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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“In light of the American Statistical Association’s 2016 “Statement on P -Values” (Wasserstein and Lazar 2016) and the subsequent publication of an issue of The American Statistician devoted to “Moving to a World Beyond ‘ P < 0.05’” (Wasserstein et al. 2019), several journals revised their reporting…”
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Mitro, S. D., Waetjen, L. E., Lee, C., Wise, L. A., Zaritsky, E. F., Harlow, S. D., Khoudary, S. R. E., Santoro, N. F., Solomon, D. H., Thurston, R. C., et al. (2024) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgae625 · Cited by 14
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“A frequent misconception is that the p-value is the probability that findings are due to chance (alone) or – put in other words but generally meaning the same – the chance that the null hypothesis (H0) is true [2].”
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“…can be seen as special components of a bigger CD picture, and these connections can be worked out more fully, both for enhanced interpretation and for better assessments of well-understood hypotheses; cf. the still ongoing debate on the uses and many misuses of p-values (Wasserstein & Lazar, 2016).”
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“Since the superiority was reported previously [15], statistical comparisons were not performed in this report in accordance with the American Statistical Association’s statement on p values [18].”
ResultMaksymowych, W. P., Strand, V., Nash, P. T., Yazıcı, Y., Thom, H. H. Z., Hünger, M., Kalyvas, C., Gandhi, K. K., Porter, B. O., & Jugl, S. M. (2018) · European Journal of Rheumatology · doi:10.5152/eurjrheum.2018.18162 · Cited by 14
Alizad, V., Meinzer, M., Frossard, L. A., Polman, R. C. J., Smith, S. S., & Kerr, G. (2018) · Trials · doi:10.1186/s13063-018-2982-z · Cited by 13
Frommelt, P. C., Hu, C., Trachtenberg, F. L., Baffa, J. M., Boruta, R. J., Chowdhury, S. M., Cnota, J. F., Dragulescu, A., Levine, J. C., Lu, J. C., et al. (2019) · Circulation Cardiovascular Imaging · doi:10.1161/circimaging.118.007865 · Cited by 13
Appropriate Standards of Evidence for Education Policy Decision Making
Conaway, C., & Goldhaber, D. D. (2019) · Education Finance and Policy · doi:10.1162/edfp_a_00301 · Cited by 14
Most recommended medical interventions reach P < 0.005 for their primary outcomes in meta-analyses
Koletsi, D., Solmi, M., Pandis, N., Fleming, P. S., Correll, C. U., & Ioannidis, J. P. A. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz241 · Cited by 14
Vliek, L., Overbeek, G. J., & de Castro, B. O. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225504 · Cited by 15
An Analysis of Nonsignificant Results in Audiology Using Bayes Factors
Brydges, C. R., & Gaeta, L. (2019) · Journal of Speech Language and Hearing Research · doi:10.1044/2019_jslhr-h-19-0182 · Cited by 14
Luck, C. C., Patterson, R. R., & Lipp, O. V. (2019) · Psychophysiology · doi:10.1111/psyp.13516 · Cited by 16
Miyachi, Y., Kaido, T., Hirata, M., Iwamura, S., Yao, S., Shirai, H., Kamo, N., Uozumi, R., Yagi, S., & Üemoto, S. (2020) · American Journal of Transplantation · doi:10.1111/ajt.15884 · Cited by 14
Rowe, S. M., Godden, S., Nydam, D. V., Lago, A., Vasquez, A. K., Royster, E., & Timmerman, J. A. (2020) · Journal of Dairy Science · doi:10.3168/jds.2019-17884 · Cited by 14
Beyer, C., Schwahn, C., Meyer, G. F., & Söhnel, A. (2020) · Journal of Prosthetic Dentistry · doi:10.1016/j.prosdent.2020.01.034 · Cited by 14
Learning Lessons on Reproducibility and Replicability in Large Scale Genome-Wide Association Studies
Lin, X. (2020) · Harvard Data Science Review · doi:10.1162/99608f92.33703976 · Cited by 17
“…the risks of irreproducible results (Baker et al., 2016; Fanelli, 2018), and called for improvements in the rigor and reproducibility in research (Collins & Tabak, 2014; Redish et al., 2018) and, in particular, the practice of statistical significance using p-values (Wasserstein and Lazar, 2016).”
