lack of effect.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In view of the prevalent misuses of and misconceptions concerning p-values, some statisticians prefer to supplement or even replace p-values with other approaches.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
There is widespread consensus in the statistical community on the principles articulated in the ASA statement.
“according to widespread consensus in the statistical community”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While the large scale of the Tabula Muris Senis dataset provides substantial power to predict subtle changes in LR interactions, the biological complexity, dependencies among communication pairs, and multiple testing burden require that these p-values be interpreted within a broader biological and statistical context [33].”
From Quantitative profiling of lifespan-dependent cell-cell communication potential reveals dynamic ligand-receptor network shifts across mouse tissues (2026) · cites this paper as [33]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These types of incorrect descriptions contribute to confirmation bias, overinterpretation of results, and reporting correlation as implied causation (Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“This is especially true of relatively large-sample-size studies (as most learning analytics studies are), which are likely to obtain statistically significant findings in relatively small variations in measures such as GPA (Field 2017; Salkind 2016 Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
In the citing paper
“In 2016, the American Statistical Association released a statement on statistical significance and the P value with six principles underlying the proper use and interpretation of this statistical tool (77).”
From Misrepresentation and distortion of research in biomedical literature (2018) · cites this paper as [77]
In the citing paper
“Although we also present p values for exploratory analyses, we refrain from labeling any of them as statistically significant, following best-practice recommendations for statistical analysis [43].”
From Comparing quality of reporting between preprints and peer-reviewed articles in the biomedical literature (2020) · cites this paper as [43]
In the citing paper
“Contrary to IJE author recommendations and recent guidance from the American Statistics Society, 16 Gao et al. largely base their conclusions on findings with a P -value equivalent to < 0.05 after multiple testing.”
From Commentary: Two-sample Mendelian randomization: opportunities and challenges (2016) · cites this paper as [16]
In the citing paper
“Following guidance,50 we focused on 95% CIs, rather than statistical significance. For example, unlike conventional interpretations, we did not outright interpret an effect estimate “non‐significant” if the lower or upper bound of the 95% CI was slightly above/below the null value; we interpreted them as “suggestive” of an effect.”
From Third‐wave cognitive behaviour therapies for weight management: A systematic review and network meta‐analysis (2020) · cites this paper as [50]
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“Statisticians and others have been sounding the alarm about these matters for decades, to little avail” [29].”
Background‘The effect is/isn’t significant!’: statistical evidence and ELT
Koval, N. G. (2023) · ELT Journal · doi:10.1093/elt/ccad028 · Cited by 2
Sedgwick, P. M. (2023) · Springer eBooks · doi:10.1007/978-3-031-26010-0_4 · Cited by 2
Evaluation of the ASTM E900 ΔT41J Prediction Equation in Light of New Data
Kirk, M. T., Ferreño, D., & Sainz-Aja, J. A. (2023) · doi:10.1520/stp164720220063 · Cited by 2
If unequal, don’t change it? The inequality-redistribution puzzle among political elites
Romo, C. M., & Marcos-Marné, H. (2023) · Current Sociology · doi:10.1177/00113921231186447 · Cited by 2
Beyond the null hypothesis: Physics-driven searches for astrophysical neutrino sources
Capel, F., Kuhlmann, J., Haack, C., Minh, M. H., Niederhausen, H., & Schumacher, L. J. (2023) · International Cosmic Ray Conference · doi:10.22323/1.444.1576 · Cited by 2
Cui, N., Gan, X., Huang, S., Chu, Z., Chen, D., Zhang, Y., Lan, M., & Jin, J. (2023) · Nursing in Critical Care · doi:10.1111/nicc.12955 · Cited by 2
From fact to fake: The importance of being significant
Hassler, U. (2023) · Research in Statistics · doi:10.1080/27684520.2023.2236995 · Cited by 2
Probability Models in Statistical Data Analysis: Uses, Interpretations, Frequentism-as-Model
Hennig, C. M. (2023) · Springer eBooks · doi:10.1007/978-3-030-19071-2_105-1 · Cited by 5
“The centrality of the concept of compatibility can be seen in the 2016 ASA (American Statistical Association) Statement on p-values (Wasserstein and Lazar (2016)), which has a single positive message on p-values, besides a number of negative ones:”
BackgroundSetting Statistical Hurdles for Publishing in Accounting
Teoh, S. H., & Zhang, Y. (2023) · Accounting Economics and Law - A Convivium · doi:10.1515/ael-2022-0104 · Cited by 2
An Exploratory Study of Mindsets, Sense of Belonging, and Help-Seeking in the Writing Center
Freeman, T., & Getty, S. (2024) · The Writing center journal · doi:10.7771/2832-9414.1935 · Cited by 2
A Sentiment Analysis Benchmark for Automated Machine Learning Applications
Silva, M. C. R., de Oliveira, V. A., & Pardo, T. A. S. (2023) · International Conference on Machine Learning and Applications · doi:10.1109/icmla58977.2023.00224 · Cited by 3
“[75] reinforces that it is necessary to be cautious when handling hypothesis testing approaches such as p-value.”
