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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Shadow education and student achievement: Myth or reality? Global evidence from TIMSS 2019
Cao, G., & Huo, G. (2026) · Studies In Educational Evaluation · doi:10.1016/j.stueduc.2026.101634
Zhang, Y., meng, X., & Lin, J. (2026) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3774398.3811597
Perera, P., Proescholdbell, S. K., Cox, M. E., McDaniel, K. M., & Austin, A. E. (2026) · Journal of Interpersonal Violence · doi:10.1177/08862605261455810
“To interpret results, we relied on the magnitude of the adjusted RR and the width and location of the corresponding 95% CI, in alignment with guidance from the American Statistical Association (Savitz et al., 2024; Wasserstein & Lazar, 2016).”
Mogulagani, V. K., Uthiran, M. R., Babu, C. H. R., et al. (2026) · Journal of Medical Physics · doi:10.4103/jmp.jmp_28_26
“[11,12] The primary aim of this work is to identify the most suitable curve-fitting method for reliable picket fence analysis in clinics lacking access to commercial MLC QA software.”
Capturing Aleatoric Uncertainty in Climate Models
Gruber, C., Funk, H., Mittermeier, M., et al. (2026) · Environmetrics · doi:10.1002/env.70108
“…a sample size this large, even negligible differences between ensemble-based and reanalysis-based estimates would become statistically significant (Wasserstein and Lazar, 2016), so we instead evaluate the magnitude and structural agreement of the estimated temporal, topographic, and spatial…”
A new in silico model to precisely design focused ultrasound brain therapies
Conti, A., Grossi, M., de Andrade, P. C., Duggento, A., & Toschi, N. (2026) · Medical Physics (Lancaster) · doi:10.1002/mp.70520
“The inclusion of standardized effect sizes (Cohen’s d 41,52,53 ) provided an additional layer of interpretation beyond classical statistical testing, enabling direct assessment of the magnitude of model-induced differences in acoustic exposure.”
Awad, M. M., Osman, Y. A., & Abdelmoteleb, M. (2026) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-026-13906-x
“Statistical significance was set at p < 0.05, while values between 0.05 and 0.1 were reported as suggestive but not significant (Wasserstein and Lazar 2016; Cesana 2018; Di Leo and Sardanelli 2020; White et al. 2022).”
InfluentialBeyond statistical significance: ranking transcription factor binding motifs by effect sizePreprint
Viner, C., Mastromatteo, S., Denisko, D., Negrea, J., Tang, Y., Zhang, L., Hoffman, M. M., & Sun, L. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.19.732679
“In these cases, the magnitude of p-values is dominated by this sample size heterogeneity, as opposed to the true effect size of interest 50,57,63 .”
Paradysz, J. J., Zawadzki, G., & Czortek, P. (2026) · Forest Ecology and Management · doi:10.1016/j.foreco.2026.124044
How Do Assignment Workload and Time Management Relate to Academic Stress in Early Adolescence?
Syahraini, K., Nurhayati, & Fatimah, K. (2026) · Women Education and Social Welfare · doi:10.70211/wesw.v3i2.504 · Cited by 1
Anonymous, & Bentley, I. (2026) · Physical Review Physics Education Research · doi:10.1103/bdl1-6bn4 · Cited by 1
Ensuring Quality in Preclinical Research: The Importance of Being Human
Lang, T., Konietschke, F., Rahnenführer, J., et al. (2026) · Biometrical Journal · doi:10.1002/bimj.70145
da Silva, A. M. P., Santos, D. H., Lima, D. D. S., Cardoso, L. J. C., Moura, C. B., Høilund‐Carlsen, P. F., Perry, G. L., Kishi, T., Barbosa, B. J. A. P., & Anghinah, R. (2026) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2026.06.014
Statistical Nonsignificance Should Not be Equated With No Association: A Comment on Lei Et Al.
Qiu, C., Yang, M., Zhao, W., et al. (2026) · Geriatrics and gerontology international/Geriatrics & gerontology international · doi:10.1111/ggi.70623
Stability-driven multi-omics integration for reproducible latent structurePreprint
Guan, H., van Gerwen, M. A. G., Kim‐Schulze, S., Colicino, E., Dolios, G., & Petrick, L. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.23.734064
Nakamura, S., Spring, R., Hamagami, K., et al. (2026) · CALICO Journal · doi:10.3138/calico-2024-0028
Esterhuizen, T. M., Mbuagbaw, L., Rehman, N., Yanwou, N., Swaby, D. J., Kittle, E., Licht, J.-C., & Thabane, L. (2026) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2026.101667
“One of the limitations discussed in the ASA's statement was that p-values do not measure effect sizes nor importance of the findings [3].”
