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
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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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Radžvilas, M., Peden, W., & Pretis, F. D. (2021) · Synthese · doi:10.1007/s11229-021-03395-y · Cited by 13
Croft, J., Teufel, C., Heron, J., Fletcher, P. C., David, A. S., Lewis, G., Moutoussis, M., FitzGerald, T. H. B., Linden, D. E. J., Thompson, A. D., et al. (2021) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2021.12.007 · Cited by 11
“Consistent with the approach recommended by Sterne et al. (39,40), and as is increasingly common practice in epidemiology, we avoided using an arbitrary cutoff to de fi ne signi fi - cance and considered p values to re fl ect the strength of evidence for each fi nding.”
MethodDoedens, P., ter Riet, G., Boyette, L., et al. (2022) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2022.01.005 · Cited by 12
Checa, M. A., Palop-Montoro, M. V., & Manzano-Sánchez, D. (2022) · Sustainability · doi:10.3390/su14031188 · Cited by 12
Leweri, C., Bartzke, G. S., Msuha, M. J., & Treydte, A. C. (2022) · PLoS ONE · doi:10.1371/journal.pone.0267082 · Cited by 12
“056) in the final model as water availability is an important variable in conservation planning [61].”
BackgroundParabens and Menopause-Related Health Outcomes in Midlife Women: A Pilot Study
Pacyga, D. C., Chiang, C., Li, Z., Strakovsky, R. S., & Ziv‐Gal, A. (2022) · Journal of Women s Health · doi:10.1089/jwh.2022.0004 · Cited by 11
“Owing to the exploratory nature of the study and recommendations from the American Statistical Association and other epidemiologists, 39,40 we focused on patterns of associations rather than statistical significance based on P -values.”
Morality in the time of cognitive famine: The effects of memory load on cooperation and honesty
Mitkidis, P., Lindeløv, J. K., Elbæk, C. T., Porubanová, M., Grzymała-Moszczyńska, J., & Ariely, D. (2022) · Acta Psychologica · doi:10.1016/j.actpsy.2022.103664 · Cited by 11
Carr, J. M. J. R., Ainslie, P. N., MacLeod, D. B., Tremblay, J. C., Nowak‐Flück, D., Howe, C. A., Stembridge, M. R., Patrician, A., Coombs, G. B., Stacey, B. S., et al. (2022) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x221119442 · Cited by 13
Bisht, L. S., & Tiwari, G. (2022) · Journal of Transportation Engineering Part A Systems · doi:10.1061/jtepbs.0000767 · Cited by 12
Bendtsen, M. (2022) · Journal of Medical Internet Research · doi:10.2196/40730 · Cited by 12
Kang, K., Jones, M. T., Armstrong, K., et al. (2023) · Psychometrika · doi:10.1007/s11336-022-09899-x · Cited by 12
“This approach may help to address the limitations of null hypothesis significance testing (Wasserstein & Lazar, 2016; Wasserstein et al., 2019) and provide guidance on whether a study finding is under-powered.”
InfluentialTransfusion Strategy in Myocardial Infarction and Anemia
Khan, M. S., Spertus, J. A., & Chan, P. S. (2024) · New England Journal of Medicine · doi:10.1056/nejmc2400982 · Cited by 12
Tume, L. N., Baines, P. B., Guerrero, R., Hurley, M. A., Johnson, R., Kalantre, A., Ramaraj, R., Ritson, P. C., Walsh, L., & Arnold, P. D. (2017) · Pediatric Critical Care Medicine · doi:10.1097/pcc.0000000000001192 · Cited by 12
“Adjustments to significance levels for multiple testing were not applied, but interpretation of p values was carried out in context as recommended by the American Statistical Association guidance (12).”
Gaffîeld, C. (2018) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-031017-100547 · Cited by 12
Gönen, M., Johnson, W. O., Lu, Y., & Westfall, P. H. (2017) · The American Statistician · doi:10.1080/00031305.2017.1322142 · Cited by 12
Structural equation modeling as a tool to investigate correlates of extra-pair paternity in birds
Crouch, N. M. A., & Mason‐Gamer, R. J. (2018) · PLoS ONE · doi:10.1371/journal.pone.0193365 · Cited by 12
Krueger, J. I., & Heck, P. R. (2018) · Collabra Psychology · doi:10.1525/collabra.108 · Cited by 12
“The p value refers to the probability of the data at least as extreme as the observed data given the statistical (often the null) hypothesis, p(D|H), and assuming that underlying assumptions are met (Greenland et al., 2016; Wasserstein & Lazar, 2016).”
