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
Open accessAbstract
Emeritus of Mathematics and Statistics at
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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.
Cited by
Sorted by citations
Items 4,501–4,600 of 6,272
Why does Researchers Run Behind P Value?
Premanath, M. (2023) · APIK Journal of Internal Medicine · doi:10.4103/ajim.ajim_11_23 · Cited by 1
Factors Affecting Compilable State at Each Keystroke in CS1
Scott, S., Hellas, A., Leinonen, J., & Edwards, J. (2023) · IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET) · doi:10.1109/icse-seet58685.2023.00036 · Cited by 1
Paphitis, K., Pearl, D. L., Berke, O., et al. (2023) · Zoonoses and Public Health · doi:10.1111/zph.13069 · Cited by 1
Ripamonti, E. (2023) · Oxford Review of Education · doi:10.1080/03054985.2023.2230890 · Cited by 1
“A nominal value of 0.05 was set to evaluate the significance of each p -value, which was reported in agreement with the ASA statement (Wasserstein & Lazar, 2016).”
MethodInfluentialMessner, W. (2023) · Journal of International Management · doi:10.1016/j.intman.2023.101056 · Cited by 2
Kondo, T., & Kato, T. (2023) · Transactions of Japan Society of Kansei Engineering · doi:10.5057/jjske.tjske-d-23-00007 · Cited by 1
Survey on Attitudes toward Career Visions for Hospital Pharmacists
Kawazoe, H., Tsuchiya, M., Todo, M., et al. (2023) · YAKUGAKU ZASSHI · doi:10.1248/yakushi.23-00020 · Cited by 1
Stochastik: Leitidee Daten und Zufall
Biehler, R., Engel, J., & Frischemeier, D. (2023) · Springer eBooks · doi:10.1007/978-3-662-66604-3_8 · Cited by 1
The replication crisis in science and its overlap into kinantropology: an introduction
Baloun, L., & Mališ, J. (2023) · Tělesná kultura · doi:10.5507/tk.2023.002 · Cited by 1
Treatment-associated network dynamics in patients with globus sensations: a proof-of-concept study
Imperiale, M. N., Lieb, R., & Meinlschmidt, G. (2023) · Scientific Reports · doi:10.1038/s41598-023-42186-y · Cited by 1
Can metacognitive accuracy be altered through prompting in biology text reading?
Elsner, S., & Großschedl, J. (2023) · European Journal of Psychology of Education · doi:10.1007/s10212-023-00747-9 · Cited by 5
“…by (Doering & Bortz, 2016, pp. 673 – 674) and well-known criticism about the use and interpretation of p -values (e.g., Gardner & Altman, 1986; Wasserstein & Lazar, 2016), we report 95% confidence intervals for mean values and effect sizes in addition to typical p -value interpretation.”
COVID-19 Research and p -Values
Govindarajulu, U. S. (2023) · CHANCE · doi:10.1080/09332480.2023.2264736 · Cited by 1
Nelinson, D. S., Ko, L., & Bass, B. (2023) · Advances in Medical Education and Practice · doi:10.2147/amep.s427663 · Cited by 1
Tada, M., Matano, H., Azuma, H., et al. (2023) · QJM · doi:10.1093/qjmed/hcad242 · Cited by 1
Extreme data compression for Bayesian model comparison
Heavens, A., Mootoovaloo, A., Trotta, R., et al. (2023) · Journal of Cosmology and Astroparticle Physics · doi:10.1088/1475-7516/2023/11/048 · Cited by 1
“…Bayes factor can indicate a preference for one model over another, but not falsify models in absolute terms, and we are not seeking frequentist methods to do this, which typically rely on tail probabilities of p (data | M ) as opposed to posterior model probabilities, p ( M | data) , cf. [38–40].”
BackgroundZhang, Q.-H., & Ni, Y. (2023) · Communication in Statistics- Theory and Methods · doi:10.1080/03610926.2023.2273202 · Cited by 1
“…whether the p -value and the posterior probability of the null hypothesis that are numerically equal mean the right resolution of the JL paradox remains an opening question because the two quantities illustrate probabilities of two fundamentally different events (see Wasserstein and Lazar 2016).”
