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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Claims the paper makes
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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Appendix B. Exemplary material for communicative tasks
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de Guzman, C. N., Pinedo, P. J., Yu, H., et al. (2026) · Dairy · doi:10.3390/dairy7040058
“Because our emphasis was not hypothesis testing, we follow Wasserstein and Lazar [33] who advise that business decisions should not be based only on whether a p -value passes a specific threshold.”
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Appendix D. Example interview with advanced learner
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Appendix C. Example interviews with beginning learners
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Turn-Taking in Second Language Acquisition
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Kovačević, A. B., Ilić, D., Meštrić, U., Cerović, M. S., Bonis, N. D., Popović, L. Č., Simić, S., Fatović, M., Hernández-García, L., Schneider, D. P., et al. (2026) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/ae8444
Appendix A. Questionnaire for stimulus design
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Heuvelman, F., van Erpecum, C.-P. L., Bornioli, A., García‐Gómez, P., Mölenberg, F. J. M., Beulens, J. W. J., & den Braver, N. R. (2026) · Environment International · doi:10.1016/j.envint.2026.110449
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Hollósy, Z., & Bacsi, Z. (2026) · Agriculture · doi:10.3390/agriculture16161725
Speech analysis for acute decompensated heart failure: reporting a pilot study in Germany
Triantafyllopoulos, A., Mayr, W., Batliner, A., et al. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1885715
Darılmaz, M. C. (2026) · Climatic Change · doi:10.1007/s10584-026-04274-6
“With roughly 20,000 window–species combinations, signifi - cance is guaranteed for effects of no practical size (Wasserstein and Lazar 2016).”
Fully, P. L., Wilkins, D., & Dahn, B. T. (2026) · Research Square · doi:10.21203/rs.3.rs-10343485/v1
Khoury, G., Deen, L., Lund, L. C., Batzella, E., Turner, M. C., Jensen, G. B., Jensen, T. K., & Tøttenborg, S. S. (2026) · Toxics · doi:10.3390/toxics14080722 · Cited by 1
“We will interpret results by evaluating the magnitude, direction, and precision of effect estimates rather than relying solely on binary significance testing, consistent with recommendations from authoritative sources [29].”
The Gunas personality framework: Associations with values, virtues, and risk-taking behaviour
Nanda, A., Mulla, Z. R., Sachar, S., & Krishnan, V. R. (2026) · IIMB Management Review · doi:10.1016/j.iimb.2026.100702
When AI agrees with us: large language models as amplifiers of scientific bias
Barber, L. A., Chen, V., Kang, E. C., Yuan, V., Mell, S. P., Cecchinato, R., Samartzis, D., & Sima, S. (2026) · European Spine Journal · doi:10.1007/s00586-026-10289-5
Collier, E. S., Harris, K. L., Niimi, J., Lahne, J., & Bendtsen, M. (2026) · Food Quality and Preference · doi:10.1016/j.foodqual.2026.106081
Palaeodiet and palaeoecology of a Late Pleistocene cave bear population in the Romanian Carpathians
Robu, M., Mirea, I. C., Petculescu, A., et al. (2026) · Acta Palaeontologica Polonica · doi:10.4202/app.01291.2025
Help! How do I determine which statistical test is appropriate for my research?
DeDonno, M. A. (2026) · Journal of Further and Higher Education · doi:10.1080/0309877x.2026.2720461
齐秀英 (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7312114
Azooz, R. E. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.124214
Adaptive System for StepMania 5 Students using Large Language Models
Tavares, S. A., Julia, R. M. S., & do Nascimento, M. Z. (2026) · doi:10.1109/segah69272.2026.11653331
Lee, S., Jayne, C., Kim, M. T., et al. (2026) · JSES Reviews Reports and Techniques · doi:10.1016/j.xrrt.2026.100859
“26 Therefore, interpretation of effect size, such as OR, is essential when evaluating study findings.”
Echevarría-Lezcano, C.-D., García-Virgen, J., García-Díaz, N., et al. (2026) · Agriculture · doi:10.3390/agriculture16161800
“Smaller p -values indicate greater incompatibility between the observed data and the null hypothesis under the assumptions of the statistical test; however, the p -value does not quantify the magnitude or practical importance of the difference [60,61].”