BackgroundThe fiscal response to revenue shocks
Berset, S., Huber, M., & Schelker, M. (2022) · International Tax and Public Finance · doi:10.1007/s10797-022-09727-z · Cited by 15
Diana, A., Haszard, J. J., Sari, S. Y. I., Rahmannia, S., Fathonah, A., Sofiah, W. N., Rizqi, H., Haekal, R., Gilmartin, A. A., Harper, M. J., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0247247 · Cited by 16
Vandekar, S., & Stephens, J. (2021) · Human Brain Mapping · doi:10.1002/hbm.25374 · Cited by 13
“…increasing criticism of PVT in the context of hypothesis testing and an increased interest in potential alternatives (Bowring et al., 2019; Bowring, Telschow, Schwartzman, & Nichols, 2021; Chen et al., 2019; Chen, Taylor, & Cox, 2017; Wasserstein & Lazar, 2016; Wasserstein, Schirm, & Lazar, 2019).”
BackgroundGolding, S. E., Ogden, J., & Higgins, H. M. (2021) · Antibiotics · doi:10.3390/antibiotics10040445 · Cited by 14
“Indeed, researchers are encouraged to avoid judgements about results based on statistical inference, and to not describe results as significant or otherwise based solely on p-values, but to consider the results in the context of what is already known about a topic [93,94].”
BackgroundResultSentence Comprehension as a Cognitive Process: A Computational Approach
Vasishth, S., & Engelmann, F. (2021) · Cited by 14
The frequent insignificance of a “significant” p ‐value
McGiffin, D. C., Cumming, G., & Myles, P. S. (2021) · Journal of Cardiac Surgery · doi:10.1111/jocs.15960 · Cited by 13
Ridder, L. W., Morris, L. R., Day, M., & Kerns, B. (2022) · Rangeland Ecology & Management · doi:10.1016/j.rama.2021.09.003 · Cited by 14
Nelms, D. W., Vargas, H. D., Bedi, R. S., & Paruch, J. L. (2021) · Diseases of the Colon & Rectum · doi:10.1097/dcr.0000000000002146 · Cited by 14
Vargas, M., Marra, A., Buonanno, P., Coviello, A., Iacovazzo, C., & Servillo, G. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10225287 · Cited by 14
“The use of the p-value approach has been heavily criticized in recent years by the American Statistical Association [3].”
BackgroundMethodBartsch, C. E., Dürr, L., Forster, A., & Koob, C. (2021) · Zeitschrift für Evidenz Fortbildung und Qualität im Gesundheitswesen · doi:10.1016/j.zefq.2021.09.008 · Cited by 17
Tso, I. F., Taylor, S. F., & Johnson, T. D. (2021) · Journal of Abnormal Psychology · doi:10.1037/abn0000707 · Cited by 13
Accounting for intangible assets – insights from meta-analysis of R&D research
Jeny, A., & Moldovan, R. (2021) · Journal of Accounting Literature · doi:10.1108/jal-11-2021-0004 · Cited by 17
Collin, L. J., Ross‐Driscoll, K., Nash, R., et al. (2022) · Annals of Surgical Oncology · doi:10.1245/s10434-022-11720-z · Cited by 14
“No hypothesis testing was performed.(28,29) All analyses were conducted using SAS v9.”
MethodMaternal diet quality moderates associations between parabens and birth outcomes
Pacyga, D. C., Talge, N. M., Gardiner, J. C., Calafat, A. M., Schantz, S. L., & Strakovsky, R. S. (2022) · Environmental Research · doi:10.1016/j.envres.2022.114078 · Cited by 16
Nieto, A. M., Catalfio, A. M., Quintanilla, H. P., Alonso‐Caraballo, Y., & Ferrario, C. R. (2022) · Obesity · doi:10.1002/oby.23613 · Cited by 14
“92), input resistance (Figure 1F: 2-tailed unpaired t test: t[27] = 0.”
