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
Cites
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011) · Psychological Science · doi:10.1177/0956797611417632 · Cited by 6,567
(1947) · The American Statistician · doi:10.1080/00031305.1947.10501534 · Cited by 3,745
The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis
Hoenig, J. M., & Heisey, D. M. (2001) · The American Statistician · doi:10.1198/000313001300339897 · Cited by 2,046
Statistics notes: Absence of evidence is not evidence of absence
Altman, D. G., & Bland, J. M. (1995) · BMJ · doi:10.1136/bmj.311.7003.485 · Cited by 1,946
Smithson, M. J. (2000) · SAGE Publications Ltd eBooks · doi:10.4135/9781446218525 · Cited by 1,871
Bayesian statistical inference for psychological research.
Edwards, W., Lindman, H., & Savage, L. J. (1963) · Psychological Review · doi:10.1037/h0044139 · Cited by 1,734
Scientific method: Statistical errors
Nuzzo, R. (2014) · Nature · doi:10.1038/506150a · Cited by 1,536
Why Most Discovered True Associations Are Inflated
Ioannidis, J. P. A. (2008) · Epidemiology · doi:10.1097/ede.0b013e31818131e7 · Cited by 1,495
Sterne, J. A. C. (2001) · BMJ · doi:10.1136/bmj.322.7280.226 · Cited by 1,466
Contradicted and Initially Stronger Effects in Highly Cited Clinical Research
Ioannidis, J. P. A. (2005) · JAMA · doi:10.1001/jama.294.2.218 · Cited by 1,465
Research works printed but not linked: 5
- Leek, J. (2014), “On the Scalability of Statistical Procedures: Why the p-Value Bashers Just Don't Get It,” Simply Statistics Blog, Available at http://simplystatistics.org/2014/02/14/on-the-scalability-of-statistical-procedures-why-the-p-value-bashers-just-dont-get-it/.
- Gelman A. and Loken E. (2014) “The Statistical Crisis in Science [online] ” American Scientist 102. Available at http://www.americanscientist.org/issues/feature/2014/6/the-statistical-crisis-in-science · DOI · Paper page
- Greenland, S., and Poole, C. (2011), “Problems in Common Interpretations of Statistics in Scientific Articles, Expert Reports, and Testimony,” Jurimetrics, 51, 113–129.
- 10.1214/13-AOS1123 · DOI
- Lavine, M. (1999), “What is Bayesian Statistics and Why Everything Else is Wrong,” UMAP Journal, 20, 2.
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Effect size and statistical power in the rodent fear conditioning literature – A systematic review
Carneiro, C. F. D., Moulin, T. C., Macleod, M. R., & Amaral, O. B. (2018) · PLoS ONE · doi:10.1371/journal.pone.0196258 · Cited by 48
“This approach, however, has well-described limitations that can lead to erroneous conclusions when researchers rely on p values alone to judge results (Nuzzo, 2014; Colquhoun, 2014; Halsey et al., 2015; Altman and Krzywinski, 2016; Wasserstein and Lazar, 2016; Greenland et al., 2016).”
ResultReview on Statistical Modeling of Travel Time Variability for Road-Based Public Transport
Büchel, B., & Corman, F. (2020) · Frontiers in Built Environment · doi:10.3389/fbuil.2020.00070 · Cited by 43
Dismantling the Fragility Index: A demonstration of statistical reasoning
Potter, G. E. (2020) · Statistics in Medicine · doi:10.1002/sim.8689 · Cited by 41
Ayala, E. S., Amutio, A., Franco, C., & Mañas, I. M. (2020) · Nutrients · doi:10.3390/nu12082450 · Cited by 42
P-valor e dimensão do efeito em estudos clínicos e experimentais
Miola, A. C., & Miot, H. A. (2021) · Jornal Vascular Brasileiro · doi:10.1590/1677-5449.210038 · Cited by 44
How to Choose the Level of Significance: A Pedagogical NotePreprint
Kim, J. H. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.2652773 · Cited by 148
Cassidy, S. A., Dimova, R., Giguère, B., Spence, J. R., & Stanley, D. J. (2019) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245919858072 · Cited by 39
“This is but one of many common errors researchers make when interpreting p values (cf. Wasserstein & Lazar, 2016; Wasserstein, Schirm, & Lazar, 2019).”
BackgroundLansford, J. L., Barnes, B. C., Rice, B. M., & Jensen, K. F. (2022) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.2c00841 · Cited by 44
Smith, M. L., Bull, C. J., Holmes, M. V., Smith, G. D., Sanderson, E. C. M., Anderson, E. L., & Bell, J. A. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104503 · Cited by 40
Prevalence of Adverse Childhood Experiences Among Adolescents
Swedo, E. A., Niolon, P. H., Anderson, K. N., Li, J., Brener, N. D., Mpofu, J. J., Aslam, M. V., & Underwood, J. M. (2024) · PEDIATRICS · doi:10.1542/peds.2024-066633 · Cited by 43
Sadeghi, S. A., Awalgaonkar, N. M., Karava, P., et al. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.10.046 · Cited by 41
Why are p-Values Controversial?