Luo, Y., Zhang, G., Agarwal, A., Weng, C., & Bernstein, E. J. (2026) · Seminars in Arthritis and Rheumatism · doi:10.1016/j.semarthrit.2026.153033
Bohrer, J., Ament, J., Schmelz, J., et al. (2026) · CEAS Aeronautical Journal · doi:10.1007/s13272-026-00984-w
Statistical Nonsignificance Should Not Be Equated With No Association: A Comment on Kato Et al.
Xiao, Y., Yang, M., Zhao, W., et al. (2026) · Geriatrics and gerontology international/Geriatrics & gerontology international · doi:10.1111/ggi.70615
Brikell, I., Astrup, A., Wimberley, T., Araki, M., Chang, Z., Demontis, D., Dong, Z., Faraone, S. V., Gao, L., Gillies, M. B., et al. (2026) · BMJ Mental Health · doi:10.1136/bmjment-2025-302469
Racial Differences in Adverse Pregnancy Outcomes and Incident Hypertension: A Mediation Analysis
Petito, L. C., Huang, X., Merz, C. N. B., Bello, N. A., Catov, J. M., Licon, E., Lane‐Cordova, A. D., Haas, D. M., Levine, L. D., McNeil, R. B., et al. (2026) · Journal of the American Heart Association · doi:10.1161/jaha.123.035681
Weller, E., Aarsman, S. R., Teague, S. J., Greenwood, C. J., Youssef, G., Mattick, R. P., Elliott, E. J., ALLSOP, S. J., Burns, L., Najman, J. M., et al. (2026) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2026.113262 · Cited by 1
Decoding Decisions: Personality-Interest Motivational Sequences as Predictors of Career Paths
Townsend, G., & Webb, P. (2026) · F1000Research · doi:10.12688/f1000research.176767.3
“…selection of the predictors to include a combination of their effect size (standardised beta coefficient, β ), their theoretical plausibility within the Five-Factor Model, as well as their contribution to the model ’ s overall predictive accuracy (Amrhein et al ., 2019; Wasserstein & Lazar, 2016).”
Ripamonti, E., Heap, J., Grande, G., Bellavia, A., Rizzuto, D., & Lennartsson, C. (2026) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2026.2697735
“A p - value threshold of p 0.05 was set for the analyses, and p -values were reported in agreement with the ASA statement recommendations (Wasserstein & Lazar, 2016).”
InfluentialWang, Q., Tao, Y., Huang, Y., & Huang, B. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1817092
Meganingtyas, Y., Yuniarti, K. W., Jongsma, M. L. A., & A’yuninnisa, R. N. (2026) · International Journal of Clinical and Experimental Hypnosis · doi:10.1080/00207144.2026.2678856
Sidebotham, D. A. (2026) · British Journal of Anaesthesia · doi:10.1016/j.bja.2026.05.015
Katabi, G., Huss, M., Lukito, S., Dekkers, T. J., Sonuga-Barke, E. J. S., & Shahar, N. (2026) · Journal of Attention Disorders · doi:10.1177/10870547261463814
“…testing driven analysis relying solely on sample size–based inference as in frequentist statistics, and instead provide full information regarding the uncertainty estimation of regression parameters (Amrhein et al., 2019; McElreath, 2020; Wasserstein et al., 2019; Wasserstein & Lazar, 2016).”
Reproducibility in Information Retrieval
Maistro, M., Breuer, T., & Ferro, N. (2026) · Foundations and Trends® in Information Retrieval · doi:10.1108/ftinr-05-2025-0087 · Cited by 1
Türkmen, S., & Paslı, S. (2026) · Turkish Journal of Emergency Medicine · doi:10.4103/tjem.tjem_214_26
“[12,13] Clinicians and researchers should consider whether the observed magnitude of effect is likely to influence decision‑making, resource utilization, or patient outcomes.”
Bağcı, R. B., & Woodside, A. G. (2026) · Journal of Services Marketing · doi:10.1108/jsm-08-2025-0561
Dick, A. S., Hawes, S. W., Bayat, M., Curtis, M., Lopez, D. A., Parekh, P., Pecheva, D., González, R., Heeringa, S. G., Linkersdörfer, J., et al. (2026) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2026.101779
“However, this power acts as a double-edged sword: there is a risk that many or most associations will yield a statistically significant 𝑝 -value under the null hypothesis significance testing (NHST) framework, even if the effect is trivially small in magnitude (Wasserstein and Lazar, 2016).”
