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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- 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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BackgroundBeyerlein, G.-S., & Ratke, L. (2024) · Macromolecular Rapid Communications · doi:10.1002/marc.202400014
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Chang, X., Yang, Z., Yan, W., Liu, Z.-T., Luo, C., & Yao, D. (2024) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2024.110938
“That is also why in recent years, an increasing number of studies have appealed to effect sizes rather than excessive reliance on statistical values (Wasserstein and Lazar, 2016).”
Dinâmica econômica, mudanças sociais e novas pautas de políticas públicas
Pompeu, J. C. B., Viana, A. R., de Magalhães, L. C. G., & Gonçalves, A. P. V. (2023) · Instituto de Pesquisa Econômica Aplicada (Ipea) eBooks · doi:10.38116/978-65-5635-064-6
A Utilitarian Perspective on Risk Quantification for Clinical Significance in Binary Outcomes
Park, J. (2024) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580241248134
“The debate on NHST has persisted, 1-15 with significant scrutiny arising from the American Statistical Association’s statement 11 on the limitations and misuse of P -values.”
Dobesh, P. P., Fermann, G. J., Christoph, M. J., et al. (2024) · Research and Practice in Thrombosis and Haemostasis · doi:10.1016/j.rpth.2024.102429
“Further, in alignment with recommendations from the American Statistical Association [7] and contrary to the suggestion from Lucarelli et al., potential confounding covariates were identi fi ed based on their clinical relevance and completeness of data rather than by statistical comparison.”
ResultIncentives, Assessment, and the Reliability of Statistical Significance Examinations of EvidencePreprint
Cready, W. M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4595552
Ferreño, D., Erickson, M., Kirk, M. T., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4823393
Ruppar, T. M. (2024) · Western Journal of Nursing Research · doi:10.1177/01939459241253384
Angelini, C. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95502-7.00015-4
Humann‐Guilleminot, S., Binkowski, Ł. J., & Helfenstein, F. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4825181
Muradchanian, J., Hoekstra, R., Kiers, H. A. L., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-62043-w
Prise en charge de l’endométriose : expérience, statistiques, vérité et doux mensonges
Koninckx, P. R., Koushik, A., & Tulandi, T. (2024) · Journal of Obstetrics and Gynaecology Canada · doi:10.1016/j.jogc.2024.102550
Logical Fallacies and the Misuse of RCT Findings: Lessons from Diagnostic Statistics
MacDougall, M. (2024) · Springer eBooks · doi:10.1007/978-3-031-25859-6_3
How to design research-aligned diversity, equity, and inclusion interventions in physics
Johnson, A. C. (2025) · Physical Review Physics Education Research · doi:10.1103/q643-8928
“…Sociological Association statement on p values put it, “ Any effect, no matter how tiny, can produce a small p value if the sample size or measurement precision is high enough, and large effects may produce unimpressive p values if the sample size is small or measurements are imprecise ” [116].”
A Global Spatial Meta-Regresssion Analysis of Mangrove Valuation StudiesPreprint
Salvo, M. D., Giuffrida, L., Signorello, G., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4855859
Factors Influencing Hg Concentrations and Body Size in Dung Beetles from Polish CarpathiansPreprint
Wiśniowska, I., Kadłub, D., Górz, A., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4852796
Spatial Patterns of Water Supply and Use in California
Helly, J., Cayan, D. R., Stricklin, J., & DeHaan, L. L. (2024) · San Francisco Estuary and Watershed Science · doi:10.15447/sfews.2024v22iss2art2
Economic History as Humanomics
McCLOSKEY, D. N. (2024) · Springer eBooks · doi:10.1007/978-3-031-35583-7_47
Adamowicz, M. A., Gortat, T., Czortek, P., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4870486
A Biosocial Return to Race? Racial Differences in DOHaD and Environmental Epigenetics
Meloni, M., Kuzawa, C. W., Issaka, A., & Moll, T. (2024) · Cambridge University Press eBooks · doi:10.1017/9781009201704.006
Fernández, B. I., Soler, L. S. D. L. T., Benayas, M. T. G., et al. (2024) · Medicina Clínica Práctica · doi:10.1016/j.mcpsp.2024.100446
Danka, M. N. (2024) · Health Psychology Update · doi:10.53841/bpshpu.2024.33.1.23
Pawel, S., & Held, L. (2024) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1093/jrsssb/qkae064
Coils design influence on corona inception
Gonçalves, C. S., Sartori, R. L., Morsch, R., et al. (2024) · IEEE Electrical Insulation Conference (EIC) · doi:10.1109/eic58847.2024.10579288
“In the context of a t-test, a low p-value (typically less than or equal the significance level ≤ 0.05) indicates that the difference observed between groups (or the effect of a factor) is statistically significant and not likely due to random chance [15].”
