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]
Citations
Cites
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011) · Psychological Science · doi:10.1177/0956797611417632 · Cited by 6,567
(1947) · The American Statistician · doi:10.1080/00031305.1947.10501534 · Cited by 3,745
The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis
Hoenig, J. M., & Heisey, D. M. (2001) · The American Statistician · doi:10.1198/000313001300339897 · Cited by 2,046
Statistics notes: Absence of evidence is not evidence of absence
Altman, D. G., & Bland, J. M. (1995) · BMJ · doi:10.1136/bmj.311.7003.485 · Cited by 1,946
Smithson, M. J. (2000) · SAGE Publications Ltd eBooks · doi:10.4135/9781446218525 · Cited by 1,871
Bayesian statistical inference for psychological research.
Edwards, W., Lindman, H., & Savage, L. J. (1963) · Psychological Review · doi:10.1037/h0044139 · Cited by 1,734
Scientific method: Statistical errors
Nuzzo, R. (2014) · Nature · doi:10.1038/506150a · Cited by 1,536
Why Most Discovered True Associations Are Inflated
Ioannidis, J. P. A. (2008) · Epidemiology · doi:10.1097/ede.0b013e31818131e7 · Cited by 1,495
Sterne, J. A. C. (2001) · BMJ · doi:10.1136/bmj.322.7280.226 · Cited by 1,466
Contradicted and Initially Stronger Effects in Highly Cited Clinical Research
Ioannidis, J. P. A. (2005) · JAMA · doi:10.1001/jama.294.2.218 · Cited by 1,465
Research works printed but not linked: 5
- Leek, J. (2014), “On the Scalability of Statistical Procedures: Why the p-Value Bashers Just Don't Get It,” Simply Statistics Blog, Available at http://simplystatistics.org/2014/02/14/on-the-scalability-of-statistical-procedures-why-the-p-value-bashers-just-dont-get-it/.
- Gelman A. and Loken E. (2014) “The Statistical Crisis in Science [online] ” American Scientist 102. Available at http://www.americanscientist.org/issues/feature/2014/6/the-statistical-crisis-in-science · DOI · Paper page
- Greenland, S., and Poole, C. (2011), “Problems in Common Interpretations of Statistics in Scientific Articles, Expert Reports, and Testimony,” Jurimetrics, 51, 113–129.
- 10.1214/13-AOS1123 · DOI
- Lavine, M. (1999), “What is Bayesian Statistics and Why Everything Else is Wrong,” UMAP Journal, 20, 2.
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“ontext Although species richness is usually strongly influenced by landscape context, we were unable to find a statistically clear relationship in this study Inferring weak effects from large p-values (Wasserstein and Lazar, 2016) ... differencesbetweentreatment and control groups were nonsignificant, with P values of at…”
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Fairburn, J., Schüle, S. A., Dreger, S., Hilz, L. K., & Bolte, G. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16173127 · Cited by 199
“05 cut-off point but there has been increasing concerning in the sciences about the use of these measures [71,72].”
BackgroundThe Impact of Physical Activity on Brain Structure and Function in Youth: A Systematic Review
Valkenborghs, S. R., Noetel, M., Hillman, C. H., Nilsson, M., Smith, J. J., Ortega, F. B., & Lubans, D. R. (2019) · PEDIATRICS · doi:10.1542/peds.2018-4032 · Cited by 220
“The P values do not provide an indication of the size of an effect nor the importance of a result and by themselves are not a good measure of evidence regarding a model or hypothesis.(70) As such, the field needs to progress to promote the reporting of effect estimates in addition to the corresponding statistics.”
BackgroundPalea, V., & Drogo, F. (2020) · Business Strategy and the Environment · doi:10.1002/bse.2550 · Cited by 219
Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence
Bonkhoff, A. K., & Grefkes, C. (2021) · Brain · doi:10.1093/brain/awab439 · Cited by 216
“On the one hand, extensive datasets will more frequently lead to statistical significance of effects with (clinically) negligible effect sizes.(73,74) For example, Miller and colleagues conducted 14 million individual association tests between MRI-derived brain phenotypes, e.”