Toward Patient-Centered Drug Approval for Treatment of Rare Diseases
Manski, C. F. (2024) · Value in Health · doi:10.1016/j.jval.2024.03.009 · Cited by 2
Reviewing research reporting in randomised controlled trials: Confidence and P-values
Ganesh, V., & Sahni, N. (2024) · Indian Journal of Anaesthesia · doi:10.4103/ija.ija_189_24 · Cited by 2
“[19] A few editorials have explained the same, which has also made its way into current major textbooks.”
BackgroundPatterns of avian tree usage in the primeval temperate forests of Białowieża National Park
Karpińska, O., Kamionka‐Kanclerska, K., Czortek, P., et al. (2024) · Ecology and Evolution · doi:10.1002/ece3.11138 · Cited by 2
“…we did not account for p-values as a tool for assessment of the significance of results, as a strong sample-size dependency of p-values may generate a risk of treating biologically interpretable patterns as statistically not significant (Nakagawa & Cuthill, 2007; Wasserstein & Lazar, 2016).”
MethodTurner, C. G., Hayat, M. J., Otis, J. S., Quyyumi, A. A., & Wong, B. J. (2024) · Physiological Reports · doi:10.14814/phy2.16149 · Cited by 2
“…do not provide information about the magnitude of observed differences and accepted statistical guidelines are to not report p values in isolation (Wasserstein & Lazar, 2016), data are presented as mean ± SD with 95% confidence interval of the difference (95% CI; lower limit, upper limit) and…”
BackgroundQuatto, P., Ripamonti, E., & Marasini, D. (2024) · Pharmaceutical Statistics · doi:10.1002/pst.2452 · Cited by 2
MAGNETIC BACTERIA AND THEIR POTENTIAL APPLICATIONS: A REVIEW ARTICLE
Eljmeli, S. R., Alshikhi, S. A., Alkreem, N. M. A., et al. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201701.108-122 · Cited by 2
Nakaguchi, T., ISHIMOTO, T., & Akazawa, N. (2018) · Rigakuryoho Kagaku · doi:10.1589/rika.33.235 · Cited by 2
Probiotics and Evidence-based Medicine
Koch, M. (2018) · Journal of Clinical Gastroenterology · doi:10.1097/mcg.0000000000001106 · Cited by 2
Research integrity and the law that never was
Mayer, M. G. (2018) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2018-110993 · Cited by 2
Smaller clinical trials for decision making; a case study to show p-values are costly
Graves, N., Barnett, A., Burn, E., & Cook, D. (2018) · F1000Research · doi:10.12688/f1000research.15522.2 · Cited by 6
Is this the End of “Statistical Significance”?
Tarran, B. (2019) · Significance · doi:10.1111/j.1740-9713.2019.01244.x · Cited by 2
Camacho, G. B. (2019) · Estudios Demográficos y Urbanos · doi:10.24201/edu.v34i2.1636 · Cited by 2
Meditation in cardiac rehabilitation: Should we be thinking about it?