BackgroundInfluentialPoufinas, T., Chen, J. M., Agiropoulos, C., et al. (2024) · Theoretical Economics Letters · doi:10.4236/tel.2024.143067
The Role of CMC Statisticians: Co‐Practitioners of the Scientific Method
Schofield, T. L. (2024) · Pharmaceutical Statistics · doi:10.1002/pst.2420
“Previous literature has highlighted issues related to the use of p values in scientific inquiry [16– 18].”
Uno, H. (2024) · Japanese Journal of Biometrics · doi:10.5691/jjb.45.3
Li, L., & Zhou, G. (2024) · Science & Education · doi:10.1007/s11191-024-00545-9
“…to draw definitive conclusions from analyzing such data, particularly after seeing a statistically significant result, yet reporting significance or not based on p -values thresholds of .05 or .01 has been contested as an acceptable good practice (Kuffner & Walker, 2019; Wasserstein & Lazar, 2016).”
Amanor‐Boadu, V., Hill, M. C., & Bloodgood, J. M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4897945
(2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13715-0.00020-0
Biomarkers in Oncology: Complexities in Biomarker-Driven Studies and Statistical Analysis
Uno, H., & Horiguchi, M. (2024) · JCO Precision Oncology · doi:10.1200/po.24.00358
Chai, C. P. (2024) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1093/jrsssb/qkae081
MacDougall, M. (2021) · Journal of University Teaching and Learning Practice · doi:10.53761/1.18.2.8
Does Renewable Energy Minimize Greenhouse Gas Emissions in Asia? Evidence from the Bayesian Approach
Nguyen, T. M., & Saijai, W. (2024) · Studies in systems, decision and control · doi:10.1007/978-3-031-59110-5_43
Philosophy Untouched by Science? Zeno’s Runner, Sextus’ Epochē, and More
Mattes, J. (2024) · Philosophies · doi:10.3390/philosophies9040115
la Ruelle, L. P. D., de Zoete, A., Ostelo, R., et al. (2024) · MethodsX · doi:10.1016/j.mex.2024.102908
“The former is traditionally evaluated according to its P-value (or confidence interval), although there is increasing movement from the international scientific community against its use [ 13 , 14 ].”
BackgroundGunter, U., & Smeral, E. (2024) · Tourism Economics · doi:10.1177/13548166241273584
“…the American Statistical Association stated in 2016 that the widespread use of statistical signi fi cance — understood as a 5% p -value threshold — to justify scienti fi c fi ndings leads to a distorted perception of the scienti fi c process (Wasserstein et al., 2019; Wasserstein and Lazar, 2016).”
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Altman, N., & Krzywinski, M. I. (2024) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-112723-034555
How should Null Findings be Interpreted?
Leoutsakos, J. (2024) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2024.08.006
Dawes, J., Walters, K., Frost, R., et al. (2024) · University of Glasgow · doi:10.3310/nihropenres.14703.r32567
Wang, T., Liu, Z., He, L., et al. (2024) · Journal of Infrastructure Policy and Development · doi:10.24294/jipd.v8i8.5704
“Although 0.05 has been widely applied as a threshold to determine the significance, recent researchers proposed that the selection of significance level depends on factors such as sample size, conventions in disciplines, and precision of measurements (Wasserstein and Lazar, 2016).”
BackgroundInfluentialBickel, D. R. (2024) · Statistical Papers · doi:10.1007/s00362-024-01597-3
“Confidence intervals and p -values have been misused and misinterpreted enough to provoke responses from the American Statistical Association and one of its journals (Wasserstein and Lazar 2016; Wasserstein et al. 2019; Benjamini et al. 2021; Kafadar 2021).”
