The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index; none of the 1 sources its claims cite is checked for support yet.
The ASA Statement on p -Values: Context, Process, and Purpose
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24 Own interpretation · 2 No basis given · 1 No full text of the sources
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The widespread use of”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Statistical significance is not equivalent to scientific, human, or economic significance.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, a p-value near 0.05 taken by itself offers only weak evidence against the null hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, identical estimated effects will have different p-values if the precision of the estimates differs.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A p-value provides one approach to summarizing the incompatibility between a particular set of data and a proposed model for the data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Conducting multiple analyses of the data and reporting only those with certain p-values (typically those passing a significance threshold) renders the reported p-values essentially uninterpretable.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Whenever a researcher chooses what to present based on statistical results, valid interpretation of those results is severely compromised if the reader is not informed of the choice and its basis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The smaller the p-value, the greater the statistical incompatibility of the data with the null hypothesis, if the underlying assumptions used to calculate the p-value hold.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Valid scientific conclusions based on p-values and related statistics cannot be drawn without at least knowing how many and which analyses were conducted, and how those analyses (including p-values) were selected for reporting.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 10
- It may state two separate claims as one. 10
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This has led to some scientific journals discouraging the use of p-values, and some scientists and statisticians recommending their abandonment, with some arguments essentially unchanged since p-values were first introduced.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The statistical community has been deeply concerned about issues of reproducibility and replicability of scientific conclusions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While the p-value can be a useful statistical measure, it is commonly misused and misinterpreted.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A conclusion does not immediately become”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All these measures and approaches rely on further assumptions, but they may more directly address the size of an effect (and its associated uncertainty) or whether the hypothesis is correct.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The validity of scientific conclusions, including their reproducibility, depends on more than the statistical methods themselves.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is a statement about data in relation to a specified hypothetical explanation, and is not a statement about the explanation itself.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Researchers should recognize that a p-value without context or other evidence provides limited information.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Likewise, a relatively large p-value does not imply evidence in favor of the null hypothesis; many other hypotheses may be equally or more consistent with the observed data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This incompatibility can be interpreted as casting doubt on or providing evidence against the null hypothesis or the underlying assumptions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Appropriately chosen techniques, properly conducted analyses and correct interpretation of statistical results also play a key role in ensuring that conclusions are sound and that uncertainty surrounding them is represented properly.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Misunderstanding or misuse of statistical inference is only one cause of the”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
What the sources say
- Not checked — no full text of the sourcecites Peng 2015 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Smaller p-values do not necessarily imply the presence of larger or more important effects, and larger p-values do not imply a lack of importance or even lack of effect.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In view of the prevalent misuses of and misconceptions concerning p-values, some statisticians prefer to supplement or even replace p-values with other approaches.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
There is widespread consensus in the statistical community on the principles articulated in the ASA statement.
“according to widespread consensus in the statistical community”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While the large scale of the Tabula Muris Senis dataset provides substantial power to predict subtle changes in LR interactions, the biological complexity, dependencies among communication pairs, and multiple testing burden require that these p-values be interpreted within a broader biological and statistical context [33].”
From Quantitative profiling of lifespan-dependent cell-cell communication potential reveals dynamic ligand-receptor network shifts across mouse tissues (2026) · cites this paper as [33]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These types of incorrect descriptions contribute to confirmation bias, overinterpretation of results, and reporting correlation as implied causation (Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“This is especially true of relatively large-sample-size studies (as most learning analytics studies are), which are likely to obtain statistically significant findings in relatively small variations in measures such as GPA (Field 2017; Salkind 2016 Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
In the citing paper
“In 2016, the American Statistical Association released a statement on statistical significance and the P value with six principles underlying the proper use and interpretation of this statistical tool (77).”
From Misrepresentation and distortion of research in biomedical literature (2018) · cites this paper as [77]
In the citing paper
“Although we also present p values for exploratory analyses, we refrain from labeling any of them as statistically significant, following best-practice recommendations for statistical analysis [43].”
From Comparing quality of reporting between preprints and peer-reviewed articles in the biomedical literature (2020) · cites this paper as [43]
In the citing paper
“Contrary to IJE author recommendations and recent guidance from the American Statistics Society, 16 Gao et al. largely base their conclusions on findings with a P -value equivalent to < 0.05 after multiple testing.”