Testing for signal-to-noise ratio in linear regression: a test under large or massive sample
Kim, J. H., & Ji, P. I. (2023) · Reviews of Management Sciences · doi:10.1007/s11846-023-00706-0 · Cited by 2
“As Wasserstein and Lazar (2016) point out, “any effect, no matter how tiny, can produce a small p -value if the sample size or measurement precision is high enough...”.”
Enhancing learning with a two-page study manual
Jemstedt, A. (2023) · Learning and Instruction · doi:10.1016/j.learninstruc.2023.101852 · Cited by 2
Statistical Methods for Testing Equity of False Non Match Rates Across Multiple Demographic Groups
Schuckers, M. E., Fatima, K., Purnapatra, S., et al. (2023) · International Conference of the Biometrics Special Interest Group (BIOSIG) · doi:10.1109/biosig58226.2023.10346007 · Cited by 1
“These methods are aimed at non-technical audience, such as policymakers, rather than the complicated analysis of variance and p-value approaches taken for similar circumstances by [9] which can be problematic [10].”
MethodPerceptions of Gender in Classrooms and Associated Expectations of Belonging
Ralph, M. C., Pascutto, J., Wright, C., & Martínez, R. P. (2023) · Journal of Interior Design · doi:10.1177/10717641231211544 · Cited by 1
“…for significance (e.g., p < .05), we also heeded calls for more contextualized, nuanced discussions of significance based on both our QuantCrit framework and movements in statistical practice generally (Ho et al., 2019; McShane et al., 2019; Wasserstein & Lazar, 2016; Wasserstein et al., 2019).”
BackgroundStang, A., & Rothman, K. J. (2024) · European Journal of Epidemiology · doi:10.1007/s10654-023-01081-6 · Cited by 1
Qiu, S., Zhang, Y., Hu, Y., & Wang, Y. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385902 · Cited by 1
Audrain, A., Cornu, J., Kerdelhué, G., et al. (2024) · The French Journal of Urology · doi:10.1016/j.fjurol.2024.102592 · Cited by 1
Empirical Bayes factors for common hypothesis tests
Dudbridge, F. (2022) · PLoS ONE · doi:10.1371/journal.pone.0297874 · Cited by 1
Prysmakova, P. (2024) · Journal of Social Entrepreneurship · doi:10.1080/19420676.2024.2303460 · Cited by 2
“Looking for p -values attached to hypotheses has been more closely scrutinised these days (Wasserstein and Lazar 2016; Wasserstein, Schirm, and Lazar 2019).”
Utility of gastrostomy tube placement at the time of pancreaticoduodenectomy
Pather, K., Mobley, E. M., & Awad, Z. T. (2024) · Surgical Endoscopy · doi:10.1007/s00464-024-10735-9 · Cited by 1
“These findings warrant further investigation and should not be taken as lack of evidence [26].”