BackgroundMethodInfluentialA scoping review of studies exploring physical activity and cognition among persons with cancer
Brunet, J., & Sharma, S. (2023) · Journal of Cancer Survivorship · doi:10.1007/s11764-023-01441-x · Cited by 14
Null regions: a unified conceptual framework for statistical inference
Smiley, A. H., Glazier, J. J., & Shoda, Y. (2023) · Royal Society Open Science · doi:10.1098/rsos.221328 · Cited by 18
Circular and unified analysis in network neuroscience
Rubinov, M. (2023) · eLife · doi:10.7554/elife.79559 · Cited by 16
“Third, significance can denote the rejection of a null hypothesis and also signal scientific importance ( Wasserstein and Lazar, 2016 ).”
BackgroundComparing motor-vehicle crash risk of EU and US vehicles
Flannagan, C. A. C., Bálint, A. F., Klinich, K. D., et al. (2018) · Accident Analysis & Prevention · doi:10.1016/j.aap.2018.01.003 · Cited by 14
“Failure to reject the null hypothesis is not evidence for the null (Wasserstein and Lazar, 2016).”
BackgroundYui, K., Tanuma, N., Yamada, H., & Kawasaki, Y. (2016) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2016.08.003 · Cited by 15
Antenatal glucocorticoids and neonatal inflammation-associated proteins
Faden, M., Holm, M., Allred, E. N., Fichorova, R. N., Dammann, O., & Leviton, A. (2016) · Cytokine · doi:10.1016/j.cyto.2016.09.015 · Cited by 14
The chemometrics revolution re‐examined
Brown, S. D. (2017) · Journal of Chemometrics · doi:10.1002/cem.2864 · Cited by 14
Osta-Omar, S. M., & Micallef, C. (2017) · Data · doi:10.3390/data2010006 · Cited by 14
“05, which indicates that both of the independent variables (temperature and concentration) are statistically significant [11].”
BackgroundThe Effect of Vaccination Against Human Papillomavirus on Fecundability
McInerney, K. A., Hatch, E. E., Wesselink, A. K., Mikkelsen, E. M., Rothman, K. J., Perkins, R. B., & Wise, L. A. (2017) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12408 · Cited by 14
Augustine, J. M., Aveldanes, J. M., & Pfeffer, C. A. (2017) · Population review · doi:10.1353/prv.2017.0007 · Cited by 14
Loet Leydesdorff, A., Bornmann, L., & Mingers, J. (2019) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24130 · Cited by 15
“…measurement precision is high enough, and large effects may produce unimpressive p-values if the sample size is small or measurements are imprecise” (Wasserstein & Lazar, 2016, 1 Bornmann, Mutz, and Daniel’s (2013) analysis of LR 2011 compared the stability intervals with other possible ways to…”
BackgroundJones, L. M., Wright, K., Jack, A. I., Friedman, J. P., Fresco, D. M., Veinot, T. C., Lü, W., & Moore, S. M. (2018) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24098 · Cited by 14
“Consistent with the American Statistical Association statement on p-value, we emphasized the magnitude of the effect sizes, nonzero correlation coefficient, and its clinical relevance (Wasserstein & Lazar, 2016).”