Gibbons, R. J., & Thomas, R. J. (2019) · Journal of Nuclear Cardiology · doi:10.1007/s12350-019-01920-8 · Cited by 2
“’’ The reference supplied in the text(7) supporting this approach is not a guideline; it is a commentary by two authors on a separate publication from the American Statistical Association (ASA).(8) The commentary has a brief section on ‘‘P values and small sample sizes’’ which states ‘‘depending on how small the study…”
BackgroundSusarla, S. M., Dodson, T. B., & Cheng, K. L. (2020) · Journal of Oral and Maxillofacial Surgery · doi:10.1016/j.joms.2019.12.031 · Cited by 2
Methodological Advances in Motor Learning and Development
Lohse, K. R. (2020) · Journal of Motor Learning and Development · doi:10.1123/jmld.2019-0054 · Cited by 2
When “facts” are not facts: what does p value really mean, and how does it deceive us?
Liao, C., Speirs, A. L., Goldsmith, S., et al. (2020) · Journal of Assisted Reproduction and Genetics · doi:10.1007/s10815-020-01751-4 · Cited by 2
Riddle, D. L., & Perera, R. A. (2020) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2020-217526 · Cited by 2
Tiwari, J., Yu, B., Fentie, B., et al. (2020) · The Rangeland Journal · doi:10.1071/rj19082 · Cited by 2
Leukel, J., Schehl, B., & Sugumaran, V. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-50232-4_18 · Cited by 3
Vorland, C. J., Kyle, T. K., & Brown, A. W. (2020) · Nutrients · doi:10.3390/nu12082335 · Cited by 2
Unlucky Number 13? Manipulating Evidence Subject to Snooping
Hassler, U., & Pohle, M. (2022) · International Statistical Review · doi:10.1111/insr.12488 · Cited by 4
“l hypothesis, see again the maximum p-value in Table 1. Except for THARKing, all these strategies are forms of MESSing. To avoid the negative eects of SHARKing or p-hacking or of MESSing in general, Wasserstein and Lazar (2016, p. 132) demanded more transparency from scientic authors: \Researchers should disclose the…”
BackgroundInfluentialINNOVATIVE MAINTENANCE AND FEEDING OF WEANING PIGLETS BASED ON NEW TECHNICAL MEANS
Morozov, N. M., Tsoy, L. M., & Rasskazov, A. N. (2020) · INMATEH Agricultural Engineering · doi:10.35633/inmateh-62-05 · Cited by 2
Bateson, A. G., & Dardick, W. R. (2020) · Personnel Assessment and Decisions · doi:10.25035/pad.2020.03.005 · Cited by 2
“Both p-values (point estimates) and confidence intervals (interval estimates) add to the body of evidence regarding the research findings and have been provided for all comparisons (Greenland et al., 2016; Wasserstein & Lazar, 2016).”
Is 3 Feet of Physical Distancing Enough?
Harris, D. A., Sobers, M., Greenwald, Z. R., et al. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciab439 · Cited by 2
“Dichotomizing findings in terms of statistical significance discards valuable information regarding the magnitude and importance of the observed effect [4, 5].”
BackgroundPathak, N. (2021) · Journal of Ayurveda and Integrative Medicine · doi:10.1016/j.jaim.2021.06.008 · Cited by 2
Yuzurihara, H., Mano, S., & Tagoshi, H. (2021) · Progress of Theoretical and Experimental Physics · doi:10.1093/ptep/ptab137 · Cited by 2
“In the recent American statistical association statement on p-values [24], the first principle is “P -values can indicate how incompatible the data are with a specified statistical model”.”
BackgroundBiomedical research at the crossroads and ways through
Pons, J. M. V., & Adam, P. (2018) · Medicina Clínica (English Edition) · doi:10.1016/j.medcle.2018.05.036 · Cited by 2
Estimating sample sizes for evidentialttests
Cahusac, P., & Mansour, S. E. (2022) · Research in Mathematics · doi:10.1080/27684830.2022.2089373 · Cited by 2
Witchel, H. J., Guy, R., Torrens, C., Langlands, K., & Doggrell, S. A. (2022) · Methods in physiology · doi:10.1007/978-3-030-95633-2_12 · Cited by 2
Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors
Fay, M. P., Proschan, M. A., Brittain, E., & Tiwari, R. C. (2022) · Statistical Science · doi:10.1214/21-sts833 · Cited by 2
“This paper will not cover the debate about the proper use of p-values and possible replacements for them (see e.g., Wasserstein & Lazar (2016) and Wasserstein et al. (2019)).”