BackgroundInference in the age of big data: Future perspectives on neuroscience
Bzdok, D., & Yeo, B. T. T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.061 · Cited by 195
Interpretation of chronic pain clinical trial outcomes: IMMPACT recommended considerations
Smith, S. M., Dworkin, R. H., Turk, D. C., McDermott, M. P., Eccleston, C., Farrar, J. T., Rowbotham, M. C., Bhagwagar, Z., Burke, L. B., Cowan, P., et al. (2020) · Pain · doi:10.1097/j.pain.0000000000001952 · Cited by 194
“With a large enough sample size or low variability in outcomes, an observed treatment effect that is clinically insignificant can be associated with a statistically significant result.(121) Conversely, as discussed previously, a trial with a small sample size or high variability in outcomes can yield a large estimated…”
BackgroundSmith, O. M., Cohen, A. L., Rieser, C. J., Davis, A. G., Taylor, J. M., Adesanya, A. W., Jones, M. S., Meier, A. R., Reganold, J. P., Orpet, R. J., et al. (2019) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2019.00082 · Cited by 195
Bertoldi, P., & Mosconi, R. (2020) · Energy Policy · doi:10.1016/j.enpol.2020.111320 · Cited by 190
“Moreover, as discussed in Wasserstein and Lazar (2016), a p-value > 0.05 does not imply that the null hypothesis is true, and “ scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold ” (see also McShane and Gal (2017),…”
InfluentialWhat is science’s crisis really about?
Saltelli, A., & Funtowicz, S. (2017) · Futures · doi:10.1016/j.futures.2017.05.010 · Cited by 207
“More bluntly, Belinda Phipps, head of the UK Science Council, noted in an interview to The Times (Whipple, 2016) that the public trusted scientists only because they did not understand their work, and that scientists ‘should take ethics oath, like doctors’ (see König et al.’s contribution in this issue on the ethos of…”
BackgroundEmotions in Tourism: Theoretical Designs, Measurements, Analytics, and Interpretations
Hosany, S., Martin, D., & Woodside, A. G. (2020) · Journal of Travel Research · doi:10.1177/0047287520937079 · Cited by 198
“…use of MRA and SEM for proposing and testing variable directional relationships (VDR) using NHST is bad science practice as a number of scholars (Hubbard 2015; Meehl 1978; Woodside 2019; Ziliak and McCloskey 2008) and the American Statistical Association (ASA) advance (Wasserstein and Lazar 2016).”
MethodRemove, rather than redefine, statistical significance
Amrhein, V., & Greenland, S. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0224-0 · Cited by 182
Asker, M., Brooke, H. L., Waldén, M., Tranæus, U., Johansson, F. R., Skillgate, E., & Holm, L. W. (2018) · British Journal of Sports Medicine · doi:10.1136/bjsports-2017-098254 · Cited by 199
Multi-decadal surface ozone trends at globally distributed remote locations
Cooper, O. R., Schultz, M. G., Schröder, S., Chang, K., Gaudel, A., Benítez, G. C., Cuevas, E., Fröhlich, M., Galbally, I. E., Molloy, S. B., et al. (2020) · Elementa Science of the Anthropocene · doi:10.1525/elementa.420 · Cited by 179
Ioannidis, J. P. A., Kim, B. Y. S., & Trounson, A. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0314-y · Cited by 175
Truong, Y., Khamseh, H. M., & Berrone, P. (2020) · Industrial Marketing Management · doi:10.1016/j.indmarman.2020.05.006 · Cited by 184
Schüle, S. A., Hilz, L. K., Dreger, S., & Bolte, G. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16071216 · Cited by 176
“However, this approach has been criticised [66,67].”