From Commentary: Two-sample Mendelian randomization: opportunities and challenges (2016) · cites this paper as [16]
In the citing paper
“Following guidance,50 we focused on 95% CIs, rather than statistical significance. For example, unlike conventional interpretations, we did not outright interpret an effect estimate “non‐significant” if the lower or upper bound of the 95% CI was slightly above/below the null value; we interpreted them as “suggestive” of an effect.”
From Third‐wave cognitive behaviour therapies for weight management: A systematic review and network meta‐analysis (2020) · cites this paper as [50]
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Meier, M., & Bigler, C. (2023) · doi:10.5194/egusphere-2022-1423 · Cited by 3
Stuedlein, A. W., Dadashiserej, A., & Jana, A. (2023) · PEER · doi:10.55461/zkvv5271 · Cited by 3
White, M., & Stovner, R. B. (2023) · doi:10.31219/osf.io/w7e8q · Cited by 3
Shao, R., Su, L., Wang, P., Han, X., Wang, T., Dai, J., Gu, Y., Luo, J., Deng, L., & Liu, J. (2023) · Research Square · doi:10.21203/rs.3.rs-3455102/v1 · Cited by 3
Piedra, L. M., Zhong, S., Howe, M. J. K., Compernolle, E. L., & Iveniuk, J. (2024) · Research Square · doi:10.21203/rs.3.rs-4178612/v1 · Cited by 3
Best, A. M., Lang, T. A., Greenberg, B. L., Gunsolley, J. C., Ioannidou, E., & _, _. (2024) · The Angle Orthodontist · doi:10.2319/ohstat_guidelines.1 · Cited by 2
Statistical Models for the Analysis of Optimization Algorithms With Benchmark Functions
Mattos, D. I., Bosch, J., & Olsson, H. H. (2021) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2021.3081167 · Cited by 27
“ample size in the p-value [9]. (3) Lack of information regarding the null hypothesis [9]–[11]. (4) Misinterpretation of the actual meaning of the p-value (including by instructors in statistics) [11]–[13]. (5) Misinterpretation of the meaning of confidence intervals [14], [15]. (6) Lack of transparency in the reporting…”
Backgroundp value variability and subgroup testing
Horgan, G. W. (2021) · European Journal of Nutrition · doi:10.1007/s00394-021-02498-z · Cited by 2
Rahman, M. T., López-Iglesias, D., Sierra-Padilla, A., García‐Guzmán, J. J., Aguilera, L. C., Bellido-Milla, D., & Santander, J. M. P. (2022) · Chemosensors · doi:10.3390/chemosensors10080316 · Cited by 2
Randomised Controlled Trial Evaluating the Strengths Model Case Management in Hong Kong
Tse, S. S.-K., Yu, C. H., Yuen, W. W. Y., Ng, C. S. M., Lo, I. W.-K., Fukui, S., Goscha, R. J., Chan, S. H., Wan, E., Wong, S., et al. (2022) · Research on Social Work Practice · doi:10.1177/10497315221118550 · Cited by 2
Serbanescu, I., Schramm, E., Walter, H., Schnell, K., Zobel, I., Drost, S., Fangmeier, T., Normann, C., & Schoepf, D. (2023) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-023-01672-0 · Cited by 2
“We abstained from calculating and including statistical significance of interaction effects between the treatment variable and the baseline variables as a further selection criterion for a baseline variable to be used for the compilation of M* [28].”
MethodWhite, M., & Stovner, R. B. (2024) · Collabra Psychology · doi:10.1525/collabra.121436 · Cited by 7
Bayesian inference and consumer behavioral theory
Hofacker, C. F., Nguyen, H. N. L., & Fina, M. (2024) · Psychology and Marketing · doi:10.1002/mar.22095 · Cited by 3
Shanahan, M. E., Austin, A. E., Durrance, C. P., Martin, S. L., Runyan, D. K., & Runyan, C. W. (2024) · Journal of Family Violence · doi:10.1007/s10896-024-00750-8 · Cited by 3
“In line with guidance from the American Statistical Association, we focus on the magnitude of the point estimate for the RR and the width and location of the corresponding 95% CI when interpreting our results (Wasserstein & Lazar, 2016).”