Chen, J., Xu, Y., Zhang, D., et al. (2026) · Language Speech and Hearing Services in Schools · doi:10.1044/2026_lshss-25-00194
Shang, M., Ma, X., Xu, Q., Niu, H., Zhao, F., Wang, L., & Shen, D.-F. (2026) · Revista do Instituto de Medicina Tropical de São Paulo · doi:10.1590/s1678-9946202668057
“…discrepancy between the significant p‑values from non‑parametric group comparisons and the low AUCs highlights a critical principle: statistical significance does not necessarily translate into clinical usefulness, especially when the distributions of measured parameters show extensive overlap 25 .”
Wattelez, G., Demaneuf, T., Bertrand-Protat, S., & Galy, O. (2026) · Open Research Europe · doi:10.12688/openreseurope.24052.1
Habib, A., Ballou, A. F., April-Sanders, A., Wickle, K. V., Meyer, M. L., Sotres‐Alvarez, D., Vanterpool, Y., Vladutiu, C. J., Welch, B. M., Graff, M., et al. (2026) · Journal of clinical lipidology · doi:10.1016/j.jacl.2026.08.014
Suyeni, S., & Bakti, S. (2026) · Priviet Social Sciences Journal · doi:10.55942/pssj.v6i7.2166
Brand image, trust, satisfaction, and loyalty among Shopee-using economics students in North Sumatra
Sahara, S., & Syarifah, T. (2026) · Priviet Social Sciences Journal · doi:10.55942/pssj.v6i7.2168
“…available at https://journal.privietlab.org/index.php/PSSJ brand-image confidence interval therefore warrants a cautious statement: the sample does not provide evidence of an independent brand-image association at α = .05, but a small positive effect remains plausible (Wasserstein & Lazar, 2016).”
InfluentialIrawan, S., & Bakti, S. (2026) · Priviet Social Sciences Journal · doi:10.55942/pssj.v6i7.2167
“Results are interpreted using effect direction, magnitude, confidence intervals, and shared variance rather than a simple significant/non-significant dichotomy (Wasserstein & Lazar, 2016).”
Dewi, L. J. E., Pasaribu, F. B., Chung, S. S., et al. (2026) · IEEE International Conference on Big Data and Artificial Intelligence (BDAI) · doi:10.1109/bdai70753.2026.11655124
Tian, X., Fu, W., Gao, Z., Ma, X., & Gao, B. (2026) · BMJ Open · doi:10.1136/bmjopen-2026-121540
“12 In small subgroups, rare outcomes or models containing multiple interaction terms, parameter estimates may become unstable and standard errors may inflate, leading to wider interval estimates and lower statistical efficiency.”
Comprehensive evaluation of helium bubbling for extending storage time in a liquid nitrogen tank
Qu, Z., Li, Y., Song, G., et al. (2026) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2026.132958
Human variation and its influence on fracture outcomes in experimental tibial blunt trauma
Harden, A., Stull, K. E., Kang, Y., et al. (2026) · Journal of Forensic Sciences · doi:10.1111/1556-4029.70444
Aminuddin, M. A. I. M., Zaaba, Z., & Shariff, M. R. M. (2026) · Journal of King Saud University: Computer and Information Sciences · doi:10.1007/s44443-026-01137-z
“It does not establish that the formats perform equally, and it is not evidence that the observed differences are absent (Wasserstein and Lazar 2016).”
Catalfio, A. M., Fetterly, T. L., Wickens, M. M., Robinson, T. E., & Ferrario, C. R. (2026) · Psychopharmacology · doi:10.1007/s00213-026-07152-2
Reading WONDER-01 At the Bedside: A Bayesian Re-Expression of Benefit and Safety
Elbaz, J., Taylor, P., Targownik, L. E., et al. (2026) · Gastroenterology · doi:10.1053/j.gastro.2026.07.039
Hanley‐Cook, G., van der Meulen, E., Beal, T., & Cacau, L. T. (2026) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2026.101495
Koeda, M., HOSOKAWA, E., Kumagai, A., Ishikawa, Y., Date, K., Kyutoku, Y., 下田, 健., Kimura, M., & Dan, I. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1778517
“Dichotomizing results by p values has been argued to distort interpretation (Wasserstein and Lazar, 2016).”