Statistical Significance and the Dichotomization of Evidence
McShane, B. B., & Gal, D. (2017) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1289846 · Cited by 174
“Statisticians and others have been sounding the alarm about these matters for decades, to little avail” (Wasserstein and Lazar 2016).”
BackgroundMethodInfluentialCrooks, C. V., Jaffe, P. G., Dunlop, C., Kerry, A. J., & Exner‐Cortens, D. (2018) · Violence Against Women · doi:10.1177/1077801218815778 · Cited by 183
“Our adherence to the p .05 criterion as the arbiter of truth does not serve us well as it does not measure the size of an effect or the importance of a result (Wasserstein & Lazar, 2016).”
MethodLow significance of evidence for black hole echoes in gravitational wave data
Westerweck, J., Nielsen, A. B., Fischer-Birnholtz, O., Cabero, M., Capano, C. D., Dent, T., Krishnan, B., Meadors, G. D., & Nitz, A. (2018) · Physical review. D/Physical review. D. · doi:10.1103/physrevd.97.124037 · Cited by 169
Taylor, D. L., Jackson, A., Narisu, N., Hemani, G., Erdos, M. R., Chines, P. S., Swift, A. J., Idol, J., Didion, J. P., Welch, R., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814263116 · Cited by 159
Poor performance of clinical prediction models: the harm of commonly applied methods
Steyerberg, E. W., Uno, H., Ioannidis, J. P. A., CALSTER, B. V., Ukaegbu, C. I., Dhingra, T. G., Syngal, S., & Kastrinos, F. (2017) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2017.11.013 · Cited by 173
Moreno–Grau, S., de Rojas, I., Hernández, I., Quintela, I., Montrreal, L., Alegret, M., Hernández‐Olasagarre, B., Madrid, L., González‐Pérez, A., Maroñas, O., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.06.4950 · Cited by 161
“Results were interpreted according to the American Statistical Association guidelines [25,26].”
InfluentialKelter, R. (2020) · BMC Medical Research Methodology · doi:10.1186/s12874-020-00980-6 · Cited by 158
RMSE is not enough: Guidelines to robust data-model comparisons for magnetospheric physics
Liemohn, M. W., Shane, A. D., Azari, A., et al. (2021) · Journal of Atmospheric and Solar-Terrestrial Physics · doi:10.1016/j.jastp.2021.105624 · Cited by 168
“In fact, the American Statistical Association issued a statement deemphasizing scholarly reliance on p-values (Wasserstein and Lazar, 2016).”
BackgroundMicronized vaginal progesterone to prevent miscarriage: a critical evaluation of randomized evidence
Coomarasamy, A., Devall, A. J., Brosens, J. J., Quenby, S., Stephenson, M. D., Sierra, S., Christiansen, O. B., Small, R., Brewin, J., Roberts, T. E., et al. (2020) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2019.12.006 · Cited by 163
Predicting the early risk of chronic kidney disease in patients with diabetes using real-world data
Ravizza, S., Huschto, T., Adamov, A., Böhm, L., Büsser, A., Flöther, F. F., Hinzmann, R., König, H., McAhren, S. M., Robertson, D. H., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0239-8 · Cited by 167
Bear, D. E., Langan, A., Dimidi, E., Wandrag, L., Harridge, S. D. R., Hart, N., Connolly, B. A., & Whelan, K. (2018) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqy373 · Cited by 167
“Effect sizes were also relied upon as these are of greater clinical relevance and recommended by both the American Statistical Association (33) and the Cochrane Handbook for Systematic Reviews of Interventions (28).”
BackgroundEnhancing Rigor in Quantitative Entrepreneurship Research
MAULA, M. V. J., & Stam, W. (2019) · Entrepreneurship Theory and Practice · doi:10.1177/1042258719891388 · Cited by 190
“Whereas the p value can indicate how incompatible the data are with a specified statistical model, it does not measure the size of an effect or the importance of a result (Wasserstein & Lazar, 2016).”