Siddique, A. B., Shaw, B. P., Dwyer, J. T., Fields, D. A., Fontaine, K. R., Hand, D. J., Schekman, R. W., Alberts, J. R., Locher, J. L., & Allison, D. B. (2024) · Science and Engineering Ethics · doi:10.1007/s11948-024-00517-w · Cited by 2
“The practice of “data dredging” (Wasserstein & Lazar, 2016), where investigators search for any significant result without a prespecified research question, can lead to misleading reports because of the likelihood that statistically significant results can almost always be found with large sample…”
BackgroundCinzori, M. E., Nicol, M., Dewald, A., Goodrich, J. M., Zhou, Z., Gardiner, J. C., Kerver, J. M., Dolinoy, D. C., Talge, N. M., & Strakovsky, R. S. (2024) · Current Zoology · doi:10.1093/eep/dvae021 · Cited by 2
To be aware or not aware: Do intrusions with and without meta-awareness differ?
Keeping, C. A., Nixon, R. D. V., Bridgland, V. M. E., & Takarangi, M. K. T. (2024) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2024.102002 · Cited by 3
Kumar, A., Kumar, P., & Saha, S. K. (2024) · Transport in Porous Media · doi:10.1007/s11242-024-02143-3 · Cited by 2
“However, according to a few studies, the significance of the features can be considered up to the p -value 0.05 (Wasserstein and Lazar 2016).”
InfluentialMorcos, M., Celis‐Aguilar, E., Zhou, A. S., Ahanotu, A., Teng, S. E., Randolph, G. W., Schmalbach, C. E., & Shin, J. J. (2024) · Otolaryngology · doi:10.1002/ohn.1078 · Cited by 2
Gilbertson‐White, S., Albashayreh, A., Ji, Y., Bandyopadhyay, A., Zeinali, N., & Cherwin, C. H. (2024) · Applied Clinical Informatics · doi:10.1055/s-0044-1791820 · Cited by 2
“34 A further bene fi t of AIC is the ability to handle both nested and non-nested models, 35 which allows for consideration of all variable subsets, providing both a statistically sound and meaningful model.”
Spatial Phylogenetics with Continuous Data: An Application to California Bryophytes
Kling, M. M., González-Ramírez, I. S., Carter, B., et al. (2026) · Systematic Botany · doi:10.1600/036364426x17703284494638 · Cited by 2
Nillni, Y. I., Schildroth, S., Yland, J. J., Brown, H. L., Wesselink, A. K., & Wise, L. A. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.01.088 · Cited by 2
Statistical Design of Experiments Enables Rapid Exploration of Perfluorobutane Sulfonate Degradation
Gaines, R. N., LaFond, J. A., Krawchuck, J. A., Bays, N., Kruse, S. M., & Kruichak, J. N. (2025) · ECS Advances · doi:10.1149/2754-2734/adb865 · Cited by 2
“10,15 Parameter and parameter range determination.”
The Q 1 Q 2 Q 3 Workflow for Statistics and Data Science Collaborations
Vance, E. A., Trumble, I. M., Alzen, J. L., & House, L. (2025) · Journal of Statistics and Data Science Education · doi:10.1080/26939169.2025.2475775 · Cited by 3
Dona, A. C., Jewett, P. I., Davidson, S., et al. (2025) · Gynecologic Oncology Reports · doi:10.1016/j.gore.2025.101723 · Cited by 2
“We analyzed the data for our study in the Controlled Tier of the All of Us Researcher Workbench.”
Pitzen, J., Lawler, J. M., Chow, C. M., Arble, E. P., & Huth‐Bocks, A. C. (2025) · British Journal of Developmental Psychology · doi:10.1111/bjdp.12560 · Cited by 5
Suzuki, J. (2025) · Physiological Reports · doi:10.14814/phy2.70341 · Cited by 3
“The statement on p values by the American Statistical Association (Wasserstein & Lazar, 2016) highlighted the widespread misuse and misunderstandings surrounding p values derived from null hypothesis significance testing (NHST).”
Bayesian Multilevel Modeling for the Intersections of Race, Gender, and Class
Much, M. (2025) · Political Research Quarterly · doi:10.1177/10659129251335233 · Cited by 3
“Using Bayesian methods can also show statistical uncertainty more candidly as an alternative to the p -value (Wasserstein, Schirm, and Lazar, 2019; Wasserstein and Lazar 2016).”