BackgroundTowards a learning system for pediatric outcomes: Harvesting meaning from evidence
Kleinman, L. C., & Barach, P. R. (2018) · Progress in Pediatric Cardiology · doi:10.1016/j.ppedcard.2018.05.002 · Cited by 12
Added Value of Subscores and Hypothesis Testing
Sinharay, S. (2018) · Journal of Educational and Behavioral Statistics · doi:10.3102/1076998618788862 · Cited by 12
Sex‐specific effects of outbreeding on offspring quality in pike (Esox lucius)
Sunde, J., Tibblin, P., Larsson, P., et al. (2018) · Ecology and Evolution · doi:10.1002/ece3.4510 · Cited by 12
Miano, T. A., Abelian, G., Seamon, M. J., Chreiman, K. M., Reilly, P. M., & Martin, N. D. (2019) · Journal of the American College of Surgeons · doi:10.1016/j.jamcollsurg.2019.02.037 · Cited by 12
“Characteristic Summary measure, n=19,353 Age, y, median (IQR) 43 (26-59)”
Shin, S. S., Carpenter, C. L., Ekstrand, M. L., Wang, Q., Grover, S., Zetola, N. M., Yadav, K., Sinha, S., & Nyamathi, A. (2019) · International Journal of STD & AIDS · doi:10.1177/0956462419825950 · Cited by 13
“In accordance with recent guidelines provided by the American Statistical Association, no alpha cutoff was specified for statistical significance.(21,22)”
Shiba, K., & Kondo, N. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16061001 · Cited by 12
Understanding the Reputation Differences between Women and Men on Stack Overflow
Wang, Y. (2018) · Asia-Pacific Software Engineering Conference (APSEC) · doi:10.1109/apsec.2018.00058 · Cited by 15
“We follow the American Statistical Association’s principles to present and interpret the statistical results [23].”
MethodMisunderstandings and omissions in textbook accounts of effect sizes.
Morris, P. H. (2020) · British Journal of Psychology · doi:10.1111/bjop.12401 · Cited by 10
“The American Statistical Association makes the excellent point that “[n]o single index should substitute for scientific reasoning” (Wasserstein & Lazar, 2016, p. 12).”
BackgroundHe, Y., Τheodoratou, E., Li, X., et al. (2019) · International Journal of Cancer · doi:10.1002/ijc.32550 · Cited by 12
P‐value thresholds: Forfeit at your peril
Mayo, D. G. (2019) · European Journal of Clinical Investigation · doi:10.1111/eci.13170 · Cited by 11
Confidence intervals: what are they to us, medical doctors?
Trkulja, V., & Hrabač, P. (2019) · Croatian Medical Journal · doi:10.3325/cmj.2019.60.375 · Cited by 12
Assessing Bayes Factor Surfaces Using Interactive Visualization and Computer Surrogate Modeling
Franck, C. T., & Gramacy, R. B. (2019) · The American Statistician · doi:10.1080/00031305.2019.1671219 · Cited by 12
EFFECT size or statistical significance, where to put your money
Cutter, G. (2019) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2019.101490 · Cited by 12
Null Hypothesis Significance Testing Defended and Calibrated by Bayesian Model Checking
Bickel, D. R. (2019) · The American Statistician · doi:10.1080/00031305.2019.1699443 · Cited by 12
“The mounting opposition against null hypothesis significance testing ranges from warnings about misusing it (Wasserstein and Lazar 2016) to its outright banning from journal publication (Trafimow and Marks 2015).”
BackgroundNull hypothesis significance testing and effect sizes: can we ‘effect’ everything … or … anything?
Lovell, D. P. (2020) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2019.12.001 · Cited by 16
McCray, C. D., Gyakum, J. R., & Atallah, E. H. (2020) · Weather and Forecasting · doi:10.1175/waf-d-19-0179.1 · Cited by 12
“Unauthenticated | Downloaded 07/15/21 08:49 PM UTC the top down (Wexler et al. 1954; Stewart 1985; Kain et al. 2000).”
El valor de p en entredicho: significación estadística, clínica y práctica
Jiménez-Paneque, R. (2016) · Medwave · doi:10.5867/medwave.2016.08.6534 · Cited by 12
“La muy reciente declaración de la American Statistical Association (ASA) es elocuente y clara a este respecto [23].”