BackgroundInfluentialAdiposity, metabolites, and colorectal cancer risk: Mendelian randomization study
Bull, C. J., Bell, J. A., Murphy, N., Sanderson, E. C. M., Smith, G. D., Timpson, N. J., Banbury, B. L., Albanes, D., Berndt, S. I., Bezieau, S., et al. (2020) · BMC Medicine · doi:10.1186/s12916-020-01855-9 · Cited by 174
Associations of Body Mass and Fat Indexes With Cardiometabolic Traits
Bell, J. A., Carslake, D., O’Keeffe, L. M., Frysz, M., Howe, L. D., Hamer, M., Wade, K. H., Timpson, N. J., & Smith, G. D. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.09.066 · Cited by 164
“Here, we focus on effect size and precision (27,28).”
Amesbury, M. J., Swindles, G. T., Bobrov, A., Charman, D. J., Holden, J., Lamentowicz, M., Mallon, G., Mazei, Y., Mitchell, E. A. D., Payne, R. J., et al. (2016) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2016.09.024 · Cited by 173
“Coupled with recent guidance that warns against the use of seemingly arbitrary p-value cut-offs and stresses the need for contextual information in decision making rather than a binary ‘yes/no’ approach (Wasserstein and Lazar, 2016), a multifaceted approach to model assessment is clearly supported.”
BackgroundInfluentialVoitalov, I., van der Hoorn, P., van der Hofstad, R., & Krioukov, D. (2019) · Physical Review Research · doi:10.1103/physrevresearch.1.033034 · Cited by 207
“The popular p -value approach used often in hypothesis testing is deeply problematic and should be avoided, as has been long known and recently well documented in a statement article by the American Statistical Association [53], followed by a special issue of The American Statistician [54].”
MethodAutogenic Sedimentation in Clastic Stratigraphy
Hajek, E. A., & Straub, K. M. (2017) · Annual Review of Earth and Planetary Sciences · doi:10.1146/annurev-earth-063016-015935 · Cited by 163
“…of the character and structure of autogenic sedimentation could help build improved statistical tests, particularly in light of recent discussions that p-tests and confidence bands are only as good as the statistical model used to describe a system (Hilgen et al. 2015, Wasserstein & Lazar 2016).”
What Have We (Not) Learnt from Millions of Scientific Papers with P Values?
Ioannidis, J. P. A. (2019) · The American Statistician · doi:10.1080/00031305.2018.1447512 · Cited by 172
“Decisive action is needed both from the statistical and wider scientific community (Wasserstein and Lazar 2016).”
BackgroundBzdok, D. (2017) · HAL · Cited by 160
Coup de Grâce for a Tough Old Bull: “Statistically Significant” Expires
Hurlbert, S. H., Levine, R. A., & Utts, J. M. (2019) · The American Statistician · doi:10.1080/00031305.2018.1543616 · Cited by 159
“Indeed, why did the ASA statement (Wasserstein and Lazar 2016) not recommend the phrase be abandoned?”
BackgroundQuantified Uncertainties in Comparative Life Cycle Assessment: What Can Be Concluded?
Beltrán, A. M., Prado, V., Vivanco, D. F., Henriksson, P. J. G., Guinée, J. B., & Heijungs, R. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.7b06365 · Cited by 176
How to Construct, Conduct and Analyze an Exercise Training Study?
Hecksteden, A., Faude, O., Meyer, T., & Donath, L. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01007 · Cited by 172
“…the formerly unrivaled p-value based hypothesis-testing approach to inferential statistics has been increasingly criticized (Sterne and Davey Smith, 2001; Wilkinson, 2014; Wasserstein and Lazar, 2016; McShane and Gal, 2017), up to the point of recommending its complete abolishment (Buchheit, 2016).”