A Unified Framework for Residual Diagnostics in Generalized Linear Models and Beyond
Liu, D., Lin, Z., & Heping Zhang, D. (2025) · Journal of the American Statistical Association · doi:10.1080/01621459.2025.2504037 · Cited by 2
“…issues in GLMs for discrete data: The methodological developments are partially driven by the increasingly easier access to larger samples of data, in which situation traditional goodness-of-fit tests are likely to lead to rejection of the hypothesis of a perfect fit (Wasserstein and Lazar 2016).”
Simmons, E., Singh, K., Wood, M. E., et al. (2025) · Journal of Midwifery & Women s Health · doi:10.1111/jmwh.13776 · Cited by 2
Pietras, M., Dyderski, M. K., Horodecki, P., et al. (2025) · Forest Ecology and Management · doi:10.1016/j.foreco.2025.122882 · Cited by 2
Chen, Y.-C., Liu, W., Liu, H.-R., Chang, H.-R., Chen, P.-W., & Liu, A. (2025) · Diagnostics · doi:10.3390/diagnostics15121474 · Cited by 2
“In accordance with the American Statistical Association’s 2016 guidelines, we also clarified the interpretation of p -values in the range of 0.05 to 0.10 as potential trends, particularly in the context of exploratory or small-sample studies [41].”
InfluentialTrends of leading pollutant in a highly polluted global city: processes involved
Radhadevi, L., Bandaru, M., Yarragunta, Y., et al. (2025) · Environmental Monitoring and Assessment · doi:10.1007/s10661-025-14243-8 · Cited by 2
“This decision aligns with recent discussions on the subject (Amrhein et al., 2019; Wasserstein & Lazar, 2016).”
Halabi, S., & Guo, S. (2025) · European Urology · doi:10.1016/j.eururo.2025.06.015 · Cited by 2
Urban, R. W., Martin, S. D., Bailey, S., Rivera, N., Lim, M. L. C., & Bracco, S. (2025) · Worldviews on Evidence-Based Nursing · doi:10.1111/wvn.70054 · Cited by 2
Siri, A., & Combary, O. S. (2025) · Economies · doi:10.3390/economies13070202 · Cited by 2
Amon, C., Dyderski, M. K., Oettel, J., Schueler, S., Essl, F., & Lapin, K. (2025) · Forest Ecology and Management · doi:10.1016/j.foreco.2025.122979 · Cited by 3
Adolescents’ knowledge of and confidence in vaccines improves with board game play
Kantorski, B., Bruzdewicz, K., Fedje, K., et al. (2025) · Discover Education · doi:10.1007/s44217-025-00683-4 · Cited by 2
“We also calculated a standardized effect size for each test to complement the p values [50].”
Survival-inferred fragility of statistical significance in phase III oncology trials
Sherry, A. D., Liu, Y., Msaouel, P., Lin, T. A., Koong, A., Lin, C. S., Jaoude, J. A., Patel, R. R., Kouzy, R., Alam, M. B. E., et al. (2025) · npj Precision Oncology · doi:10.1038/s41698-025-01024-2 · Cited by 3
Rubber tapping of Yunyan 77−4 rubber tree in winter and dry season: research on rubber properties
Xu, S., Zeng, Z., Yang, S., et al. (2025) · Journal of Rubber Research · doi:10.1007/s42464-025-00310-9 · Cited by 2
“…the P value refers to the probability that a more extreme outcome of the sample observations obtained will occur when the original hypothesis is true [36], and the smaller the P value, the smaller the probability of the original hypothesis situation occurring, indicating a more significant result.”
