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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Additional file 1 of On clinical trial fragility due to patients lost to follow up
Baer, B. R., Fremes, S. E., Gaudino, M. F. L., Charlson, M. E., & Wells, M. T. (2021) · Figshare · doi:10.6084/m9.figshare.17056754
Griffin, B. A., Schuler, M. S., Stuart, E. A., Patrick, S., McNeer, E. A., Smart, R., Powell, D., Stein, B. D., Schell, T. L., & Pacula, R. L. (2021) · Figshare · doi:10.6084/m9.figshare.17169561
Hartnack, S., & Roos, M. (2021) · Figshare · doi:10.6084/m9.figshare.17125841
Bone, J. N., Bellad, M., Goudar, S., Mallapur, A. A., Charantimath, U., Ramadurg, U., Katageri, G., Lesperance, M., Woo Kinshella, M.-L., Suleman, R., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19766456
Benzon, B., Marijan, S., Pervan, M., & Čikeš Čulić, V. (2024) · Figshare · doi:10.6084/m9.figshare.26582222
Ma, Z., He, W., Zhou, Y., Mai, L., Xu, L., Li, C., & Li, M. (2024) · Figshare · doi:10.6084/m9.figshare.26410011
Benzon, B., Marijan, S., Pervan, M., & Čikeš Čulić, V. (2024) · Figshare · doi:10.6084/m9.figshare.26582219
Remch, M., Swink, G., Mautz, C., Austin, A. E., & Naumann, R. B. (2024) · Figshare · doi:10.6084/m9.figshare.26606326
Leite, P. H. A. D. C., Coelho, L. E., Cardoso, S. W., Moreira, R. I., Veloso, V. G., Grinsztejn, B., & Luz, P. M. (2022) · Figshare · doi:10.6084/m9.figshare.19785731
Agley, J. D., Xiao, Y., Eldridge, L. A., Meyerson, B. E., & Golzarri‐Arroyo, L. (2022) · Figshare · doi:10.6084/m9.figshare.19746067
Naghipour, S., Cox, A. J., Fisher, J. J., Plan, M. R., Stark, T., West, N., Peart, J. N., Headrick, J. P., & Toit, E. F. D. (2024) · Figshare · doi:10.6084/m9.figshare.26734986
Bove, F. J., Greek, A., Gatiba, R., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26170617
Srimaneekarn, N., Leelachaikul, P., Thiradilok, S., & Manopatanakul, S. (2024) · Figshare · doi:10.6084/m9.figshare.26569024
Silva, M. D. B., de Oliveira, R. D. V. C., da Silveira Barroso Alves, D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.13521201
Carneiro, C. F. D., Queiroz, V. G. S., Moulin, T. C., Carvalho, C. A. M., Haas, C. B., Rayêe, D., Henshall, D. E., De‐Souza, E. A., Amorim, F. E., Boos, F. Z., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13310563
Ma, Z., He, W., Zhou, Y., Mai, L., Xu, L., Li, C., & Li, M. (2024) · Figshare · doi:10.6084/m9.figshare.26755888
Bull, C. J., Bell, J. A., Murphy, N., Sanderson, E., Smith, G. D., Timpson, N. J., Banbury, B. L., Albanes, D., Berndt, S. I., Bezieau, S., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13466703
Bell, J. A., Santos Ferreira, D. L., Fraser, A., Soares, A. L. G., Howe, L. D., Lawlor, D. A., Carslake, D., Smith, G. D., & O’Keeffe, L. M. (2021) · Figshare · doi:10.6084/m9.figshare.14100471
Elgersma, I. H., Hart, R. K., Straiton, M. L., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26601250
Heuts, S., Ubben, J. F. H., Kawczynski, M. J., Gabrio, A., Suverein, M. M., Delnoij, T., Kaválková, P., Rob, D., Komárek, A., van der Horst, I. C. C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26742932
Fink, D. S., Stohl, M., Mannes, Z. L., Shmulewitz, D., Wall, M., Gutkind, S., Olfson, M., Gradus, J. L., Keyhani, S., Maynard, C. C., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22607671
Benzon, B., Marijan, S., Pervan, M., & Čikeš Čulić, V. (2023) · Figshare · doi:10.6084/m9.figshare.26582213
Additional file 1 of Interrater reliability estimators tested against true interrater reliabilities