MethodVilas, M. G., Santilli, M., Mikulan, E. P., Adolfi, F., Caro, M. M., Manes, F., Herrera, E., Sedeño, L., Ibáñez, A., & García, A. M. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.01.007 · Cited by 13
“…et al., 2003; Moreno and Kutas, 2005; Nichols and Joanisse, 2016; Pakulak and Neville, 2011; Santilli et al., 2018; Waldron and Hernandez, 2013; Weber-Fox and Neville, 2001, 1996) and our findings replicate a general pattern of results in AoA research, whereby neural responses are more…”
InfluentialArtificial Intelligence in Medicine: Validation and Study Design
Oakden-Rayner, L., & Palmer, L. J. (2019) · Artificial Intelligence in Medical Imaging · doi:10.1007/978-3-319-94878-2_8 · Cited by 14
Grawe, S. J., & Ralston, P. M. (2019) · International Journal of Physical Distribution & Logistics Management · doi:10.1108/ijpdlm-03-2018-0118 · Cited by 15
Interval-Based Hypothesis Testing and Its Applications to Economics and Finance
Kim, J. H., & Robinson, A. P. (2019) · Econometrics · doi:10.3390/econometrics7020021 · Cited by 14
How null results can be significant for physics education research
Conlin, L. D., Kuo, E., & Hallinen, N. R. (2019) · Physical Review Physics Education Research · doi:10.1103/physrevphyseducres.15.020104 · Cited by 14
Tabullo, Á., Shalóm, D. E., Sevilla, Y., Gattei, C., París, L., & Wainselboim, A. J. (2019) · Mind Brain and Education · doi:10.1111/mbe.12205 · Cited by 17
Strassle, P. D., Sickbert-Bennett, E. E., Klompas, M., Lund, J. L., Stewart, P. W., Marx, A. H., DiBiase, L., & Weber, D. J. (2019) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2019.241 · Cited by 15
Rhetorical Citizenship and the Science of Science Communication
Fahnestock, J. (2019) · Argumentation · doi:10.1007/s10503-019-09499-7 · Cited by 16
Zeid, N. G., Mohamed, A. S., El-Fouly, M., et al. (2019) · Plastic Surgery · doi:10.1177/2292550319880919 · Cited by 14
The work–family interface in a gendered cultural context: Cross-national analysis of work stress
Davis, S. N. (2020) · International Journal of Cross Cultural Management · doi:10.1177/1470595820904111 · Cited by 16
“10 threshold, appropriate when measures may be imprecise (Wallerstein and Lazar, 2016), as may be the case given that the coefficient in question is for a cross-level interaction that separates out family-to-work conflict (2013; a concept with more variability in measurement precision than 66 International Journal of…”
BackgroundInfluentialKruis, N. E., & Choi, J. (2020) · Journal of Criminal Justice Education · doi:10.1080/10511253.2020.1736112 · Cited by 17
Condy, E. E., Friedman, B. H., & Gandjbakhche, A. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.575589 · Cited by 15
“The sole reliance on p-values, and consequently, the correcting of p-values, is cautioned by the American Statistical Association (Wasserstein and Lazar, 2016).”
BackgroundFierro, P., Hughes, R. M., & Valdovinos, C. (2021) · Neotropical Entomology · doi:10.1007/s13744-021-00900-3 · Cited by 14
The Current State of Undergraduate Bayesian Education and Recommendations for the Future
Dogucu, M., & Hu, J. (2022) · The American Statistician · doi:10.1080/00031305.2022.2089232 · Cited by 14
“Bayesian concepts, such as Bayes factor and credible intervals, are among the recommended measures of evidence as alternatives to the p -value and confidence intervals (Wasserstein & Lazar 2016).”
BackgroundInference on Time-Invariant Variables Using Panel Data: A Pretest EstimatorPreprint
Chatelain, J., & Ralf, K. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3165633 · Cited by 14
Call for Papers-Special Issue on Experiments in Organizational Theory
(2019) · Organization Science · doi:10.1287/orsc.2018.1257 · Cited by 14
“– Reporting of exact p-values and statistical power, discussion of effect sizes, and use of alternatives to null hypothesis testing (Wasserstein and Lazar 2016).”
MethodMichel, M. C., Murphy, T. J., & Motulsky, H. J. (2019) · Drug Metabolism and Disposition · doi:10.1124/dmd.119.090027 · Cited by 13
Morning or Evening? An Examination of Circadian Rhythms of CS1 Students
Zavgorodniaia, A., Shrestha, R., Leinonen, J., Hellas, A., & Edwards, J. (2021) · 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET) · doi:10.1109/icse-seet52601.2021.00036 · Cited by 13
“We report p-values of our statistical tests as one component among others that together contribute to understanding of our results [43].”
