The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index; none of the 1 sources its claims cite is checked for support yet.
The ASA Statement on p -Values: Context, Process, and Purpose
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24 Own interpretation · 2 No basis given · 1 No full text of the sources
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The widespread use of”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Statistical significance is not equivalent to scientific, human, or economic significance.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, a p-value near 0.05 taken by itself offers only weak evidence against the null hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, identical estimated effects will have different p-values if the precision of the estimates differs.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A p-value provides one approach to summarizing the incompatibility between a particular set of data and a proposed model for the data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Conducting multiple analyses of the data and reporting only those with certain p-values (typically those passing a significance threshold) renders the reported p-values essentially uninterpretable.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Whenever a researcher chooses what to present based on statistical results, valid interpretation of those results is severely compromised if the reader is not informed of the choice and its basis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The smaller the p-value, the greater the statistical incompatibility of the data with the null hypothesis, if the underlying assumptions used to calculate the p-value hold.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Valid scientific conclusions based on p-values and related statistics cannot be drawn without at least knowing how many and which analyses were conducted, and how those analyses (including p-values) were selected for reporting.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 10
- It may state two separate claims as one. 10
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This has led to some scientific journals discouraging the use of p-values, and some scientists and statisticians recommending their abandonment, with some arguments essentially unchanged since p-values were first introduced.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The statistical community has been deeply concerned about issues of reproducibility and replicability of scientific conclusions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While the p-value can be a useful statistical measure, it is commonly misused and misinterpreted.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A conclusion does not immediately become”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All these measures and approaches rely on further assumptions, but they may more directly address the size of an effect (and its associated uncertainty) or whether the hypothesis is correct.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The validity of scientific conclusions, including their reproducibility, depends on more than the statistical methods themselves.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is a statement about data in relation to a specified hypothetical explanation, and is not a statement about the explanation itself.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Researchers should recognize that a p-value without context or other evidence provides limited information.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Likewise, a relatively large p-value does not imply evidence in favor of the null hypothesis; many other hypotheses may be equally or more consistent with the observed data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This incompatibility can be interpreted as casting doubt on or providing evidence against the null hypothesis or the underlying assumptions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Appropriately chosen techniques, properly conducted analyses and correct interpretation of statistical results also play a key role in ensuring that conclusions are sound and that uncertainty surrounding them is represented properly.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Misunderstanding or misuse of statistical inference is only one cause of the”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
What the sources say
- Not checked — no full text of the sourcecites Peng 2015 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Smaller p-values do not necessarily imply the presence of larger or more important effects, and larger p-values do not imply a lack of importance or even lack of effect.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In view of the prevalent misuses of and misconceptions concerning p-values, some statisticians prefer to supplement or even replace p-values with other approaches.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
There is widespread consensus in the statistical community on the principles articulated in the ASA statement.
“according to widespread consensus in the statistical community”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While the large scale of the Tabula Muris Senis dataset provides substantial power to predict subtle changes in LR interactions, the biological complexity, dependencies among communication pairs, and multiple testing burden require that these p-values be interpreted within a broader biological and statistical context [33].”
From Quantitative profiling of lifespan-dependent cell-cell communication potential reveals dynamic ligand-receptor network shifts across mouse tissues (2026) · cites this paper as [33]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These types of incorrect descriptions contribute to confirmation bias, overinterpretation of results, and reporting correlation as implied causation (Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“This is especially true of relatively large-sample-size studies (as most learning analytics studies are), which are likely to obtain statistically significant findings in relatively small variations in measures such as GPA (Field 2017; Salkind 2016 Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
In the citing paper
“In 2016, the American Statistical Association released a statement on statistical significance and the P value with six principles underlying the proper use and interpretation of this statistical tool (77).”
From Misrepresentation and distortion of research in biomedical literature (2018) · cites this paper as [77]
In the citing paper
“Although we also present p values for exploratory analyses, we refrain from labeling any of them as statistically significant, following best-practice recommendations for statistical analysis [43].”
From Comparing quality of reporting between preprints and peer-reviewed articles in the biomedical literature (2020) · cites this paper as [43]
In the citing paper
“Contrary to IJE author recommendations and recent guidance from the American Statistics Society, 16 Gao et al. largely base their conclusions on findings with a P -value equivalent to < 0.05 after multiple testing.”
From Commentary: Two-sample Mendelian randomization: opportunities and challenges (2016) · cites this paper as [16]
In the citing paper
“Following guidance,50 we focused on 95% CIs, rather than statistical significance. For example, unlike conventional interpretations, we did not outright interpret an effect estimate “non‐significant” if the lower or upper bound of the 95% CI was slightly above/below the null value; we interpreted them as “suggestive” of an effect.”