Zhao, X., Feng, G. C., Ao, S. H., & Liu, P. L. (2022) · Figshare · doi:10.6084/m9.figshare.20727709
Diaz-Quijano, F. A., Calixto, F. M., & da Silva, J. M. N. (2020) · Figshare · doi:10.6084/m9.figshare.12422171
Simić, M., Harmer, A. R., Agaliotis, M., Nairn, L., Bridgett, L., March, L., Votrubec, M., Edmonds, J. P., Woodward, M., Day, R., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14737049
Carneiro, C. F. D., Queiroz, V. G. S., Moulin, T. C., Carvalho, C. A. M., Haas, C. B., Rayêe, D., Henshall, D. E., De‐Souza, E. A., Amorim, F. E., Boos, F. Z., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13310584
Ma, Z., He, W., Zhou, Y., Mai, L., Xu, L., Li, C., & Li, M. (2024) · Figshare · doi:10.6084/m9.figshare.26409909
Ghaem Maghami, N., Helfenstein, F., Manegold‐Brauer, G., & Bencaiova, G. A. (2023) · Figshare · doi:10.6084/m9.figshare.24548155
Agley, J. D., Xiao, Y., Eldridge, L. A., Meyerson, B. E., & Golzarri‐Arroyo, L. (2022) · Figshare · doi:10.6084/m9.figshare.19746073
Kidwell, K., Roychoudhury, S., Wendelberger, B., Scott, J., Moroz, T., Yin, S., Majumder, M., Zhong, J., Huml, R. A., & Miller, V. (2022) · Figshare · doi:10.6084/m9.figshare.19728445
Heuts, S., Ubben, J. F. H., Kawczynski, M. J., Gabrio, A., Suverein, M. M., Delnoij, T., Kaválková, P., Rob, D., Komárek, A., van der Horst, I. C. C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26742929
Agley, J. D., Xiao, Y., Eldridge, L. A., Meyerson, B. E., & Golzarri‐Arroyo, L. (2022) · Figshare · doi:10.6084/m9.figshare.19746070
Agley, J. D., Xiao, Y., Eldridge, L. A., Meyerson, B. E., & Golzarri‐Arroyo, L. (2022) · Figshare · doi:10.6084/m9.figshare.19746076
Wallace, M. L., Mentch, L., Wheeler, B. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26598260
Benzon, B., Marijan, S., Pervan, M., & Čikeš Čulić, V. (2023) · Figshare · doi:10.6084/m9.figshare.26582216
Communicating Adverse Impact Analyses Clearly: A Bayesian ApproachPreprint
Egan, R. L., & Courey, K. A. (2022) · OSF Preprints (OSF Preprints)
Al'vovskiy, I. K., Tochil'nikov, G. V., & Bespalov, V. G. (2016) · Medical academic journal · doi:10.17816/maj164175-176
DADOU, S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5534281
Health-Related Quality of Life following Sirolimus Treatment for Vascular Anomalies
He, M., Courtemanche, R., Shayan, S., et al. (2025) · Journal of Vascular Anomalies · doi:10.1097/jova.0000000000000129
Privacy-Aware Federated nnU-Net for ECG Page DigitizationPreprint
Nemati, N. (2025) · medRxiv · doi:10.1101/2025.10.25.25338789
Weissgerber, S. C., & Rummer, R. (2025) · Learning and Individual Differences · doi:10.1016/j.lindif.2025.102806
Seya, H., Koike, A., & Iwasaki, K. (2025) · Japanese Journal of JSCE · doi:10.2208/jscejj.25-00035
王泽晗 (2025) · Advances in Applied Mathematics · doi:10.12677/aam.2025.1412518
Li, Y. Y., Au, M. L., Tong, L. K., Fong, I. H., Ren, X. H., & Cheng, L. (2025) · BMC Nursing · doi:10.1186/s12912-025-04203-5 · Cited by 1
Romo, M. L., LaHood, A., Stagg, H. R., et al. (2025) · BMJ Open Respiratory Research · doi:10.1136/bmjresp-2025-003777
Middle and High School Teachers’ Perceived Expertise and Needs in Disciplinary Literacy
Savitz, R. S., Morrison, J. D., Brown, C., Kane, B. D., Aldrich, C., & O’Byrne, W. I. (2025) · AERA Open · doi:10.1177/23328584251400255 · Cited by 2
“(Wasserstein & Lazar, 2016) To date, little DL research has focused on teachers’ perceptions of their DL expertise in a quantitative manner, so we did not use a priori hypotheses suitable for a null hypothesis significance testing approach.”