Trontin, J., Sow, M. D., Delaunay, A., et al. (2024) · PLANT PHYSIOLOGY · doi:10.1093/plphys/kiae600 · Cited by 13
The Impact of Artificial Intelligence Capabilities on Decision-Making Performance
Guthrie, C. H., Wamba, S. F., de Queiroz, M. M., & Cai, H. (2025) · Journal of Global Information Management · doi:10.4018/jgim.395344 · Cited by 22
Nguyen, T. T. H. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-49046-5_1 · Cited by 13
Connecting Theory to Life: Learning Greener Electrochemistry by Taking Apart a Common Battery
Keen, C., Couture, S., Meseh, N. A. E., et al. (2020) · Journal of Chemical Education · doi:10.1021/acs.jchemed.9b00840 · Cited by 13
Bayesian Analyses of Cardiovascular Trials—Bringing Added Value to the Table
Brophy, J. M. (2021) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2021.03.014 · Cited by 14
Doberschütz, P. H., Schwahn, C., & Krey, K. (2021) · Clinical Oral Investigations · doi:10.1007/s00784-021-04006-3 · Cited by 13
Wade, R. G., Bourke, G., Wormald, J. C. R., Totty, J. P., Stanley, G. H. M., Lewandowski, A., Rakhra, S. S., Gardiner, M. D., Collaborative, T. C., Bindra, R. R., et al. (2021) · BJS Open · doi:10.1093/bjsopen/zrab117 · Cited by 16
Pinos-Navarrete, A., Abarca-Álvarez, F. J., & Martos, J. C. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19052580 · Cited by 13
“To this end, and following the recommendations of the American Statistical Association [71], we quantified the statistical significance and the Effect Size (ES) for each variable–profile pair [72].”
MethodXia, J., & O'Shea, C. M. (2022) · Leadership and Policy in Schools · doi:10.1080/15700763.2022.2056059 · Cited by 13
“To interpret the results, we followed the most recent recommendations (Kline, 2020; Wasserstein et al., 2019) including the American Statistical Association ( ASA) Statement on P-Values and Statistical Significance (Wasserstein & Lazar, 2016).”
MethodHau, J., Baker, A., Chaaban, C., Kohli, J. S., Keehn, R. J. J., Linke, A. C., Mash, L. E., Wilkinson, M. K., Kinnear, M., Müller, R., et al. (2022) · Cortex · doi:10.1016/j.cortex.2022.04.004 · Cited by 13
Fredriksen, A. B., & van den Tillaar, R. (2022) · Journal of Functional Morphology and Kinesiology · doi:10.3390/jfmk7030058 · Cited by 13
“It suggests that external weights between conditions have a practical effect [19], but due to the low number of repetitions and durability, we cannot state this with high probability.”
BackgroundSimeone, R. M., House, L. D., von Essen, B. S., Kortsmit, K., Virella, W. H., Bernal, M. I. V., Galang, R. R., D’Angelo, D. V., Shapiro‐Mendoza, C. K., & Ellington, S. (2023) · Public Health Reports · doi:10.1177/00333549221142571 · Cited by 13
“17,18 Instead, we reported differences in prevalence > 5% or an increased prevalence ratio of at least 50%.”
BackgroundCheung, R. W., Willan, K., Dickerson, J., & Bowyer‐Crane, C. (2023) · BMJ Paediatrics Open · doi:10.1136/bmjpo-2022-001764 · Cited by 13
Weight gain patterns among pregnancies with obesity and small‐ and large‐for‐gestational‐age births
Petersen, J. M., Hutcheon, J. A., Bodnar, L. M., Parker, S. E., Ahrens, K. A., & Werler, M. M. (2023) · Obesity · doi:10.1002/oby.23693 · Cited by 14
“05 or 95% CI excluding 1) as recommended by the American Statistical Association [19].”