BackgroundEptinezumab for prevention of chronic migraine: A randomized phase 2b clinical trial
Dodick, D. W., Lipton, R. B., Silberstein, S. D., Goadsby, P. J., Biondi, D. M., Hirman, J., Cady, R. K., & Smith, J. (2019) · Cephalalgia · doi:10.1177/0333102419858355 · Cited by 155
Abdallah, M. S., Adam, J., Adamczyk, L., Adams, J. R., Adkins, J. K., Agakishiev, G., Aggarwal, I., Aggarwal, M. M., Ahammed, Z., Alekseev, I. G., et al. (2021) · Physical Review C · doi:10.1103/physrevc.104.024902 · Cited by 154
Editorial: Enhancing quantitative theory-testing entrepreneurship research
Anderson, B. S., Wennberg, K. J., & McMullen, J. S. (2019) · Journal of Business Venturing · doi:10.1016/j.jbusvent.2019.02.001 · Cited by 166
“…of a finding using the p-value is the assumption that the null hypothesis is true; the p-value simply being the probability that the observed effect or a larger effect is due to random variation under the assumption of a true null hypothesis (Greenland et al., 2016; Wasserstein and Lazar, 2016).”
BackgroundOn the Reproducibility of Psychological Science
Johnson, V., Payne, R., Wang, T., Asher, A., & Mandal, S. (2016) · Journal of the American Statistical Association · doi:10.1080/01621459.2016.1240079 · Cited by 145
Kennard, B. D., Goldstein, T., Foxwell, A. A., McMakin, D. L., Wolfe, K., Biernesser, C., Moorehead, A., Douaihy, A., Zullo, L., Wentroble, E., et al. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.17101151 · Cited by 154
“Effect sizes were calculated as Hedges’ g (38).”
MethodStatistical inference as severe testing how to get beyond the statistics wars
Mayo, D. G. (2018) · Cited by 152
Nam, K., & Seong, N. (2018) · Decision Support Systems · doi:10.1016/j.dss.2018.11.004 · Cited by 154
Economic Significance in Corporate Finance
Mitton, T. (2022) · The Review of Corporate Finance Studies · doi:10.1093/rcfs/cfac008 · Cited by 167
Delay causality network in air transport systems
Du, W., Zhang, M., Zhang, Y., Cao, X., & Zhang, J. (2018) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2018.08.014 · Cited by 152
“Clustering coefficient is used to qualify the inherent cluster tendency of airports (Watts and Strogatz, 1998; Fagiolo, 2007).”
MethodBrain Connectivity and Neuroimaging of Social Networks in Autism
Müller, R., & Fishman, I. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.09.008 · Cited by 154
Philosophy of science and the replicability crisis
Romero, F. (2019) · Philosophy Compass · doi:10.1111/phc3.12633 · Cited by 166
High Sensitivity of Compound Drought and Heatwave Events to Global Warming in the Future
Zhang, Q., Zhang, L., She, D., Wang, G., Chen, J., & Hao, Z. (2022) · Earth s Future · doi:10.1029/2022ef002833 · Cited by 156
“F-test is used to test the statistical significance of results of sensitivity.”
MethodInfluentialCarneiro, C. F. D., Queiroz, V. G. S., Moulin, T. C., Carvalho, C. A. M., Haas, C. B., Rayêe, D., Henshall, D. E., De-Souza, E. A., Amorim, F. E., Boos, F. Z., et al. (2020) · Research Integrity and Peer Review · doi:10.1186/s41073-020-00101-3 · Cited by 146
Kennedy‐Shaffer, L. (2019) · The American Statistician · doi:10.1080/00031305.2018.1537891 · Cited by 165
“With a little modernization of language, Cournot could have written principles 2, 5, and 6 of the ASA Statement (Wasserstein and Lazar 2016).”