Yadav, A., & Kumar, J. (2025) · The Indian Journal of Medical Research · doi:10.25259/ijmr_3160_2025
“Current recommendations emphasise reporting effect sizes with confidence intervals, interpreting results relative to the minimum clinically important difference, and avoiding dichotomisation into “significant” versus “non-significant” 2,3 .”
InfluentialArtificial intelligence-based evaluation of perovskite coatings for enhanced solar cell performance
Sierra, J. D., Hernández-Salazar, C. A., & González-Estrada, O. A. (2025) · Journal of Physics Conference Series · doi:10.1088/1742-6596/3164/1/012010
“However, its moderate coefficient of determination (R 2 ≈0.39) highlights limitations in its ability to accurately model extreme values and highly nonlinear interactions [16].”
InfluentialBourne, G., Henderson, N., Dick, J. E., et al. (2025) · BMC Cancer · doi:10.1186/s12885-025-14847-w
“When comparing across two sample, a Cohen’s d of 0.2, 0.5, and 0.8 indicates a small, medium, and large effect, while a Cramer’s V of 0.1, 0.3, and 0.5 indicates a small, medium, and large effect, respectively [27, 28].”
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Ash, A. S. (2025) · Medical Care · doi:10.1097/mlr.0000000000002284
Counterfactual Analysis: Theory and Practice
Derbez, L. P. (2025) · Springer eBooks · doi:10.1007/978-3-032-11862-2_4
Koch, T., Seeger, C., & Müller, P. (2025) · Studienbücher zur Kommunikations- und Medienwissenschaft · doi:10.1007/978-3-658-49131-4_9
Zumitzavan, V. (2025) · Springer eBooks · doi:10.1007/978-981-95-4318-2_7
Nguyen, L., & Sim, J. H. (2025) · Language Variation and Change · doi:10.1017/s0954394525100641
Meslé, R. (2025) · La Revue de l Ostéopathie · doi:10.65071/rev.osteo2025.01.31.1
Beyond p-Values: Probabilistic Thinking and Early-Stage Inference in BiomedicinePreprint
Kah, T. A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.5998034
Thiele, J., Firemoon, P., Johnson, O., et al. (2026) · AIDS Care · doi:10.1080/09540121.2025.2611078
“This approach reflects a growing standard of practice for statistical research that considers p -values on a continuum from 0 to 1 and avoids using strict cutoff values for hypothesis testing (Amrhein et al., 2019; Andrade, 2019; Wasserstein et al., 2019; Wasserstein & Lazar, 2016).”
Okazawa, Y., Yoshida, S., Miyake, K., et al. (2026) · Journal of Cardiothoracic and Vascular Anesthesia · doi:10.1053/j.jvca.2026.01.001
Aarsman, S. R., Dashti, S. G., Bas, G. A. L., Macdonald, J. A., Greenwood, C. J., Hutchinson, D. M., Biden, E. J., Kerr, J. A., Kretschmer, T., Ritland, L., et al. (2026) · Archives of Women s Mental Health · doi:10.1007/s00737-025-01641-7
“We focus our interpretation primarily on the direction, magnitude and precision of point estimates and their public health relevance, rather than their statistical sig - nificance as defined by dichotomisation of p-values (Was - serstein et al. 2019 ; Wasserstein and Lazar 2016 ).”
Lakomý, M., Šácha, J., & Stopka, P. (2026) · International Journal of Training and Development · doi:10.1111/ijtd.70020
Identifying the impact of hypothetical stakes on experimental outcomes and treatment effects
Fitzgerald, J. (2026) · Experimental Economics · doi:10.1017/eec.2025.10035
“12 This is a widely-known misinterpretation of statistical (in)significance, which can yield high Type II error rates if applied generally (see Altman and Bland, 1995; Wasserstein and Lazar, 2016; Fitzgerald, 2025).”