Feeling disadvantaged? Type of employment contract and political attitudes
Gatskova, K., Pilc, M., & Beręsewicz, M. (2024) · Socio-Economic Review · doi:10.1093/ser/mwae011 · Cited by 1
A validity test for a multivariate linear measurement error model
Kukush, A. G., & Mandel, I. (2024) · Model Assisted Statistics and Applications · doi:10.3233/mas-231494 · Cited by 1
“in fact, they represent a small fraction of all works. This bias strongly contributes into the roots of the actively discussed now “reproducibility crisis” [12] and “statistical significance crisis” [13, 14]. A lot of work for investigating different conditions in a sense of the table 1 lies ahead, in our opinion. In…”
Confidence distributions and hypothesis testing
Melilli, E., & Veronese, P. (2024) · Statistical Papers · doi:10.1007/s00362-024-01542-4 · Cited by 1
“Regrettably, this methodology is not as secure as it may seem, as evidenced by a large literature, see the ASA’s Statement on p -values (Wasserstein and Lazar 2016) and The American Statistician (2019, vol. 73, sup1) for a discussion of various principles, misconceptions, and recommendations…”
Tanjung, M. H., & Varianto, G. (2024) · Jurnal Aplikasi Manajemen · doi:10.21776/ub.jam.2024.022.01.11 · Cited by 1
Experimental Design and Statistics in Animal Research
Högg, T., Willé, D. R., & Bate, S. T. (2024) · Springer eBooks · doi:10.1007/978-981-97-0048-6_3 · Cited by 1
Factors affecting composition of fatty acids in wild-growing forest mushrooms
Stojek, K., Bobrowska‐Korczak, B., Kusińska, B., Czerwonka, M., Decruyenaere, J., Decock, L., Klama, J., Müeller, S., Ponette, Q., Scherer‐Lorenzen, M., et al. (2024) · Mycologia · doi:10.1080/00275514.2024.2325045 · Cited by 2
“To avoid the risk of treating ecologically relevant patterns as statistically not significant, we accounted for the effect size and biological significance of the obtained results rather than for statistical significance (Nakagawa and Cuthill 2007; Wasserstein and Lazar 2016).”
BackgroundChefranov, R. M., Lalomov, A. V., & Chefranova, A. V. (2023) · Геология рудных месторождений · doi:10.31857/s0016777023020016 · Cited by 1
Fujimoto, H., Iida, M., Takeuchi, S., et al. (2024) · Japan Journal of Nursing Science · doi:10.1111/jjns.12599 · Cited by 1
Integrating measures of replicability into scholarly search: Challenges and opportunities
Wu, C., Chakravorti, T., Carroll, J. M., & Rajtmajer, S. M. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3643043 · Cited by 3
“For instance, P7’s statement about p-values showed a common misconception about p-values [113] and, therefore, an incorrect definition of replication.”
BackgroundHeterogeneity, Bayesian thinking, and phenotyping in critical care: A primer
Jones, T. W., Hedrick, T., & Chase, A. M. (2024) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/zxae139 · Cited by 1
Dakin, M., Manneville, F., Langlois, J., Briançon, S., Lecomte, E., Spitz, É., Legrand, K., Böhme, P., Guillemin, F., & Omorou, A. Y. (2024) · British Journal Of Nutrition · doi:10.1017/s0007114524001090 · Cited by 1
“Fourth, the result about the effectiveness of interventions aiming to improve PA on social inequalities of weight status (BMIz) should be taken with caution because absence of evidence is not evidence of absence (43) .”
Developing a Bayesian workshop for full-time staff statisticians
Khalatbari, S. H., Baladandayuthapani, V., Kaciroti, N., et al. (2024) · Journal of Clinical and Translational Science · doi:10.1017/cts.2024.558 · Cited by 1
How Muriel's Tea Stained Management Research Through Statistical Significance Tests
Schwab, A., & Starbuck, W. H. (2024) · Journal of Management Inquiry · doi:10.1177/10564926241257164 · Cited by 1
“Misinterpretation of NHST results has been documented by Amrhein et al. (2019), Armstrong (2007), Cohen (1994), Fidler et al. (2004), Greenland et al. (2016), Oakes (1986), and Wasserstein and Lazar (2016).”
Sánchez, E., García-Ríos, V. N., & Sepúlveda, F. (2024) · Educational Studies in Mathematics · doi:10.1007/s10649-024-10330-8 · Cited by 1
“Misinterpretations of the p -value, for instance, are prevalent not just among students but also among professionals using significance tests (Goodman, 2008; Wasserstein & Lazar, 2016).”