BackgroundRegional Variation and Temporal Trends in Surgery for Pelvic Organ Prolapse in Canada, 2004-2014
Lisonkova, S., Geoffrion, R., Sanaee, M., Muraca, G. M., Wen, Q., Yong, P. J., Larouche, M., & Cundiff, G. W. (2020) · Journal of Obstetrics and Gynaecology Canada · doi:10.1016/j.jogc.2019.12.016 · Cited by 12
Kelter, R. (2020) · BMC Research Notes · doi:10.1186/s13104-020-05291-z · Cited by 11
Bayesian Analysis in Strategic Management Research: Time to Update Your Priors
McCann, B. T., & Schwab, A. (2023) · Strategic Management Review · doi:10.1561/111.00000053 · Cited by 12
Assessment of the Value of Tumor Variation Profiling Perceived by Patients With Cancer
Butow, P. N., Davies, G., Napier, C. E., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.4721 · Cited by 12
Bayesian hierarchical modelling for process optimisation
Ouyang, L., Park, C., Ma, Y., et al. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1769873 · Cited by 12
“…used p-values to identify the important predictors (Wang et al. 2020), whereas the use of the p-value method has recently been criticised, since the p-values often overestimate the evidence against the null hypothesis; see, for example, Wagenmakers (2007) and Wasserstein and Lazar (2016).”
MethodBringing Visual Inference to the Classroom
Loy, A. (2021) · Journal of Statistics and Data Science Education · doi:10.1080/26939169.2021.1920866 · Cited by 12
“Note: With only one observer this binary result (identifying the data or not) can appear to reinforce the type of bright-line thinking that the statistics community is trying to avoid (Wasserstein and Lazar 2016).”
BackgroundFragility index of network meta-analysis with application to smoking cessation data
Xing, A., Chu, H., & Lin, L. (2020) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2020.07.003 · Cited by 12
Lin, C. D., Brugnolo, L., Marinova, M., Plebani, M., Iliceto, S., Tona, F., & Vitiello, G. (2020) · Entropy · doi:10.3390/e22080818 · Cited by 12
“Clarification on the Concept of Statistical Significance in Biology/Medicine The P-value indicates the probability that two apparently different groups of data actually come (or not) from the same population and does not indicate whether the hypotheses under study is true or false [31].”
BackgroundZong, Z., Wen, L., Hu, X., et al. (2021) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2021.3063118 · Cited by 12
“However, policy decisions should not only depend on whether a p-value passes a specific threshold [24].”
BackgroundMethodWatson, J. (2021) · Spatial Statistics · doi:10.1016/j.spasta.2021.100500 · Cited by 12
Shaw, B. P. (2021) · Journal of Research in Music Education · doi:10.1177/00224294211006415 · Cited by 17
“Null hypothesis significance testing’s limitations are well documented (e.g., Wasserstein & Lazar, 2016).”
BackgroundReplicability Crisis and Scientific Reforms: Overlooked Issues and Unmet Challenges
Andreoletti, M. (2020) · International Studies in the Philosophy of Science · doi:10.1080/02698595.2021.1943292 · Cited by 16
Ninham, B. W., Bolotskova, P. N., Gudkov, S. V., et al. (2022) · Polymers · doi:10.3390/polym14081511 · Cited by 12
Doyle, T. R., Davey, M. S., & Hurley, E. T. (2022) · Journal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine · doi:10.1016/j.jisako.2022.04.003 · Cited by 12
“The American Statistical Association (ASA) statement in 2016 reaffirmed that P values do not measure the probability of a true result, “the size of an effect or the importance of a result” [94].”
BackgroundLi, H., Zhou, G., & Wang, J. (2022) · Buildings · doi:10.3390/buildings12081184 · Cited by 12
DeVries, M. S., Cordes, M. A., Rodriguez, J. D., Stevenson, S. A., & Riters, L. V. (2016) · Brain Research · doi:10.1016/j.brainres.2016.05.031 · Cited by 12
“To assist in interpretation of these and all other results (as recently recommended by the American Statistical Association (Wasserstein and Lazar, 2016)) we also report confidence intervals and effect sizes using Cohen's d values to provide insight into the strength of the difference between…”
InfluentialIndividual differences in the shape of the nasal visual field
Swanson, W. H., Dul, M. W., Horner, D. G., et al. (2016) · Vision Research · doi:10.1016/j.visres.2016.04.001 · Cited by 12
“This was an exploratory data analysis, so we examined effect size using correlation, linear regression, and F-tests (Wasserstein & Lazar, 2016).”