Ergüt, M., Ozbay, S., Karateke, S., & Zontul, M. (2026) · Molecules · doi:10.3390/molecules31173005
“Nevertheless, the p -values were interpreted together with the signs and magnitudes of the estimated coefficients and were not treated as independent measures of scientific or practical importance [41].”
Harahap, F. A., & Triastuti, N. (2026) · Priviet Social Sciences Journal · doi:10.55942/pssj.v6i8.2170 · Cited by 3
“Because significance is one input to inference rather than a decision rule applied in isolation (Wasserstein & Lazar, 2016), coefficient magnitude and interval width are reported alongside the tests.”
Martínez‐Flores, R., Martín-Sobrino, I., Falgàs, N., Grau‐Rivera, O., Suárez‐Calvet, M., Cristi‐Montero, C., Ibáñez, A. M., Fernández‐Lebrero, A., Contador, J., Navalpotro‐Gómez, I., et al. (2026) · GeroScience · doi:10.1007/s11357-026-02487-2 · Cited by 1
Devina, A., & Normansyah, N. (2026) · Priviet Social Sciences Journal · doi:10.55942/pssj.v6i8.2171
“Inference uses a two-tailed α of .05 and is governed by the exact p value rather than by comparison with a tabulated critical value (Wasserstein & Lazar, 2016).”
Purpose-Affirmation: A Novel Intervention for Cultivating Adolescents’ Purpose in Life
Yan, W., Jiang, L., Wang, Y., Chen, Y., Wu, Y., & Kizilcec, R. F. (2026) · Journal of Happiness Studies · doi:10.1007/s10902-026-01081-9
“Effects with p values between 0.05 and 0.10 were reported as exploratory, reflecting the view that such values may indicate suggestive but inconclusive results (Wasserstein & Lazar, 2016).”
InfluentialAtahau, A. D. R., Pakereng, Y. M., & Huruta, A. D. (2026) · Energy Sustainable Development/Energy for sustainable development · doi:10.1016/j.esd.2026.102125
Silva, R. O., & Hernández, P. H. (2026) · medRxiv · doi:10.64898/2026.08.28.26361649
Matsushita, S., Yamazaki, H., Yamada, Y., Ogawa, Y., & Yamamoto, Y. (2026) · PLoS ONE · doi:10.1371/journal.pone.0355726
“We used STATA BE 17 (StataCorp, College Station, TX, USA) for all statistical analyses and reported 95% two-sided CIs [38].”
Sarıtaş, T. B. (2026) · European Journal of Orthopaedic Surgery & Traumatology · doi:10.1007/s00590-026-04949-x
“Because several spectral and demographic associations were examined without a stated multiplicity strategy, the p values should be presented as exploratory rather than confirmatory, with confidence intervals and influence analyses emphasized instead of binary significance [3].”
Response to Hutton et al. letter to the editor
Volpi, J. J., Wolters, L. F., Louwsma, T., et al. (2026) · Journal of Medical Economics · doi:10.1080/13696998.2026.2724713
Krick, J., Vasquez, M. M., O'Reilly, D., et al. (2026) · American Journal of Perinatology · doi:10.1055/a-2950-0669
Yan, S., Li, G., Wang, K., Li, F., Yang, S., & Deng, H. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7398380
The ventilatory response pattern to exercise across the age‐span in healthy adults
Williams, Z. J., Cenerini, G., Schwendinger, F., Knaier, R., Wagner, J., Hull, J. H., & Schmidt‐Trucksäss, A. (2026) · Physiological Reports · doi:10.14814/phy2.71065
“A p - value < 0.05 was considered statistically significant for all analyses (Wasserstein & Lazar, 2016).”
InfluentialWang, Y. (2026) · The American Statistician · doi:10.1080/00031305.2026.2729003
Wydooghe, E., Schutijser, P., Ngan, M. Y. O., Lee, M.-F., Lai, C., Wong, C.-L., Zhao, Z.-H., & Tang, F. M. K. (2026) · Frontiers in Veterinary Science · doi:10.3389/fvets.2026.1846733
“…sizes for these comparisons were calculated using the r statistic and Cliff’s δ Effect sizes are also reported alongside p -values for all primary comparisons to characterize the magnitude of group differences and to guard against spurious Type I error inferences based on p - values alone (25, 26).”