BackgroundStatistical Nonsignificance in Empirical Economics
Abadie, A. (2020) · American Economic Review: Insights · doi:10.1257/aeri.20190252 · Cited by 148
“Previous studies have described the important limitations of significance testing as an inferential tool in the social sciences and other disciplines (see, in particular, Leamer, 1978; Berger, 1985; Berger and Selke, 1999; Sims and Uhlig, 1991; Gelman and Stern, 2006; Ziliak and McCloskey, 2008; Greenland and Poole, 2…”
BackgroundBayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
van Doorn, J. B., Ly, A., Marsman, M., & Wagenmakers, E. (2020) · Journal of Applied Statistics · doi:10.1080/02664763.2019.1709053 · Cited by 167
“The debate on alternatives to null hypothesis significance tests based on p -values [63] has led to a renewed interest in the Bayesian alternative known as the Bayes factor.”
Fulkerson, J. A., Friend, S. E., Horning, M. L., Flattum, C. F., Draxten, M. L., Neumark‐Sztainer, D., Gurvich, O. V., Garwick, A. W., Story, M. T., & Kubik, M. (2017) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2017.04.006 · Cited by 143
Is the statistic value all we should care about in neuroimaging?
Chen, G., Taylor, P. A., & Cox, R. W. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.066 · Cited by 137
Editorial: Bayesian methods for advancing psychological science
Vandekerckhove, J., Rouder, J. N., & Kruschke, J. K. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-018-1443-8 · Cited by 133
“The American Statistical Association recently published an unusual warning against inference based on p values (Wasserstein & Lazar, 2016).”
BackgroundReducing bias, increasing transparency and calibrating confidence with preregistration
Hardwicke, T. E., & Wagenmakers, E. (2023) · Nature Human Behaviour · doi:10.1038/s41562-022-01497-2 · Cited by 205
Reinertsen, E., & Clifford, G. D. (2018) · Physiological Measurement · doi:10.1088/1361-6579/aabf64 · Cited by 136
Cho, Y., Haycock, P., Sanderson, E. C. M., Gaunt, T. R., Zheng, J., Morris, A. P., Smith, G. D., & Hemani, G. (2020) · Nature Communications · doi:10.1038/s41467-020-14452-4 · Cited by 139
“We take forward putative associations based on false discovery rate (FDR) 0.05, where the null hypothesis is true, but we note that the use of arbitrary thresholds is problematic 48,49 , and we use them here to make high dimensional investigations more manageable.”
MethodInfluentialSchmitt, S. A., Korucu, I., Napoli, A. R., Bryant, L. M., & Purpura, D. J. (2018) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2018.04.006 · Cited by 157
Clinical Effects of Balanced Crystalloids vs Saline in Adults With Diabetic Ketoacidosis
Self, W. H., Evans, C. S., Jenkins, C. A., Brown, R. M., Casey, J. D., Collins, S. P., Coston, T. D., Felbinger, M., Flemmons, L. N., Hellervik, S. M., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.24596 · Cited by 145
Network Physiology of Exercise: Vision and Perspectives
Balagué, N., Hristovski, R., Almarcha, M., García‐Retortillo, S., & Ivanov, P. C. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.611550 · Cited by 136
Selecting the “Best” Factor Structure and Moving Measurement Validation Forward: An Illustration
Schmitt, T. A., Sass, D. A., Chappelle, W. L., & Thompson, W. T. (2018) · Journal of Personality Assessment · doi:10.1080/00223891.2018.1449116 · Cited by 148
“…tend to overfit the data; thus, using global goodness-of-fit indexes as the only model selection criteria is analogous to “p-hacking” and is not prudent (Browne & Cudeck, 1992; Head, Holman, Lanfear, Kahn, & Jennions, 2015; Roberts & Pashler, 2000; Siegfried, 2010; Wasserstein & Lazar, 2016).”