Cescon, M., Peruzzini, M., & Gaglione, D. (2026) · Applied Sciences · doi:10.3390/app16146921
Yang, H., Ding, D., Qin, H., Miao, H., Wang, C., Zang, Y., Chi, L., & Wu, B. (2026) · Behavioral and Brain Functions · doi:10.1186/s12993-026-00344-y · Cited by 1
“…model generalizability. this literature remains heavily anchored to null-hypothe-sis significance testing (NHST) and single p-value thresholds, despite clear calls to move beyond dichotomous “significant/non-significant” decisions toward richer effect-size and uncertainty quantification [1, 43].”
Risk of Infections With Infliximab vs Adalimumab Among Children With Inflammatory Bowel Disease
Lyu, N., Tracy, M., Schneeweiß, S., et al. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.22684
Goyal, K., Kalra, R., & Nagpal, A. (2026) · Geriatrics and gerontology international/Geriatrics & gerontology international · doi:10.1111/ggi.70656
Bridging Scales and Cognitive Dualities: Dimensional Analysis and Memory Reconstruction
Douar, A. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-24807-7_15
Koornneef, D. J. M., de Kok, J. W. T. M., Termorshuizen, F., et al. (2026) · BMC Health Services Research · doi:10.1186/s12913-026-15093-x
Teachers’ detection and reporting of children at risk: findings from a vignette study in Hungary
Kopasz, M., Herke, B. L., & Balogh, K. (2026) · Children and Youth Services Review · doi:10.1016/j.childyouth.2026.109182
Noise beyond the curriculum? The influence of social work education on risk assessments
Bächler, C. M. (2026) · Social Work Education · doi:10.1080/02615479.2026.2701675
Tuan, T. T., Huan, P. T., Quang, K. D., & Hoang, S. L. (2026) · WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS · doi:10.37394/23207.2026.23.79
Assessing the robustness of clinical trials regarding novel therapies in inflammatory bowel disease
Zheng, J., Huang, P., Li, L., et al. (2026) · Gastroenterology report · doi:10.1093/gastro/goag051
“Specifically, an overreliance on the P value can easily lead to the results being reversed, as the strength of rejecting the null hypothesis is weak when the P value approaches 0.05 [10].”
InfluentialKovacevic, M. (2026) · Research Square · doi:10.21203/rs.3.rs-10013003/v1
From Rainfall to Absolute Landslide Probability: A Machine Learning–Based Approach
Jin, J., Xue, Z., Xu, C. B., et al. (2026) · Natural Hazards Review · doi:10.1061/nhrefo.nheng-2545
Beyond rurality: Regional and service-system variation in cancer patient experience in Scotland
Murchie, P., McLernon, D. J., Murchie, A., et al. (2026) · Journal of Cancer Policy · doi:10.1016/j.jcpo.2026.100781
Li, Y., Wang, H., Chandrashekhar, R., Major, J., Chandna, M., & Bodison, S. C. (2026) · JMIR Formative Research · doi:10.2196/93019
Suzuki, M., & Wong, G. T. W. (2026) · Contemporary Justice Review · doi:10.1080/10282580.2026.2704154
Radners, J., Schweizer, C., Eckmann, S., et al. (2026) · Theoretical and Applied Fracture Mechanics · doi:10.1016/j.tafmec.2026.105820
Mehta, R. S., Aljawai, Y. M., Kebriaei, P., Fingrut, W. B., Smallbone, P., Oran, B., Olson, A. L., Popat, U., Champlin, R. E., & Shpall, E. J. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.23265
Romero, H. R. C., Tusa, F., Ocampo, R. D. L. S., & Célleri-Pacheco, J. (2026) · Trends in Higher Education · doi:10.3390/higheredu5030067 · Cited by 2
Yuzawa, Y., & Kondo, T. (2026) · Research Square · doi:10.21203/rs.3.rs-10151610/v1
Ahomed, R., & Guevara, R. (2026) · SAGE Open · doi:10.1177/21582440261467840
de Kok, J. W. T. M., Koornneef, D. J. M., Termorshuizen, F., Schnabel, R. M., van der Horst, I. C. C., de Keizer, N. F., Brinkman, S., & van Bussel, B. C. T. (2026) · Critical Care Medicine · doi:10.1097/ccm.0000000000007271
“We focused on effect sizes presented as ORs with 95% CI rather than p values, which provide little added value in the present study, particularly given the large sample size (42, 43).”
Detection of Variability in Seyfert 2 Galaxies and Measurement of the Optical Scattering Region Size
Kovacevic, N., Dai, X., Yuk, H., et al. (2026) · The Astrophysical Journal · doi:10.3847/1538-4357/ae7d0d
Piccolo, M., dos Santos, D. W., Pancheri, V., Teixeira, W., Stochero, M., Galdino, S. R., Sato, J., Pinheiro, E. D., Tencatt-Abrita, A. P. C., Zatorre, L., et al. (2026) · The Arts in Psychotherapy · doi:10.1016/j.aip.2026.102508
Laicans, J., Bartkevičs, V., Pugajeva, I., Dejus, S., Zviedris, M., Dejus, B., & Juhna, T. (2026) · Water · doi:10.3390/w18141766
How Should We Interpret the Association Between Abortion and Mild Psychiatric Illness?