Feng, L., Lee, K. C. S., & Leong, S. (2026) · Behavioral Sciences · doi:10.3390/bs16091568
“…confidence intervals, R 2 and ∆ R 2 , consistency across robustness checks, and theoretical plausibility were considered together, in line with guidance against interpreting p values as stand-alone measures of effect size, importance, or evidential certainty (Wasserstein & Lazar, 2016).”
CLINICAL AND RESEARCH CASE CONCEPTUALIZATIONS USING THE NIH TOOLBOX® COGNITION TESTS
Hook, J. N., Giella, A. K., & Sivan, A. B. (2026) · Wiley eBooks · doi:10.1002/9781394310784.ch7
Discriminating among common probabilistic models for radon data: a Bayesian approach
Escobar, M. D. C. M., Rubiano, J. G., Miquel-Armengol, N., et al. (2026) · Environmental and Ecological Statistics · doi:10.1007/s10651-026-00759-w
Olojede, B. O., Opawole, A., & Onaolapo, J. (2026) · Sustainable Energy Research · doi:10.1186/s40807-026-00267-2
“Following standard econometric conventions, the statistical significance indicators are categorized as highly significant ( p < 0.01), statistically significant ( p ≤ 0.05), and not statistically significant ( p > 0.05) (Wasserstein & Lazar, 2016).”
InfluentialBriceño, C. A., Idowu, O. O., Khong, J. J., et al. (2026) · Ophthalmology · doi:10.1016/j.ophtha.2026.08.039
Chong, G.-H., Yun, J., & Yoo, S. (2026) · Sustainability · doi:10.3390/su18179136
Hamed, L. M. M., Saeed, A. A., Darrag, H. M., et al. (2026) · Environmental Geochemistry and Health · doi:10.1007/s10653-026-03485-1
Tekerlek, H., & Göksülük, M. B. (2026) · Acta cardiologica. Supplementum · doi:10.1080/00015385.2026.2729514
A Unified Scale for Interpreting Quantitative Measurements Across Distributions
Raham, T. F. (2026) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.70569
Schmidt, M., & Parner, E. (2026) · Annals of Epidemiology · doi:10.1016/j.annepidem.2026.110275
Sanchez, A. D. L., Dastgerdi, M. F., Rodríguez-Lescure, Á., et al. (2026) · Journal of Cancer Policy · doi:10.1016/j.jcpo.2026.100808
From Ordered Categories to Defensible Conclusions: A Decision Framework for Likert-Scale Data
Doronila, R. A. (2026) · Measurement Interdisciplinary Research and Perspectives · doi:10.2139/ssrn.7407799
Questions asked and, maybe, answered with Mendelian randomization
Shi, J., Diemer, E. W., & Swanson, S. A. (2026) · American Journal of Epidemiology · doi:10.1093/aje/kwag223
Effect Sizes of Permanently Listed Digital Health Applications (DiGAs) in GermanyPreprint
Fritz, M. S., & Zenner, H. P. (2026) · Research Square · doi:10.21203/rs.3.rs-10879796/v1
Yi, C., Kim, S., & Yun, B.-H. (2026) · Applied Spatial Analysis and Policy · doi:10.1007/s12061-026-10008-z
What P ‐Values Can (and Cannot) Tell Us in Clinical Neurology
Rovetta, A., Biscetti, L., & Mansournia, M. A. (2026) · Movement Disorders · doi:10.1002/mds.70503
Mendes, H., Correia, J. V. S., Salles, M. M. M., Kattan, E., Hernández, G., & Melo, R. (2026) · Critical Care Medicine · doi:10.1097/ccm.0000000000007364
Kendrick, J. S., Shaw, D. A., Jourdain, M., Senn, C., Beyer, H., & Sewell, F. R. (2026) · Frontiers in Toxicology · doi:10.3389/ftox.2026.1854281
“In practice, regulators and scientists increasingly find that the biological context of individual data points is often more meaningful than any statistically significant group mean (Lazar, 2016).”
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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