Research design, statistics and soil carbon: Responses to von Haden et al. and Spertus
Bradford, M. A., Polussa, A., Eash, L., Jevon, F. V., Kuebbing, S. E., Rosenzweig, S. T., & Oldfield, E. E. (2024) · Geoderma · doi:10.1016/j.geoderma.2024.116961 · Cited by 1
Best, A. M., Lang, T. A., Greenberg, B. L., et al. (2024) · Journal of Oral and Maxillofacial Surgery · doi:10.1016/j.joms.2024.06.175 · Cited by 1
Jiao, C., Lao, Y., Zhang, W., Braunstein, S. E., Salans, M. A., Villanueva-Meyer, J. E., Hervey‐Jumper, S. L., Yang, B., Morin, O., Valdés, G., et al. (2024) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ad64b8 · Cited by 2
“The p -value is a metric for null-hypothesis significance testing (Montgomery 2019), where the metric measures the significance of the probability of obtaining test results under the assumption that the null hypothesis is correct (Wasserstein and Lazar 2016).”
de la Chica, A. G., Corley, M. K., Spence‐Aizenberg, A., et al. (2024) · American Journal of Primatology · doi:10.1002/ajp.23669 · Cited by 1
Probability Models in Statistical Data Analysis: Uses, Interpretations, Frequentism-as-Model
Hennig, C. M. (2024) · Springer eBooks · doi:10.1007/978-3-031-40846-5_105 · Cited by 2
Guidelines for using financial incentives in software-engineering experimentation
Krüger, J., Çalıklı, G., Bershadskyy, D., Otto, S., Zabel, S., & Heyer, R. (2024) · Empirical Software Engineering · doi:10.1007/s10664-024-10517-w · Cited by 1
A Consumer-Centric Approach for a Sustainable Honey Supply Chain: The Case of Strawberry Tree Honey
Papachristos, I., Anastasiadis, F., Kontopanou, M., et al. (2024) · Sustainability · doi:10.3390/su16166957 · Cited by 1
Dourado, I. C., Magno, L., Leite, B. O., Bastos, F. I., da Mota, J. C., Veras, M. A. D. S. M., & Castejón, M. J. (2024) · Revista Brasileira de Epidemiologia · doi:10.1590/1980-549720240004.supl.1.2 · Cited by 4
Two P or Not Two P: Mendel Random Variables in Combining Fake and Genuine p-Values
Brilhante, M. F., Gomes, M. I., Mendonça, S., et al. (2024) · AppliedMath · doi:10.3390/appliedmath4030060 · Cited by 1
Blalock, D. V., Greene, L., Kane, R. M., Smith, V. A., Jacobs, J., Rao, M., Cohen, A. J., Zulman, D. M., & Maciejewski, M. L. (2024) · Journal of General Internal Medicine · doi:10.1007/s11606-024-09125-7 · Cited by 3
“…assessed characteristics of the 4121 survey respondents (Table 1) and compared them to non-respond-ents on all available EHR covariates using standardized mean differences (SMDs) since they are insensitive to sample size, 44,45 using the “tableone” package in R (version 3.6.0; Table 2).”
InfluentialWood, E. E., Liang, Y., Moon, T., Hill‐Kapturczak, N., Wasserman, A. M., Roache, J. D., Mathias, C. W., Blumenthal, H., & Dougherty, D. M. (2024) · Substance Use & Misuse · doi:10.1080/10826084.2024.2434007 · Cited by 1
“In response to the misuses and misconceptions surrounding p value, we reported both p value and confidence intervals (CIs), as recommended by the American Statistical Association (Wasserstein & Lazar, 2016).”
Mirończuk, M., Müller, A., & Witold Pedrycz, C. (2024) · IEEE Access · doi:10.1109/access.2024.3513550 · Cited by 1
“In most cases, the purpose of evaluation is to assess two different approaches: frequentist [140], [141], [142], [143], [144], [145], [146], [147], [149], [150], [151], [152], [153], [154] and Bayesian [150], [155], [156], [157].”
A logical framework for data-driven reasoning
Baldi, P., Corsi, E. A., & Hosni, H. (2024) · Logic Journal of IGPL · doi:10.1093/jigpal/jzae113 · Cited by 2
“Clearly the p-value is not entirely data-driven, as it features data which in fact one has not seen – see [58] for an extensive discussion on this and related point.”