BackgroundMethodRandomised clinical trials in critical care: past, present and future
Granholm, A., Alhazzani, W. A., Derde, L. P. G., Angus, D. C., Zampieri, F. G., Hammond, N. E., Sweeney, R. M., Myatra, S. N., Azoulay, É., Rowan, K., et al. (2021) · Intensive Care Medicine · doi:10.1007/s00134-021-06587-9 · Cited by 136
A proposed conceptualization of talent in sport: The first step in a long and winding road
Baker, J. R., Wattie, N., & Schorer, J. (2018) · Psychology of sport and exercise · doi:10.1016/j.psychsport.2018.12.016 · Cited by 168
Multiple comparisons: To compare or not to compare, that is the question
Barnett, M. J., Doroudgar, S., Khosraviani, V., & Ip, E. J. (2021) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2021.07.006 · Cited by 133
Hodi, F. S., Wolchok, J. D., Schadendorf, D., Larkin, J., Long, G. V., Qian, X., Saci, A., Young, T. C., Srinivasan, S., Chang, H., et al. (2021) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-20-0983 · Cited by 138
P values and the search for significance
Altman, N., & Krzywinski, M. I. (2016) · Nature Methods · doi:10.1038/nmeth.4120 · Cited by 129
Hydroxychloroquine early in pregnancy and risk of birth defects
Huybrechts, K. F., Bateman, B. T., Zhu, Y., Straub, L., Mogun, H., Kim, S. C., Desai, R. J., & Hernández–Dı́az, S. (2020) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2020.09.007 · Cited by 131
Transcendental values and the valuation and management of ecosystem services
Raymond, C. M., & Kenter, J. O. (2016) · Ecosystem Services · doi:10.1016/j.ecoser.2016.07.018 · Cited by 127
“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).”
MethodThe Harm Done to Reproducibility by the Culture of Null Hypothesis Significance Testing
Lash, T. L. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx261 · Cited by 128
Ziegler, G., Hauser, T. U., Moutoussis, M., Bullmore, E. T., Goodyer, I. M., Fonagy, P., Jones, P. B., Lindenberger, U., & Dolan, R. J. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0394-3 · Cited by 120
Technical Considerations in the Use of the E-Value
VanderWeele, T. J., Ding, P., & Mathur, M. B. (2019) · Journal of Causal Inference · doi:10.1515/jci-2018-0007 · Cited by 127
A Revised Ground‐Motion Prediction Model for Shallow Crustal Earthquakes in Italy
Lanzano, G., Luzi, L., Pacor, F., et al. (2019) · Bulletin of the Seismological Society of America · doi:10.1785/0120180210 · Cited by 126
Coming of age: the past, present, and future of quantitative SLA research
Gass, S. M., Loewen, S., & Plonsky, L. (2020) · Language Teaching · doi:10.1017/s0261444819000430 · Cited by 122
“As stated by the American Statistical Association (Wasserstein & Lazar, 2016), ‘Proper inference requires full reporting and transparency’ (p. 131).”
BackgroundMichel, M. C., Murphy, T. J., & Motulsky, H. J. (2020) · Molecular Pharmacology · doi:10.1124/mol.119.118927 · Cited by 127
Antimicrobial Use and Veterinary Care among Agro-Pastoralists in Northern Tanzania
Caudell, M. A., Quinlan, M. B., Subbiah, M., Call, D. R., Roulette, C. J., Roulette, J. W., Roth, A. R., Matthews, L., & Quinlan, R. J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0170328 · Cited by 135
The False Positive Risk: A Proposal Concerning What to Do About p -Values
Colquhoun, D. (2019) · The American Statistician · doi:10.1080/00031305.2018.1529622 · Cited by 134
“(Sellke, Bayarri and Berger 2001, p. 71) The ASA statement (Wasserstein and Lazar 2016) gave a cogent critique of p-values.”
BackgroundO’Malley, E., Richter, C., King, E. A., Strike, S. C., Moran, K., Franklyn‐Miller, A., & Moran, R. (2018) · Journal of Athletic Training · doi:10.4085/1062-6050-480-16 · Cited by 123
Moews, B., Herrmann, J. M., & Ibikunle, G. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.11.027 · Cited by 123
“In 2016, the American Statistical Association published an official warning regarding the wide-spread misuse of p -values (Wasserstein and Lazar, 2016).”
Background
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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