The Role of Phonological Factors in the Processing of Polish Phonotactics
Orzechowska, P., Porębski, A., & Nowak, M. (2025) · Language and Speech · doi:10.1177/00238309251327671 · Cited by 2
Alif, F. K., Ali, N., & Safari, M. A. M. (2025) · Mathematical Modeling and Computing · doi:10.23939/mmc2025.03.819 · Cited by 2
An Assessment on Threshold Selection for Generalized Pareto Distribution using Goodness of Fit
Alif, F. K., Ali, N., & Safari, M. A. M. (2025) · Malaysian Journal of Mathematical Sciences · doi:10.47836/mjms.19.3.06 · Cited by 2
Povey, A. C., Bulgin, C. E., & Gruber, A. (2025) · Surveys in Geophysics · doi:10.1007/s10712-025-09906-7 · Cited by 2
Chan, W. N., Ye, F., Ho, M., & Lee, J. J. (2025) · Nursing and Health Sciences · doi:10.1111/nhs.70236 · Cited by 4
Mulder, J., Pfadt, J. M., & Wagenmakers, E. (2025) · Behavior Research Methods · doi:10.3758/s13428-025-02846-5 · Cited by 2
“In the last decades, classical significance testing using Fish-erian p values has been under severe scrutiny (Berger & Delampady, 1987; Sellke et al., 2001; Wagenmakers, 2007; Wasserstein & Lazar, 2016; Benjamin et al., 2018, among many others).”
Li, H., Liu, Y., Du, J., & Pan, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3624627 · Cited by 2
“The probability level was set at 0.05, consistent with established norms in the social sciences [111], [112].”
InfluentialE2P Simulator: An Interactive Tool for Estimating Real-World Predictive Utility of Research Findings
Karvelis, P., & Diaconescu, A. O. (2025) · The Journal of Open Source Software · doi:10.21105/joss.08334 · Cited by 2
Adams, J., Klein, C., Ludwig, S., Stosch, C., Vogel, K., Bauer, N. H., Bruns, C. J., & Datta, R. R. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1715561 · Cited by 3
“This conventional threshold aligns with current recommendations in biomedical and educational research (21).”
Ground motion models for Campi Flegrei (Italy)
Scala, A., Strumia, C., Cito, P., et al. (2025) · Bulletin of Earthquake Engineering · doi:10.1007/s10518-025-02315-6 · Cited by 2
“05) , particularly for PGA, PGV and short period SAs, suggesting that they do not have a statistically meaningful influence on IM (Wasserstein and Lazar 2016).”
Bergh, D. D., Powell, R. G., Zhao, Y., & Schwab, A. (2025) · Strategic Organization · doi:10.1177/14761270251410355 · Cited by 2
Willis, S. A., Alruwaili, A., Hartescu, I., Deighton, K., Goodwin, C., Henson, J. J., Thackray, A. E., Stensel, D. J., & King, J. A. (2025) · Appetite · doi:10.1016/j.appet.2025.108428 · Cited by 2
EHLAN, K. B., Richardson, Y., Lare, Y., et al. (2025) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2025.108836 · Cited by 2
Adegoke, A., Akanmu, A. A., Abraham, Y. S., & Nnaji, C. A. (2025) · Journal of Architectural Engineering · doi:10.1061/jaeied.aeeng-2041 · Cited by 4
Assessment and biomarker exploration of chronic pain using wearable EEG device
Chen, Y., Tian, Y., Zhou, H., Xu, J., Sun, Y., Zhao, C., & Liu, H. (2025) · Discover Sensors · doi:10.1007/s44397-025-00030-0 · Cited by 6
Z-Drug Use in the First Trimester of Pregnancy and Risk of Congenital Malformations
Fung, K., Straub, L., Bateman, B. T., Hernández–Dı́az, S., Brill, G., Zhu, Y., Cohen, L. S., Gray, K. J., & Huybrechts, K. F. (2025) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2025.3874 · Cited by 2
The perils of multiple statistical tests: controlling for false positives
Sidebotham, D. A., & Chen, X. (2025) · British Journal of Anaesthesia · doi:10.1016/j.bja.2025.11.008 · Cited by 2
Jiang, X., Li, J., Wang, C., Yao, H., Du, Y., Gao, M., Zhang, F., & Wang, S. (2025) · Journal of Remote Sensing · doi:10.34133/remotesensing.0940 · Cited by 4
Reporting guidelines for single-case experimental design research: Recommendations for data analysis
Kratochwill, T. R., Ferron, J. M., & Levin, J. R. (2026) · Journal of School Psychology · doi:10.1016/j.jsp.2025.101528 · Cited by 3