Huybrechts, K. F., Rothman, K., & Wisner, K. L. (2026) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2025.3561
Aderolu, I. A., Oyerinde, A. A., & Agunloye, O. O. M. (2026) · International Journal of Tropical Insect Science · doi:10.1007/s42690-026-01924-1
“(Wasserstein & Lazar, 2016 ; Habibzadeh, 2025 ).”
Tay, J. R. H., Bashir, N. Z., & Cooray, U. (2026) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.2026420
A cultural finance perspective on the low volatility anomaly
Solanki, K., Seetharam, Y., & Page, D. (2026) · Research in International Business and Finance · doi:10.1016/j.ribaf.2026.103562
Academic Library Succession Planning in Research Universities in the United States
Goldman, C. (2026) · Journal of Library Administration · doi:10.1080/01930826.2026.2699317
“In line with guidance encouraging a move away from a rigid focus on p .05 (e.g., Wasserstein & Lazar, 2016), this study reports significance at multiple levels.”
Joeloidian, G., Irawan, R., & Yong, B. (2026) · Spatial and Spatio-temporal Epidemiology · doi:10.1016/j.sste.2026.100832
Disciplinary Action Trends within Engineering and Architecture Professions in Arizona and New Mexico
Jaafer, S., Hoover, C. G., & Lamanna, A. J. (2026) · Journal of Legal Affairs and Dispute Resolution in Engineering and Construction · doi:10.1061/jladah.ladr-1543
Rojas, N., Calderon, L. E., Kogut, K. R., Perez-Rocha, Y., Guadamuz, J. S., Fleming, M. D., Warner, M. L., Eskenazi, B., González, H. M., DEARDORFF, J., et al. (2026) · SLEEP Advances · doi:10.1093/sleepadvances/zpag085
“…to move towards best practices in the f ield of epidemiology and highlight f indings of public health signif icance, we report meaningful associations regardless of statistical signif icance arbitrarily def ined by p = .05 [ 76, 77] but have included P -values in our tables for interested readers.”
Wang, B. G., Li, R., & Sun, Y. (2026) · Forest Ecology and Management · doi:10.1016/j.foreco.2026.124109
Data Analysis Planning and Reporting for Confirmatory Multi‐Lab Preclinical Trials: A Tutorial
Arroyo-Araujo, M., Carneiro, C. F. D., Piper, S. K., Wilcke, J. C., Ellenbach, N., Boulesteix, A., Emprechtinger, R., Ineichen, B. V., Riecken, L. B., Haller, B., et al. (2026) · Biometrical Journal · doi:10.1002/bimj.70152
“…the strengths and limitations of different statistical frameworks or approaches is also key from the planning of the study, through interpreting and reporting of results, to making decisions regarding the translational potential of the findings (Hoekstra et al. 2018 ; Wasserstein and Lazar 2016 ).”
Zareipour, M., Rasoulzadeh, S., & Dadloo, Z. A. (2025) · Journal of Environmental Health Engineering · doi:10.66224/jehe.13.3.333
Restrictive vs Liberal Transfusion Strategy After Myocardial Infarction
Bertolet, M., Carrier, F. M., Glynn, S., et al. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.24991
Castillo-Villar, K. K., Keith, K., & Alaeddini, A. (2026) · Energies · doi:10.3390/en19153570
Peng, Z., Han, T., Li, Y., et al. (2026) · Scientific Reports · doi:10.1038/s41598-026-62337-1
“Consistent with recommended statistical reporting practice, only statistically significant between-condition EMG differences were interpreted, and non-significant comparisons were not described as “trends” 49 .”
When significance misleads: content factors explain little of content popularity
Ghanbarpour, T., & Solvoll, M. K. (2026) · Journal of Marketing Analytics · doi:10.1057/s41270-026-00519-6 · Cited by 1
de Souza, D. C., Nunes, L. M. P., de Camargo, R., et al. (2026) · Energy Conversion and Management X · doi:10.1016/j.ecmx.2026.102163
The Bayes e-Value: Testing by Betting Given a Prior Probability of the Null Hypothesis
Bickel, D. R. (2026) · Journal of Statistical Theory and Practice · doi:10.1007/s42519-026-00600-4
“Another problem with the p -value that may also contribute to the replication crisis is its persistent tendency to be misinterpreted [55].”
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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