BackgroundBoelaert, J., & Ollion, É. (2018) · Revue Française de Sociologie · doi:10.3917/e.rfs.593.0475 · Cited by 61
Stock returns and investors' mood: Good day sunshine or spurious correlation?Preprint
Kim, J. H. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2764029 · Cited by 25
“Note that the American Statistical Association (Wasserstein & Lazar, 2016) recently issued a statement expressing grave concerns that improper use of the p-value criterion is distorting the scientific process and invalidating many scientific conclusions.”
Tressoldi, P. E., Pederzoli, L., Matteoli, M., et al. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2654264 · Cited by 2
A framework for philosophical biologyPreprint
Ehsani, S. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.00033 · Cited by 3
“What exactly is uncertainty, and is it possible to postulate theories that go beyond a statistical description of uncertainty? For example, the American Statistical Association has recently emphasized that a p-value is “a statement about data in relation to a specified hypothetical explanation, and is not a statement…”
BackgroundValidating Methods that Promote Reduction and Refinement in Laboratory Animal Science
WALKER, M. D. (2016) · The Atrium (University of Guelph) · Cited by 2
Hoenig, J. M. (2016) · UA Campus Repository (The University of Arizona) · Cited by 2
A Practical Guide to Translating Nanomedical Products
Bawa, R. (2016) · Wiley eBooks · doi:10.1002/9783527800681.ch28 · Cited by 3
Kim, J. H., & Shamsuddin, A. F. M. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2851370 · Cited by 2
Does democracy cause growth? A meta-analysis perspectivePreprint
Colagrossi, M., Rossignoli, D., & Maggioni, M. A. (2017) · RePEc: Research Papers in Economics · doi:10.13140/rg.2.2.35700.86403 · Cited by 2
Arnold, N. W. (2018) · Wiley eBooks · doi:10.1002/9781119128304.ch24 · Cited by 2
Tackling False Positives in Finance: A Statistical Toolbox With ApplicationsPreprint
Kim, J. H. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3192611 · Cited by 2
Reply to the comment on: “Reporting matters: Brain mapping with transcranial magnetic stimulation”
Massé‐Alarie, H., Bergin, M., Schneider, C., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24471 · Cited by 2
“…our study (as recommended by the “Guideline for reporting statistics” [CurranEverett & Benos, 2004]) and using terms as statistically and non-statistically significant as suggested by a statement released by American Statistical Association (AMA) on the use of p-values (Wasserstein & Lazar, 2016).”
MethodPerepelkin, E. E., Sadovnikov, B. I., Иноземцева, Н. Г., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.09424 · Cited by 2
Visual Entropy and the Visualization of UncertaintyPreprint
Holliman, N. S., Çöltekin, A., Fernstad, S. J., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.12879 · Cited by 2
“For researchers there already exists in-depth advice on the use and presentation of p-values, and other uncertainty measures, from professional bodies [20] and practical guidance on how to design experiments that severely test hypotheses [19].”
BackgroundA reckless guide to P-values: local evidence, global errors
Lew, M. J. (2019) · arXiv · doi:10.48550/arxiv.1910.02042 · Cited by 2
“In response to the widespread expressions of concern over the misuse and misunderstanding of P-values, the ASA convened a group of experts to consider the issues and to collaborate on drafting an official statement on P-values [Wasserstein and Lazar, 2016].”
BackgroundMethodInfluentialMendrik, A. M., & Aylward, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.08531 · Cited by 6
“The widespread misinterpretation of statistical significance as a measure of practical significance or generalization has prompted statistical journals to discourage the use of tests of statistical significance [52].”
BackgroundCommentary: Let's not trade one problem for another: Moving beyond P values and confidence intervals
Tam, D. Y., & Fremes, S. E. (2020) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2020.04.159 · Cited by 2
P-Values in a Post-Truth WorldPreprint
Vogelstein, J. T. (2020) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/yw6sr · Cited by 2
“In particular, ASA released a statement in 2016 discussing the perils of p-values [15] (which we refer to hereafter as ASA I, following Deborah Mayo’s convention [16].”