Matthews, R. A. (2026) · Journal of the Royal Society of Medicine · doi:10.1177/01410768261419062 · Cited by 2
Agarwal, A., Santesso, N. A., Agoritsas, T., Guyatt, G. H., & Brignardello‐Petersen, R. (2026) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2026.112206 · Cited by 2
Kirkland, S., Tran, P., Aziz, F. N., Banerjee, P., & Kuehl, M. W. (2026) · European Journal of Cardiovascular Nursing · doi:10.1093/eurjcn/zvag058 · Cited by 2
The Effects of Digital Detox on Digital Phobias, Motivation, Self-Efficacy, and Academic Performance
Özbay, Ö., Sarıkahya, S. D., & Özbay, S. Ç. (2026) · Participatory Educational Research · doi:10.17275/per.26.26.13.2 · Cited by 3
Statistical Stockholm syndrome: the statistical significance myth is the problem
Rigdon, E. E. (2026) · Journal of Marketing Analytics · doi:10.1057/s41270-026-00474-2 · Cited by 2
Resource Substitution: Local Governments' Issue Attention and Policy Reinvention
Zhang, Y., Yao, Y., & Yang, K. (2026) · Policy Studies Journal · doi:10.1111/psj.70113 · Cited by 3
Hershey, M. S., Anthony, C., Pacheco, M. B., Ugarte-Abollado, C., Enwright, C., & Bohlin, K. E. (2026) · Journal of Moral Education · doi:10.1080/03057240.2026.2637804 · Cited by 2
Demystifying machine learning approaches in digital bone imaging using microCT and HRpQCT
David, M., Williams, K., Constantine, E. P., et al. (2026) · Bone Reports · doi:10.1016/j.bonr.2026.101911 · Cited by 2
“…parametric and nonparametric testing), which increases the risk of both type 1 and type 2 errors when making multiple comparisons with increased numbers of knowingly, or potentially, interrelated parameters (Coulombe et al., 2021a; Neeteson et al., 2024; Albers, 2019; Wasserstein and Lazar, 2016).”
Attanayake, C. P., Kasmerchak, C. S., Villamil, M. B., Indorante, K., Eldessouky, S. E. I., & Margenot, A. J. (2026) · Applied Soil Ecology · doi:10.1016/j.apsoil.2026.107014 · Cited by 3
Batista, P. K. A., Montenegro, M. V., Gaelzer, G. C., Molinari, M. E., Malik, M., Silva, R. R. A. D. S., de Lucena, L. A., Bacca, C. D. O. F., & Giorgi, J. M. (2026) · Thrombosis Research · doi:10.1016/j.thromres.2026.109735 · Cited by 3
Худолій, О. М., Іващенко, О. В., & Khudolii, M. (2026) · Physical Education Theory and Methodology · doi:10.17309/tmfv.2026.4.01 · Cited by 4
“Similar limitations have been repeatedly identified in methodological literature as one of the major causes of the low cumulative value of applied research (Glasziou et al., 2014; Wasserstein & Lazar, 2016).”
Carter, D. B. (2026) · Behavior Research Methods · doi:10.3758/s13428-026-03144-4 · Cited by 3
“Consistent with broader reporting guidance emphasizing transparency and estimation-based inference (Appelbaum et al., 2018; Wasserstein & Lazar, 2016), the present paper provides a set of practical recommendations for strengthening distal outcome reporting in mixture modeling applications.”
Gang Warfare: What are the criteria for deriving assertions from facts in science?
Weiss, K. M. (2016) · Evolutionary Anthropology Issues News and Reviews · doi:10.1002/evan.21509 · Cited by 2
Are New York City Drivers more Likely to get a Ticket at the End of the Month?
Auerbach, J. (2017) · Significance · doi:10.1111/j.1740-9713.2017.01053.x · Cited by 2
Lowering the P Value Threshold
Wei, Y., & Chen, F. (2018) · JAMA · doi:10.1001/jama.2018.8721 · Cited by 2
The Phaistos Disk: A New Way of Viewing the Language Behind the Script
Davis, B. (2018) · Oxford Journal of Archaeology · doi:10.1111/ojoa.12151 · Cited by 2
Not p-Values, Said a Little Bit Differently
Startz, R. (2019) · Econometrics · doi:10.3390/econometrics7010011 · Cited by 2
“The American Statistical Association statement on “Statistical Significance and P-values” (Wasserstein and Lazar 2016) aimed at reminding the statistics community about a number of pitfalls that are commonly fallen into, in the everyday use of p-values.”
BackgroundInfluential
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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