From Third‐wave cognitive behaviour therapies for weight management: A systematic review and network meta‐analysis (2020) · cites this paper as [50]
Citations
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Statistics notes: Absence of evidence is not evidence of absence
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Scientific method: Statistical errors
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Why Most Discovered True Associations Are Inflated
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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/.
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Appendix 2. Questionnaire videos
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(2022) · Studies in language variation · doi:10.1075/silv.29.app
Appendix 1. Localities interviewed with the corpus COSER
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Appendix 3. Localities interviewed with the questionnaire
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Appendix 4. List of analysed verbs and their classification
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“This raised concerns about the appropriateness of the significance threshold and replication issues, which is aligned with the current statistical controversy on the appropriate use of a p -value (Wasserstein and Lazar 2016; Wasserstein, Schirm, and Lazar 2019; Gibson 2021; Gwise et al. 2021).”
Hypothesis Testing Within Bayesian Inference
Natário, I. (2024) · Emerging topics in statistics and biostatistics · doi:10.1007/978-3-031-69690-9_2
Highway systems: How good are they, really?
Chondrogiannis, T., & Grossniklaus, M. (2024) · GeoInformatica · doi:10.1007/s10707-024-00533-9
Reducing the Travel Burden for Patients to Access Specialized Medicines in Paraná, Brazil
Rossignoli, P., Pontarolo, R., & Fernández-Llimós, F. (2024) · Value in Health Regional Issues · doi:10.1016/j.vhri.2024.101065
Králik, R., Gabriel, P., Dušek, M., et al. (2024) · Kvasny Prumysl · doi:10.18832/kp2024.70.967
Khin, Y. P., Nawa, N., Yamaoka, Y., et al. (2024) · Pediatrics International · doi:10.1111/ped.15851
“20,21 Supplementary analysis was also conducted to examine the differences in participants' characteristics and the associations between mixed or foreign parentage and influenza vaccination across survey years.”
Healy, B. C. (2025) · Frontiers in Applied Mathematics and Statistics · doi:10.3389/fams.2024.1487750
Response to Liu, Xiao, Liu, et al.
Danese, M. D., & Groundland, J. S. (2025) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djae333
Revisiting Tumor Mutational Burden Cutoff: Multi-Study Replicability in ImmunotherapyPreprint
Jaljuli, I., Whiting, K. A., E, E. R. P., & Qin, L. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.02.631104
Why Should P-Values Be Abandoned in Scientific Research?Preprint
Huang, H. (2025) · Qeios · doi:10.32388/3syvej
Inferência estatística versus inferência causal
Luiz, R. R. (2025) · Revista Brasileira de Saúde Ocupacional · doi:10.1590/2317-6369/00124pt2025v50edisfl1
“Nesse contexto, o uso e a interpretação do p-valor na pesquisa biomédica têm sido ponto de intenso debate e controvérsias há mais de 30 anos, tendo, inclusive, obrigado a American Statistical Association (ASA) a se pro-nunciar oficialmente 7 .”
Early Stopping Based on Repeated Significance
Bax, E. T., Sarkar, A., & Shtoff, A. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825201
“However, early stopping introduces the potential for a temporal form of data dredging [1], [2], [3]: selecting a stopping time based on indicators of statistical significance affects whether those indicators are accurate.”
Statistical analysis and data interpretation
Reyes, L. H., & Cruz, J. C. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-15393-8.00005-1
Nisbet, R., McCormick, K., & Miner, G. D. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-15845-2.00028-1
Cross-sectional analysis of self-promotional language in texts of grant proposals across gender
Heyard, R., Lim, S. F., & Jorstad, A. (2024) · Research Evaluation · doi:10.1093/reseval/rvaf002
Kondylis, A., Kogel, U., Ho, J., et al. (2025) · Contributions to Tobacco & Nicotine Research · doi:10.2478/cttr-2025-0003
Lima, D. L., Perim, V., & Nogueira, R. (2025) · Elsevier eBooks · doi:10.1016/b978-0-323-91790-2.00044-7
Zhang, T., Santostefano, C. M., Harris, D., Coe, A. B., Zullo, A. R., Gerlach, L. B., Joshi, R., Bynum, J., & Shireman, T. I. (2025) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2024.105480 · Cited by 1
From hypothesis to conclusion: the essential role of statistics in science
Henríquez-Roldán, C. F., Bangdiwala, S. I., Guajardo, R. I. B., et al. (2025) · Research in Statistics · doi:10.1080/27684520.2025.2450532
Geometric and statistical curvatures of the skew- t distributions and their application
Wu, Q., & Hu, H. (2025) · Communication in Statistics- Theory and Methods · doi:10.1080/03610926.2025.2457494
“In 2016, an official statement on p -value was issued by Wasserstein and Lazar (2016).”