BackgroundKim, J. H., Megquier, K., Thomas, R. J., Sarver, A. L., Song, J. M., Kim, Y. T., Cheng, N., Schulte, A. J., Linden, M. A., Murugan, P., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.11.246777 · Cited by 7
Suzuki, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.07478 · Cited by 2
Toward Replicability With Confidence Intervals for the Exceedance Probability
Segal, B. D. (2019) · Figshare · doi:10.6084/m9.figshare.10762796.v1 · Cited by 2
Too Fast to Live? Effects of Growth on Survival Across the Growth DistributionPreprint
Coad, A., Frankish, J. S., & STOREY, D. J. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2997193 · Cited by 2
Please refrain from presenting p-values!
Verhagen, A. P. (2021) · Musculoskeletal Science and Practice · doi:10.1016/j.msksp.2021.102351 · Cited by 2
Zeevi, Y., Astashenko, S., Mudrik, L., & Benjamini, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.11585 · Cited by 4
Statisticians roll up your sleeves! There’s a crisis to be solved.Preprint
Seibold, H., Charlton, A., Boulesteix, A., et al. (2020) · doi:10.31222/osf.io/frta7 · Cited by 2
Statistical Power, P ‐Values, and the Positive Predictive Value
Barnes, J. C., & Linning, S. J. (2021) · The Encyclopedia of Research Methods in Criminology and Criminal Justice · doi:10.1002/9781119111931.ch68 · Cited by 3
La recherche et l'innovation dans l'enseignement
OECD, & Centre for Educational Research and Innovation (2010) · La recherche et l’innovation dans l’enseignement · doi:10.1787/20769695 · Cited by 2
Bapna, S., & Burtch, G. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3938577 · Cited by 2
In this issue… p <.05 and other qualitative musings
Piedra, L. M., & Lanesskog, D. (2022) · Qualitative Social Work · doi:10.1177/14733250221080531 · Cited by 2
“(All emphasis mine; Wasserstein & Lazar, 2016: 132.)”
MethodInfluential(2018) · Wiley eBooks · doi:10.1002/9781118280249.refs · Cited by 2
Angelini, C. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.20356-7 · Cited by 4
Heino, M. T. J., Fried, E. I., Sund, R., et al. (2019) · doi:10.31234/osf.io/46rzm · Cited by 2
Statistical guidance to authors at top-ranked journals across scientific disciplinesPreprint
Hardwicke, T. E., Salholz‐Hillel, M., Malički, M., et al. (2022) · doi:10.31222/osf.io/q6ajt · Cited by 2
Kim, H. (2022) · Journal of Periodontal & Implant Science · doi:10.5051/jpis.225203edi01 · Cited by 2
“In recent years, to address prevalent misuses of and misconceptions concerning P values, statisticians have suggested supplementing or even replacing P values with other approaches [1].”
BackgroundReverse-Bayes methods for evidence assessment and research synthesisPreprint
Held, L., Matthews, R., Ott, M., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.13443 · Cited by 2
“Good (1983, p. 29) There is now a common consensus that the most widely-used methods of statistical inference have led to a crisis in both the interpretation of research findings and their replication ( e. g. Gelman and Loken, 2014; Wasserstein and Lazar, 2016).”
BackgroundMethodInfluential
Metadata
- Authors
- Wasserstein, R. L., & Lazar, N. A.
- Affiliations
- American Statistical Association, 732 North Washington Street, Alexandria, VA 22314-1943
- American Statistical Association (US)
- ORCID
- Lazar, Nicole A.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 2016-04-02
- Volume
- 70
- Issue
- 2
- Pages
- 129-133
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2293040502
- Semantic Scholar
- 81a65f23474ffceb2481836328608102950da979
- Cited by
- 6,306
- References
- 45
- Citations by year
- 2026: 625 · 2025: 629 · 2024: 575 · 2023: 543 · 2022: 642 · 2021: 676 · 2020: 678 · 2019: 666 · 2018: 596 · 2017: 438 · 2016: 226
- FWCI
- 649.74
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The American Statistician (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- p-values, statistical evidence, p-value interpretation, statistical inference, hypothesis testing
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