BackgroundZurovac, J., Shin, E., Earlywine, J. J., et al. (2024) · Journal of Substance Use and Addiction Treatment · doi:10.1016/j.josat.2024.209621 · Cited by 1
McDermott, K. L., Rajzer-Wakeham, K. L., Andres, J. M., Yan, K., Liegl, M., & Schindler, C. A. (2025) · American Journal of Critical Care · doi:10.4037/ajcc2025828 · Cited by 1
Wolves and human‐caused mortality—a reply to Cassidy et al.
Caudill, D., Schmidt, J. H., Frye, G. G., et al. (2025) · Frontiers in Ecology and the Environment · doi:10.1002/fee.2830 · Cited by 1
Proposal for modifying procedures for declaring significant trends in TIMSS
Braun, H. I., von Davier, M., & Chen, J. (2025) · Large-scale Assessments in Education · doi:10.1186/s40536-025-00236-z · Cited by 1
“It has been well documented that, in practice, many initial ‘discoveries’ are not replicated in later studies (Szucs & Ioannidis, 2017; Wasserstein & Lazar, 2016).”
Reverse Fragility Index in Plastic Surgery Randomized Controlled Trials
Ahdoot, R., Benítez, T. M., Wang, C.-W., et al. (2025) · Plastic & Reconstructive Surgery Global Open · doi:10.1097/gox.0000000000006456 · Cited by 1
“4,5 However, the reliance on this P value threshold for interpreting RCT outcomes can be problematic.”
Straub, L., Cox, S. A., Moran, L. V., Ruble, M. W., Aldis, R., Gibbons, J. B., Liu, J., Peloquin, J., Wood, R., Albano, A., et al. (2025) · Psychiatric Services · doi:10.1176/appi.ps.20240187 · Cited by 1
Bultez, A. V., & Seghers, B. (2025) · Journal of Economic Analysis · doi:10.58567/jea04020006 · Cited by 1
Rethinking Suicide Prevention Research – Moving Beyond Traditional Statistical Significance
Griffin, B. A., Hassler, G. W., Sheftall, A. H., Ohana, E., & Ayer, L. A. (2025) · Crisis · doi:10.1027/0227-5910/a000992 · Cited by 1
Domazetoska, I., & Zhao, H. (2025) · Language Learning · doi:10.1111/lang.12710 · Cited by 2
“Recently, the notion of “black-and-white thinking” stemming from null hypothesis testing has gained prominent attention in scholarly discussions (Cumming, 2014; Kruschke & Liddell, 2018; Wasserstein & Lazar, 2016).”
Agreement Evaluation in Statistical Analyses: Misconceptions and Key Features
Lee, S. (2025) · Annals of Laboratory Medicine · doi:10.3343/alm.2024.0685 · Cited by 1
“The P-value represents the probability of obtaining a result at least as extreme as the one observed, assuming that the null hypothesis is true [1].”
Quintana, S. R., von Hippel, F. A., Orozco, M., et al. (2025) · Environmental Pollution · doi:10.1016/j.envpol.2025.126273 · Cited by 1
Newhouse, R., Agley, J., Bakoyannis, G., Ferren, M. D., Mullins, C., Keen, A., & Parker, E. (2025) · BMC Nursing · doi:10.1186/s12912-025-03079-9 · Cited by 1
“The confidence level was set at 0.95 but we report exact p-values [47].”
InfluentialAligning EMR Structure with Treatment Cycles: Enhancing Data Management and CDSS Functionality
Azadi, A., & García‐Peñalvo, F. J. (2025) · Applied Sciences · doi:10.3390/app15105273 · Cited by 1
Roberts, T. A., & Smolkowski, K. (2025) · The Journal of Educational Research · doi:10.1080/00220671.2025.2496313 · Cited by 1
“Wasserstein and Lazar (2016), in the American Statistical Association’s statement on p values, stipulate that “researchers should bring many contextual factors into play to derive scientific inferences, including the design of a study, the quality of the measurements, the external evidence for the…”
InfluentialBoş Zaman Çalışmalarında Farklı İstatistiksel Yaklaşımlar: BAYES Teoremi
Tütüncü, Ö. (2025) · Anatolia Turizm Araştırmaları Dergisi · doi:10.17123/atad.1698985 · Cited by 1
Decision Rules in Frequentist and Bayesian Hypothesis Testing: P-Value and Bayes Factor
Fordellone, M., Schiattarella, P., Nicolao, G. D., et al. (2025) · International Journal of Public Health · doi:10.3389/ijph.2025.1608258 · Cited by 1
“Widespread misusages concerning the p-value encourage statisticians to explore alternative approaches, such as the Bayes Factor [13].”