BackgroundInfluentialPereira, C. P., Santos, R., Nushi, V., et al. (2023) · International Journal of Legal Medicine · doi:10.1007/s00414-023-03011-3 · Cited by 13
Ribeiro, C., Farmer, C., de Magalhães, J. P., & Freitas, A. A. (2023) · Aging · doi:10.18632/aging.204866 · Cited by 13
Farrington, D. P., & Malvaso, C. (2023) · International Journal of Offender Therapy and Comparative Criminology · doi:10.1177/0306624x231188231 · Cited by 14
“In concordance with the American Statistical association (e.g. Wasserstein & Lazar, 2016) and editorial statements from journals (e.g. Sullivan & Feinn, 2012; Trafimow & Marks, 2015), we believe that effect sizes are more important than p-values in indicating the strength of relationships (e.g.…”
Comparative Safety of Antidepressants in Adults with CKD
Zhu, N., Xu, H., Lagerberg, T., Johnell, K., Carrero, J. J., & Chang, Z. (2023) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.0000000000000348 · Cited by 15
“35 All statistical analyses were performed using R software version 4.0.5 (R Foundation for Statistical Computing).”
MethodInfluentialChoueiri, T. K., Donahue, A. C., Braun, D. A., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-0680 · Cited by 13
“These analyses should be interpreted alongside other factors including sample size, effect size, and the exploratory nature of the analyses while also acknowledging the limitation of using P values as the evidence against the null hypothesis (46–48).”
BackgroundCourtenay, L. A., Barbero-García, I., Martínez-Lastras, S., Pozo, S. D., de la Calle, M. C., Garrido, A., Guerrero, D., Hernández‐López, D., & González‐Aguilera, D. (2024) · PLoS ONE · doi:10.1371/journal.pone.0300400 · Cited by 13
For a proper use of frequentist inferential statistics in public health
Rovetta, A., Mansournia, M. A., & Vitale, A. (2024) · Global Epidemiology · doi:10.1016/j.gloepi.2024.100151 · Cited by 17
“” Wasserstein and Lazar [50], representatives of the American Statistical Association (ASA), chose to start their article on the ASA's official statement on the P -value with this declaration by Professor George Cobb (Professor Emeritus of Mathematics and Statistics at Mount Holyoke College).”
BackgroundNaghipour, S., Cox, A. J., Fisher, J. J., Plan, M. R., Stark, T., West, N. P., Peart, J. N., Headrick, J. P., & Toit, E. F. D. (2024) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-024-01368-y · Cited by 17
“Values of p 0.10 are highlighted as potentially relevant biological responses worthy of study, in accordance with recommendations of the American Statistical Association [34].”
ResultInfluentialChin, S., & Collins, J. E. (2024) · The Journal of Rheumatology · doi:10.3899/jrheum.2024-0519 · Cited by 14
Guo, R., Shamsi, M. H., Sharifi, M., et al. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.124411 · Cited by 13
“The P-value associated with the KS statistic helps determine the significance of the test result; a P-value ≤ 0.05 typically indicates a statistically significant difference between the distributions [41].”
InfluentialAdjusting the significance of daily climate responses in tree-ring proxies
Torbenson, M. C. A., Stagge, J. H., Chen, F., Ziaco, E., & Esper, J. (2024) · Journal of Forestry Research · doi:10.1007/s11676-024-01799-3 · Cited by 13
“That discussion, in itself, is part of ongoing conversations that concern how researchers perceive and use statistical significance (Lin et al. 2013; Wasserstein and Lazar 2016).”
Pohl, J., Verheyden, G., Held, J. P. O., Luft, A. R., Easthope, C. A., & Veerbeek, J. M. (2025) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01512-9 · Cited by 12
“We focused on the strength and direction of the relationships, excluding p-values due to their susceptibility to misinterpretation and sample size dependency [71].”
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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