Controlling the marginal false discovery rate in inferences from a soil dataset with α ‐investment
Lark, R. M. (2017) · European Journal of Soil Science · doi:10.1111/ejss.12413 · Cited by 12
“This approach can enable us to avoid problems entailed by multiple testing in a disciplined, hypothesis-driven approach to inference from data, which both maintains statistical power and guards against the perils of ‘P-hacking’.”
BackgroundInfluentialAIC identifies optimal representation of longitudinal dietary variables
VanBuren, J. M., Cavanaugh, J. E., Marshall, T. A., Warren, J. J., & Levy, S. M. (2017) · Journal of Public Health Dentistry · doi:10.1111/jphd.12220 · Cited by 13
“the overuse of P-values and P-value based methods (5,6).”
MethodPrediction and inference diverge in biomedicine: Simulations and real-world dataPreprint
Bzdok, D., Engemann, D. A., Grisel, O., Varoquaux, G. P., & Thirion, B. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/327437 · Cited by 12
“An official report of the American Statistical Association (ASA) emphasized that ‘Statistical significance is not equivalent to scientific, human, or economic significance’ (10).”
BackgroundNguyen, T. V., Rivadeneira, F., & Civitelli, R. (2019) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.3885 · Cited by 12
“To help our readers and prospective authors, we would like to underscore a few key points for correct p value interpretation, based on recommendations by the American Statistical Association.”
BackgroundMethodInfluentialPutting the P Value in its PlacePreprint
Krueger, J. I., & Heck, P. R. (2018) · doi:10.31234/osf.io/y49mp · Cited by 12
Common errors in statistics and methods
Flom, P., Harron, K., Ballesteros, J., Kalinda, C., Koutoumanou, E., Miles, J., Nevitt, S. J., & Rohloff, P. (2024) · BMJ Paediatrics Open · doi:10.1136/bmjpo-2024-002755 · Cited by 10
Can $p$-values be meaningfully interpreted without random sampling?
Hirschauer, N., Grüner, S., Mußhoff, O., Becker, C., & Jantsch, A. (2020) · Statistics Surveys · doi:10.1214/20-ss129 · Cited by 11
Esterhuizen, T. M., Mbuagbaw, L. C. E., Rehman, N., Yanwou, N., Swaby, D. J., Kittle, E., Licht, J.-C., & Thabane, L. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-100411 · Cited by 12
Progesterone Modulates Mitochondrial Functions in Human Glioblastoma Cells
Atif, F., Yousuf, S., Espinosa‐García, C., & Stein, D. G. (2021) · Molecular Neurobiology · doi:10.1007/s12035-021-02382-1 · Cited by 12
Grand Challenges for Artificial Intelligence in Molecular Medicine
Emmert‐Streib, F. (2021) · Frontiers in Molecular Medicine · doi:10.3389/fmmed.2021.734659 · Cited by 14
“Of particular interest are studies that clarify the understanding of problems of widely used methods or approaches (Ioannidis, 2005; Tripathi et al., 2013; Wasserstein and Lazar, 2016).”
Stedall, P. M., Spencer‐Smith, M. M., Mainzer, R., Treyvaud, K., Burnett, A., Doyle, L. W., Spittle, A. J., & Anderson, P. J. (2022) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2022.03.013 · Cited by 11
Oliver, A. P., Bell, L. A., Agley, J., Bixler, K., Hulvershorn, L., & Adams, Z. W. (2022) · La Clinica pediatrica · doi:10.1177/00099228221107816 · Cited by 11
Interpreting Results from Statistical Hypothesis Testing: Understanding the Appropriate P-value
Tsushima, E. (2022) · Physical Therapy Research · doi:10.1298/ptr.r0019 · Cited by 11
Vail, E. A., & Avidan, M. S. (2022) · British Journal of Anaesthesia · doi:10.1016/j.bja.2022.06.023 · Cited by 14
Zhang, Z., Li, N., Buckley, J. P., Cecil, K. M., Chen, A., Eaton, C. B., Kalkwarf, H. J., Lanphear, B. P., Yolton, K. A., & Braun, J. M. (2022) · Pediatric Obesity · doi:10.1111/ijpo.12979 · Cited by 12
“Moreover, we focused on the precision and magnitude of the associations and did not specify a threshold for statistical significance, as recommended by the American Statistical Association and others.(43,44) Lastly, our analyses adjusted for a comprehensive set of potential confounders, but unmeasured confounders, suc…”
MethodThe Impact of Non-Interest Income on the Performance of Commercial Banks in the ASEAN Region
Phan, T. T. H., An, P. T. H., Le, H. A., et al. (2022) · Journal of risk and financial management · doi:10.3390/jrfm16010018 · Cited by 11
“Utilizing p -values to test a hypothesis has been criticized for decades (Wasserstein and Lazar 2016).”