Bickel, D. R. (2024) · Journal of Verification Validation and Uncertainty Quantification · doi:10.1115/1.4066380
The Relationship of Chronic Disease Burden and Racial-Ethnic Disparities in Depression Treatment
Hernandez, J. V., & Harman, J. S. (2024) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-024-02081-2
Liu, M., Teng, X., & Jiang, J. (2024) · PLoS ONE · doi:10.1371/journal.pone.0309432
Soloniuk, L. J. (2024) · Springer eBooks · doi:10.1007/978-3-031-62756-9_48
Post, A. K. (2024) · doi:10.33612/diss.1086344391
Factors influencing Hg concentrations and body size in dung beetles from Polish Carpathians
Wiśniowska, I., Kadłub, D., Górz, A., et al. (2024) · Chemosphere · doi:10.1016/j.chemosphere.2024.143268
Ability in Medical Statistics (Hypothesis Testing) of Medical Staff and Associated Factors
Miura, T., Inagaki, K., INUZUKA, H., et al. (2024) · JOURNAL OF THE JAPANESE ASSOCIATION OF RURAL MEDICINE · doi:10.2185/jjrm.73.61
Bergh, D. D., Powell, R. G., Zhao, Y., & Schwab, A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4949370
Commentary: “How should Null Findings be Interpreted?”
South, C. C., & Arndt, S. V. (2024) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2024.09.004
Mugnai, C., Maistrello, L. F., Fiacca, G., et al. (2024) · medRxiv · doi:10.1101/2024.09.16.24313294
Singichetti, B., Wang, Y. C., Golightly, Y. M., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0310270
“…in NC and due to best practice guidance on moving away from a reliance on p-values to examine differences, we examined and described the overall magnitude and differences in the percentages and rates (with CIs) of personal and contextual characteristics, and in trends, by suspension type [59].”
Misunderstandings Regarding Sampling and the Role of Statistics in AI
Rodríguez, G. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01665
Evidence-Based Quantum-Information Processing: Applications on Photonic Quantum Systems
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Contextualizing the Conclusion Generator: From the ASA statement to PhD curriculum
Schmidt, M., & Parner, E. T. (2024) · Annals of Epidemiology · doi:10.1016/j.annepidem.2024.09.006
Monaghan, T. F., Wein, A. J., & Dmochowski, R. R. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-90186-4.00073-0
COUNTERPOINT: Abandon or Reassess? Interpreting Treatment Effects in “Negative” Clinical Trials
Overbey, J., Zieroth, S. R., & Viele, K. (2024) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2024.09.007
Nakata, K., Okumura, K., & Kobayashi, T. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c05785
Racial‐ethnicity group distributions of blood product use in acute trauma care transfusion
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Effectiveness of group analytic and psychodynamic psychotherapy in routine secondary-care practice
Story, G. W., Dalton, F., Selway, A. G., Caparrotta, L., O’Reilly, J., Colam, A., Larney, A., Ritchie, S., & Hillen, T. (2024) · Group Analysis · doi:10.1177/05333164241257239
“There is increasing awareness of how null hypothesis significance testing (NHST), by imposing an arbitrary decision criterion, can distort the interpretation of data (Amrhein et al., 2019; Wasserstein and Lazar, 2016).”
Comments on “The Roles, Challenges, and Merits of the P Value” by Chén et al.Preprint
Huang, H. (2024) · Qeios · doi:10.32388/svhlga.2
Measuring Strength of Randomized Clinical Trials
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Konopka, A., Führer, A., Binder, M., Diexer, S., Frese, T., Gekle, M., Girndt, M., Gottschick, C., Hoell, J. I., Klee, B., et al. (2024) · Psychiatry International · doi:10.3390/psychiatryint5040050
Fragility index for extended prophylaxis following abdominopelvic surgery: A methodological survey
McKechnie, T., Bogdan, R.-M., Brennan, K., Shi, V., Grewal, S., Eskicioglu, C., Farooq, A. O., & Patel, S. V. (2024) · The American Journal of Surgery · doi:10.1016/j.amjsurg.2024.116020
The FDR in the Context of Bayesian Statistics
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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
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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.
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