Partouche, N., Maumy‐Bertrand, M., Chamaraux‐Tran, T., Bertrand, F., Schneider, F., Meyer, N., Solis, M., Fafi‐Kremer, S., Noll, É., & Pottecher, J. (2025) · PLoS ONE · doi:10.1371/journal.pone.0321533 · Cited by 1
“Effect plots [51] based on estimated marginal means (also called least-squares means or predicted marginal means) [52,53] were drawn using the sjPlot package [54].”
Holder, N. D., Batten, A. J., Shiner, B. R., Neylan, T. C., & Maguen, S. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119472 · Cited by 2
Cooper, C., Fahey, K. T., & Jones, R. (2025) · PLoS ONE · doi:10.1371/journal.pone.0324507 · Cited by 1
“To mitigate the well-known limitations of p values [53] we graphically present some results as regression coefficients with confidence intervals to make clear the distinction between effect size and significance.”
Ouyang, Y., Luo, B., Dixon, S. N., Al‐Jaishi, A. A., Devereaux, P. J., Walsh, M. W., Wald, R., Zwarenstein, M., Anderson, S., & Garg, A. X. (2025) · Canadian Journal of Kidney Health and Disease · doi:10.1177/20543581251341710 · Cited by 1
Courey, K. A., & Oswald, F. L. (2025) · Journal of Business and Psychology · doi:10.1007/s10869-025-10044-5
Tanaka, Y., Fujita, H., Kitayama, R., et al. (2025) · Journal of obstetrics and gynaecology research · doi:10.1111/jog.16361 · Cited by 1
Sherry, A. D., Msaouel, P., Miller, A. M., Lin, T. A., Jaoude, J. A., Kouzy, R., Passy, A. H., Meirson, T., Ignatiadis, N., McCaw, Z. R., et al. (2025) · European Journal of Cancer · doi:10.1016/j.ejca.2025.115596 · Cited by 1
A Hybrid PLO-Transformer-CEEMDAN Model for Natural Gas Price Forecasting
Wang, X., Wang, H., Wang, Z., Wu, D., Xue, Y., Ye, L., & Zhang, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3597657 · Cited by 2
“Inline with the statistical reporting standards recommended by the American Statistical Association [47], significance levels in this article are expressed as follows: for p 0.01, for p 0.05, for p 0.10, with no asterisk indicating no statistical significance.”
InfluentialGebremichael, B., Begum, M., Bianco‐Miotto, T., Zhou, S. J., & Lassi, Z. S. (2025) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2025.112422 · Cited by 1
Evidence About Benefits and Risks of Vaccines
Califf, R. M. (2025) · JAMA Cardiology · doi:10.1001/jamacardio.2025.3521 · Cited by 1
Nakhlé, G., Tardif, J., Dubois, A., & LeLorier, J. (2025) · Journal of Cardiovascular Translational Research · doi:10.1007/s12265-025-10703-1 · Cited by 1
“In its 2016 statement, the American Statistical Association (ASA) [1] cautioned against using p -values as the sole basis for scientific inference, highlighting issues such as p-hacking, selective reporting, and overreliance on rigid thresholds.”
Infodemiology of interest in Mukbang on YouTube in Eastern Europe 2020–2025
Siminiuc, R., Țurcanu, D., & Siminiuc, S. (2025) · Discover Social Science and Health · doi:10.1007/s44155-025-00298-y · Cited by 1
“Following current recommendations on GT use, we therefore report descriptive effect-size summaries (absolute and relative change) and refrain from p-values or causal inference [33].”