MethodMeta-study of sensitivity analysis in solar renewable energy application
Karim, A. R. A., & Mohammad, R. (2023) · Progress in Energy and Environment · doi:10.37934/progee.23.1.1425 · Cited by 11
Yang, J., Shu, L., Duan, H., & Li, H. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104372 · Cited by 11
Spatial niche segregation between bird species in the Białowieża primeval forest (NE Poland)
Karpińska, O., Kamionka-Kanclerska, K., Czortek, P., Dyderski, M., & Czeszczewik, D. (2023) · Forest Ecosystems · doi:10.1016/j.fecs.2023.100129 · Cited by 10
Cybersecurity in SMEs – Drivers of Cybercrime, Insufficient Equipment and Prevention
Kappe, M., Härting, R.-C., Karg, C., & Deffner, D. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2023.10.358 · Cited by 13
Fróes, R. D. S. B., Andrade, A. R., Faria, M. A. G., de Souza, H. S. P., Parra, R. S., Zaltman, C., dos Santos, C. H. M., Bafutto, M., Quaresma, A. B., Santana, G. O., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-54332-1 · Cited by 11
Aggerbeck, M. R., Frøkjær, E. E., Johansen, A., Ellegaard‐Jensen, L., Hansen, L. H., & Hansen, M. A. (2024) · Environmental Research · doi:10.1016/j.envres.2024.119242 · Cited by 15
An empirical study of fault localization in Python programs
Rezaalipour, M., & Furia, C. A. (2024) · Empirical Software Engineering · doi:10.1007/s10664-024-10475-3 · Cited by 14
Yland, J. J., Huybrechts, K. F., Wesselink, A. K., Straub, L., Chiu, Y., Seely, E. W., Patorno, E., Bateman, B. T., Mogun, H., Wise, L. A., et al. (2024) · Diabetes Care · doi:10.2337/dc23-2056 · Cited by 11
Xu, Y., Derington, C. G., Addo, D. K., He, T., Jacobs, J. A., Mohanty, A. F., An, J., Cushman, W. C., Ho, P. M., Bellows, B. K., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.124.036557 · Cited by 11
“As recommended by statistical experts, 29 we performed minimal hypothesis testing for 3 reasons: (1) Given our large sample size, P values become mean-ingless because any trivial differences can be detected as statistically significant; (2) The typical significance level of 0.05 is arbitrary, and…”
InfluentialPFAS Exposure is Associated with a Lower Spermatic Quality in an Arctic Seabird
Humann‐Guilleminot, S., Blévin, P., Gabrielsen, G. W., Herzke, D., Nikiforov, V. A., Jouanneau, W., Moe, B., Parenteau, C., Helfenstein, F., & Chastel, O. (2024) · Environmental Science & Technology · doi:10.1021/acs.est.4c04495 · Cited by 11
Cerebrovascular Function in Sporadic and Genetic Cerebral Small Vessel Disease
Stringer, M. S., Blair, G. W., Kopczak, A., Kerkhofs, D., Thrippleton, M. J., Chappell, F. M., Maniega, S. M., Brown, R., Shuler, K., Hamilton, I. F., et al. (2024) · Annals of Neurology · doi:10.1002/ana.27136 · Cited by 11
Chasen, A., Borrego, M. J., Koolman, E., Landgren, E., & Tripp, H. C. (2025) · Journal of Engineering Education · doi:10.1002/jee.20627 · Cited by 12
“We acknowledge p -values as imperfect indicators of the strength of evidence (Wasserstein & Lazar, 2016), yet we include them in the tables where available following traditionally used ranges for reporting as the most meaningful way to consistently summarize the findings.”
Puvvula, J., Hwang, W., McCandless, L. C., Xie, C., Braun, J. M., Vuong, A. M., Oulhote, Y., Schisterman, E. F., Shinohara, R. T., Booij, L., et al. (2025) · Environment International · doi:10.1016/j.envint.2025.109298 · Cited by 13
Zhu, X., Du, X., Zhu, Y., Zhou, L., Liu, C., Niu, Y., Zhang, Q., Jiang, Y., Kan, H., & Chen, R. (2025) · Environment International · doi:10.1016/j.envint.2025.109495 · Cited by 13
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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