Why Should P-Values Be Abandoned in Scientific Research?Preprint
Huang, H. (2025) · Qeios · doi:10.32388/3syvej.2
Machine Learning for Prediction User Preferences Based on Personality Traits
Ketipov, R., Balabanov, T., Angelova, V., & Doukovska, L. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-80853-1_34
de Araújo, E. M., Oliveira, R., & Sampaio, A. A. S. (2025) · Revista Brasileira de Segurança Pública · doi:10.31060/rbsp.2025.v19.n1.1976
Distribution-free Bayesian analyses with the DFBA statistical package
Chechile, R. A., & Barch, D. H. (2025) · Behavior Research Methods · doi:10.3758/s13428-025-02605-6 · Cited by 1
Farkas, A. H., Escobar, J. C., Gilbert, F. E., Ding, M., & Keil, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.16.638555
Statistics Reform: Practitioner’s PerspectivePreprint
Huang, H. (2025) · Qeios · doi:10.32388/jvyejz.2
Collin, L. J., Cushing‐Haugen, K. L., Terry, K. L., Goode, E. L., Wu, A. H., Harris, H. R., Sasamoto, N., Cramer, D. W., Modugno, F., Elishaev, E., et al. (2025) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-24-1143 · Cited by 2
Assessment of Usability of Digital Side Mirror Technology Concerning Parking Speed and Accuracy
Povýšil, J., Hruška, M., Jelen, S., et al. (2025) · Acta Technologica Agriculturae · doi:10.2478/ata-2025-0006
Prioritization Reservoir Dredging Sites Using Sentinel-1 SAR Imagery
Cho, H., & Ryu, D. (2025) · 대한원격탐사학회지 · doi:10.7780/kjrs.2025.41.1.16
Précis of Thinking About Statistics
Otsuka, J. (2025) · Asian Journal of Philosophy · doi:10.1007/s44204-025-00259-x
Design of portable instrument for measuring leaf area index based on hemispherical photography
Wang, P., Tong, L., Gong, X., et al. (2025) · IEICE Electronics Express · doi:10.1587/elex.22.20250149
Combs, K. G., Austin, A. E., Shiue, K. Y., et al. (2025) · North Carolina Medical Journal · doi:10.18043/001c.121420
“Consistent with best practice statistical guidance, we examined the magnitude and precision of estimates to discuss potential differences between groups [7, 8].”
LoBue, C., Stopschinski, B. E., Saez-Calveras, N., Salter, A. R., Galasko, D. R., Giza, C. C., Cullum, C. M., Douglas, P. M., & Hart, J. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251325757
Flame Quenching Characteristics of Gas Explosion in the Confined Spaces
Wang, Z., & Cao, X. (2025) · Springer eBooks · doi:10.1007/978-981-96-3121-6_6
The fragility index of randomized controlled trials in advanced/metastatic renal cell cancer
Bi, Y., Wei, H., Ma, Q., et al. (2025) · Urologic Oncology Seminars and Original Investigations · doi:10.1016/j.urolonc.2025.03.003
Ergonomic analysis of book web services’ interfaces
Kłodnicka, P., & Matraszek, D. (2025) · Journal of Computer Sciences Institute · doi:10.35784/jcsi.6607
“W celu sprawdzenia, czy taka różnica ma znaczenie, należy wykonać test t Studenta - obliczyć wartość p [16].”
Addressing common inferential mistakes when failing to reject the null-hypothesis
Schmidt, A. F. (2025) · F1000Research · doi:10.12688/f1000research.158434.3
Adkins, V. J., England, S., & Stephan, A. W. (2026) · Geophysical Research Letters · doi:10.1029/2026gl122291
“This alone does not provide evidence for how strongly the connection between wind speeds and EPB occurrence is, simply that a connection likely exists (Wasserstein & Lazar, 2016).”
Agab, S. A., & Elsamani, M. O. (2025) · Journal of Umm Al-Qura University for Applied Sciences · doi:10.1007/s43994-025-00229-2
Deconstructing myths in quantitative research
Taylor, J. W. (2021) · International Forum Journal · doi:10.63201/otrq7600
Chappell, K. D., Chinbaatar, O., Goodman, K. J., & Kroeker, K. I. (2025) · Journal of Digestive Diseases · doi:10.1111/1751-2980.13342
A Bureaucratic Theory of Statistics
Recht, B. (2025) · Observational Studies · doi:10.1353/obs.2025.a956843
Statistics Reform: Practitioner’s Perspective
Huang, H. (2025) · AppliedMath · doi:10.3390/appliedmath5020049
The Bayesian New Statistics (Public)Preprint
Kruschke, J. K., & Liddell, T. M. (2017) · doi:10.31234/osf.io/wntsa_v1
Preceding Options Affect Subsequent Listwise but Not Pairwise Choice, Even for Experts
Forsgren, M., Frimanson, L., & Juslin, P. (2025) · Journal of Behavioral Decision Making · doi:10.1002/bdm.70019
“In light of recent critiques of the use of p values (e.g., Wasserstein and Lazar 2016; Wasserstein et al. 2019), we will assess evidence in the GLMMs by inspecting the credible intervals.”