New Polystochastic Statistical Inference in Social Sciences - Defining new Rules and Thresholds
Opić, S. (2025) · Revija za elementarno izobraževanje · doi:10.18690/rei.4907 · Cited by 1
Spreckelsen, T. F., & van der Horst, M. (2016) · Sociological Research Online · doi:10.5153/sro.4076 · Cited by 1
Strategies to Increase Rigor and Reproducibility of Data in Manuscripts: Reply to Héroux
Yates, B. J. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00646.2016 · Cited by 1
“We are also cognizant that there are disagreements about which experimental details should be reported and how differences in procedures and findings between studies should be evaluated (Morris 2012; Wasserstein and Lazar 2016).”
BackgroundInferential misconceptions and replication crisis
Hirschauer, N., Mußhoff, O., Grüner, S., Frey, U. J., Theesfeld, I., & Wagner, P. (2022) · Epidemiology Biostatistics and Public Health · doi:10.2427/12066 · Cited by 1
Heat treatment of Pennsylvania jasper
Dillian, C. D. (2016) · North American Archaeologist · doi:10.1177/0197693116682082 · Cited by 1
“…this direction, and if a higher p value were set, it would be possible to successfully argue for significance at a p< .1 level (for a discussion of p values in statistics, see Wasserstein and Lazar 2016); however, for the purposes of these experiments, p value was held at the standard p< .05 level.”
MethodPorcher, R. (2017) · Clinical Orthopaedics and Related Research · doi:10.1007/s11999-016-5225-1 · Cited by 1
Respuesta a la carta al Editor
Muriel-Vizcaíno, R., Treviño-Garza, G., Murata, C., et al. (2017) · Acta Pediátrica de México · doi:10.18233/apm38no2pp136-1381367 · Cited by 1
Reviews of Books and Teaching Materials
Ramezan, R. (2017) · The American Statistician · doi:10.1080/00031305.2017.1271242 · Cited by 1
MULT ICRITERIA SYSTEMS OF OPTIMIZAT ION IN AGRO-INDUSTRIAL COMPLEX
Шешунова, Е. В. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201701.067-076 · Cited by 1
The use of intelligent systems for risk management in software projects
Gushchina, O. A. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201702.250-263 · Cited by 1
The use of intelligent systems for risk management in software projects
Tumbinskaya, M. V. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201702.264-288 · Cited by 1
Senin, P. V., Викторович, Р. Н., & Makeykin, A. M. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201702.154-168 · Cited by 1
Optimum design of the metal bellows on the SolidWorks platform
Chugunov, M. V., & Николаевна, П. И. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201702.169-177 · Cited by 1
Wick, J., Yeh, H., & Gajewski, B. J. (2017) · The American Statistician · doi:10.1080/00031305.2016.1247014 · Cited by 1
“By contrast, evidence from frequentist methods is assessed through a p-value which, by definition, is a probability associated with data (both observed and unobserved) given the assumed truth of the null hypothesis and is often misinterpreted (Wasserstein and Lazar 2016).”
BackgroundBayesian Analysis on a Noncentral Fisher–Student’s Hypersphere
Blanc, R. L. (2017) · The American Statistician · doi:10.1080/00031305.2017.1377111 · Cited by 1
Big Sensor Data Acquisition and Archiving with Compression
Lee, D. (2017) · Springer eBooks · doi:10.1007/978-3-319-63917-8_7 · Cited by 1
Nisbet, R., Miner, G. D., & Yale, K. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-416632-5.00020-7 · Cited by 1
O'Donnell, J. L. (2018) · Internal Medicine Journal · doi:10.1111/imj.13723 · Cited by 1
“I Hope I Get It”: impact of Tony Award nominations and wins on Broadway production longevity
Warne, R. T. (2018) · Arts and the Market · doi:10.1108/aam-06-2017-0013 · Cited by 1
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 ›
Are you an author, or do you see a problem with this page? Request a review