Exploring $f(Q)$ gravity through variable generalized Chaplygin gas and matter creation cosmology
Bhardwaj, Y., & Singh, C. P. (2026) · Astrophysics and Space Science · doi:10.1007/s10509-026-04533-z
“We employ the p-value which is used for statistical inference (Neyman and Pearson 1933; Wasserstein and Lazar 2016) to evaluate the consistency between our cosmological models and the observational data under the assumption that the model in question is correct (i.e., the null hypothesis).”
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Leppänen, L., Leinonen, J., Hellas, A., Kaila, E., & Mannila, L. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328633
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Hemerik, J., & Koning, N. W. (2026) · Statistical Science · doi:10.1214/25-sts983 · Cited by 5
Alfayyadh, A., Williams, J. R., Neal, K., et al. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15020680
“This approach emphasizes estimation with appropriate tests and avoids over-interpretation of p -values in isolation [15,16].”
Agbor, C. F., Dada, B. M., & Adegboyega, S. A.-A. (2025) · Journal of Applied Life Sciences and Environment · doi:10.46909/alse-584192
Electrophysiological correlates of detection and identification awareness for digits and letters
Wiens, S., Greičiūtė, M., Gerdfeldter, B., & Andersson, A. (2026) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2026.109371 · Cited by 1
Ebbing, C., Halmoy, A., Jauniaux, E. R. M., Einum, A., Rasmussen, S., & Moster, D. (2026) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.70164
“In accordance with the American Statistical Association guideline 24 , we emphasized the magnitude of effect size (proportions, ORs with 95% CI) in the interpretation of the results, rather than statistical hypothesis testing with dichotomous inference about the presence or absence of an…”
Choi, J., Lee, K., Chavalarias, D., Shin, J. I., & Ioannidis, J. P. A. (2026) · medRxiv · doi:10.64898/2026.01.14.26344149
Fukuda, T., Tatsumi, K., Inagaki, N., et al. (2026) · Inflammatory Intestinal Diseases · doi:10.1159/000550219
“We reported two-sided 95% CIs as an informal measure of uncertainty and followed the recommendation of the American Statistical Association to avoid using terms such as “statistically significant” [18].”
Barboza, R. S. L., Correia, J. M. D. S., Souto, A., Diniz, G. T. N., & Schiel, N. (2026) · Frontiers in Amphibian and Reptile Science · doi:10.3389/famrs.2025.1719531
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Dou, S., Hu, Y., Feng, S., Wu, Y., & Zou, D. (2026) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2026.3656384
“Furthermore, we test for sample variability using the T-test [80], and the P-values [81] obtained by all algorithms are all less than 0.05, demonstrating significant variability between clones and non-clones.”
InfluentialDomazetoska, I., & Patrick, C. J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6118207
Sohn, M., Ritschl, V., Tartaglia, D., Chiarugi, M., Strambi, S., Brillantino, A., Agha, A., May, M. C., Kim, M., Maghames, M., et al. (2026) · Colorectal Disease · doi:10.1111/codi.70356 · Cited by 1
Metadata
- Authors
- Wasserstein, R. L., & Lazar, N. A.
- Affiliations
- American Statistical Association, 732 North Washington Street, Alexandria, VA 22314-1943
- American Statistical Association (US)
- ORCID
- Lazar, Nicole A.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 2016-04-02
- Volume
- 70
- Issue
- 2
- Pages
- 129-133
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2293040502
- Semantic Scholar
- 81a65f23474ffceb2481836328608102950da979
- Cited by
- 6,306
- References
- 45
- Citations by year
- 2026: 625 · 2025: 629 · 2024: 575 · 2023: 543 · 2022: 642 · 2021: 676 · 2020: 678 · 2019: 666 · 2018: 596 · 2017: 438 · 2016: 226
- FWCI
- 649.74
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The American Statistician (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- p-values, statistical evidence, p-value interpretation, statistical inference, hypothesis testing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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