Bhandari, A., & Golden, J. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5190587
Beauregard, C. G., Danforth, C. M., & Dodds, P. S. (2025) · JMIR Formative Research · doi:10.2196/70853
“It is important to underscore how to interpret significant p -values in this context [27–29].”
Whooten, R., Rifas‐Shiman, S. L., Perng, W., Chavarro, J. E., Oken, E., & Hivert, M. (2025) · Journal of Pediatric and Adolescent Gynecology · doi:10.1016/j.jpag.2025.04.011 · Cited by 1
Masayoshi, K., Hashimoto, M., Toda, N., et al. (2025) · Japanese Journal of Radiology · doi:10.1007/s11604-025-01772-y
Effects of incentivized commercial harvest on Common Carp and Bigmouth Buffalo populations
Simonson, M. A., Annear, A. R., & Weber, M. J. (2025) · North American Journal of Fisheries Management · doi:10.1093/najfmt/vqaf021
Hong, Y., Liu-Galvin, R. E., Khan, M., Nguyen, O. T., Yoon, H., Yang, J. J., & Prosperi, M. (2025) · Journal of Public Health · doi:10.1007/s10389-025-02477-2 · Cited by 1
Mueed, A., Raza, R., & Ilyas, M. (2025) · Journal of Robotic Surgery · doi:10.1007/s11701-025-02383-5
Using various natural products to prepare basturma (Iraqi fermented meat sausage)
Zaini, Z. E. H., Bisly, A. A., & Mahdi, A. S. (2025) · Food Research · doi:10.26656/fr.2017.9(3).082
Turtura, J. E., Fainstein, D., Kosty, D. B., Hermida, J., Clarke, B., Doabler, C. T., & Morgan, J. J. (2025) · Implementation and Replication Studies in Mathematics Education · doi:10.1163/26670127-bja10028
From LLMs to Randomness: Analyzing Program Input Efficacy With Resource and Language Metrics
Black, G., Yocam, E., Vaidyan, V. M., Comert, G., & Wang, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3571205
“In all tests, KS α is set at 0.05, which is considered a reasonable threshold in statistical literature [47].”
Influential(2025) · IGI Global eBooks · doi:10.4018/979-8-3373-2377-0.ch012
Lifetime breastfeeding and mortality among parous women in the Mexican Teacher's Cohort
Lozano‐Esparza, S., Unar‐Munguía, M., Trabert, B. L., Gómez‐Flores‐Ramos, L., Brochier, M., Hernández‐Ávila, J. E., Stern, D., & Lajous, M. (2025) · International Journal of Gynecology & Obstetrics · doi:10.1002/ijgo.70183
Qualitative methods and mixed methods
Mehta, R., & Naveed, M. (2025) · Elsevier eBooks · doi:10.1016/b978-0-12-821426-8.00027-3
Agley, J. D., Deemer, S. E., & Allison, D. B. (2025) · BMC Medical Research Methodology · doi:10.1186/s12874-025-02590-6
“The medium of publication (e.g., journals, publishing groups) may be slow to adapt to shifts in best-practice methods, such as recommendations on the appropriate use of p -values [35], and may instead recommend less valid approaches (e.g., reporting p -thresholds).”
Streich, M. (2025) · Springer eBooks · doi:10.1007/978-3-658-46951-1_4
Hirayama, Y., Yamazaki, H., Ogawa, Y., Yamada, Y., & Yamamoto, Y. (2025) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2025.105688
Improving the false coverage rate adjusted confidence intervals
Frostig, T., & Benjamini, Y. (2025) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1093/jrsssb/qkaf024
Miller, E., Begg, S. J., & Lee, P. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009522342.007
Ramaiah, L., Arndt, T., Thomas, G., et al. (2025) · Toxicologic Pathology · doi:10.1177/01926233251339113
“77 Questioning the historical reliance on statistical P -value interpretations (significance) becomes even more relevant to toxicologic pathology as global laboratory animal use considerations continue to shrink the laboratory animal group sizes in toxicological studies, thereby reducing the power…”
Adamowicz, M. A., Gortat, T., Czortek, P., et al. (2025) · Acta Oecologica · doi:10.1016/j.actao.2025.104095
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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