Kuffner, T. A., & Walker, S. G. (2017) · The American Statistician · doi:10.1080/00031305.2016.1277161 · Cited by 41
“This headline-grabbing decision elicited responses from the International Society for Bayesian Analysis (ISBA) (Schmidt et al. 2015) and the American Statistical Association (ASA) (Wasserstein and Lazar 2016), among others.”
BackgroundHuang, S., Ting, I., Huang, A. M., et al. (2017) · Critical Care · doi:10.1186/s13054-017-1876-x · Cited by 41
“95%CI was presented wherever possible and when effect size was more informative, otherwise P value was presented [13].”
BackgroundCraftwashing in the U.S. Beer Industry
Howard, P. H. (2017) · Beverages · doi:10.3390/beverages4010001 · Cited by 41
“356 1 Following recent suggestions from the American Statistical Association, p values are reported, but not used as a measure of importance [44].”
MethodHow diversified is cropping in Malawi? Patterns, determinants and policy implications
Kankwamba, H., Kadzamira, M., & Pauw, K. (2018) · Food Security · doi:10.1007/s12571-018-0771-x · Cited by 41
“Table 3 provides detailed results of average values of farmlevel crop diversification across the ADDs and over the two 5 In all cases in this paper, we advise and conform to the strict interpretation of the p-value according to Wasserstein and Lazar (2016).”
MethodBilingualism in the Community: Code-switching and Grammars in Contact
Cacoullos, R. T., & Travis, C. E. (2018) · Cited by 41
Galvagno, S. M., Sikorski, R. A., Floccare, D. J., et al. (2020) · Shock · doi:10.1097/shk.0000000000001567 · Cited by 41
Can Students' Spatial Skills Predict Their Programming Abilities?
Bockmon, R., Cooper, S., Gratch, J. S., et al. (2020) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/3341525.3387380 · Cited by 41
“The use of a one-way analysis of variance test (ANOVA) test, or a Kruskal-Wallis non-parametric (if the data was not normally distributed), was used to test for significant differences between groups [26].”
MethodP-values – a chronic conundrum
Gao, J. (2020) · BMC Medical Research Methodology · doi:10.1186/s12874-020-01051-6 · Cited by 51
Speech metrics, general disability, brain imaging and quality of life in multiple sclerosis
Noffs, G., Boonstra, F. M. C., Perera, T., Butzkueven, H., Kolbe, S., Maldonado, F., Lizama, L. E. C., Galea, M. P., Stankovich, J. M., Evans, A. H., et al. (2020) · European Journal of Neurology · doi:10.1111/ene.14523 · Cited by 38
“As with conventional P values [40], the critical P should be used only as a reference value for interpreting results rather than a fixed threshold for significance.”
BackgroundZulman, D. M., Maciejewski, M. L., Grubber, J. M., Weidenbacher, H. J., Blalock, D. V., Zullig, L. L., Greene, L., Whitson, H. E., Hastings, S. N., & Smith, V. A. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.21457 · Cited by 41
History and nature of the Jeffreys–Lindley paradox
Wagenmakers, E., & Ly, A. (2022) · Archive for History of Exact Sciences · doi:10.1007/s00407-022-00298-3 · Cited by 49
“Informally, the p value is the chance under the null hypothesis of finding a test statistic at least as extreme as the one obtained (e.g., Wasserstein and Lazar 2016).”
On p-Values and Statistical Significance
Bonovas, S., & Piovani, D. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12030900 · Cited by 51
“The ASA’s statement [1] outlined above discusses the main issues regarding the use and interpretation of p-values in applied research.”
BackgroundInfluentialKoroukian, S. M., Douglas, S. L., Vu, L., Fein, H. L., Gairola, R., Warner, D. F., Schiltz, N. K., Cullen, J., Owusu, C., Sajatovic, M., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.0394 · Cited by 41
Roelants, J. A., Vlaardingerbroek, H., van den Akker, C. H. P., et al. (2016) · Journal of Parenteral and Enteral Nutrition · doi:10.1177/0148607116678196 · Cited by 40
Lyngbakken, M. N., Skranes, J. B., de Lemos, J. A., Nygård, S., Dalen, H., Hveem, K., Røsjø, H. R., & Omland, T. (2016) · Circulation · doi:10.1161/circulationaha.116.023726 · Cited by 40
Leadership in Statistics: Increasing Our Value and Visibility
Gibson, E. W. (2017) · The American Statistician · doi:10.1080/00031305.2017.1336484 · Cited by 40
“More recently, the ASA issued a position statement for the scientific community on the “proper use and interpretation of the p-value” (Wasserstein and Lazar 2016).”
BackgroundMarks, M., Hensler, S., Wehrli, M., et al. (2017) · The Journal Of Hand Surgery · doi:10.1016/j.jhsa.2017.07.023 · Cited by 40
Grolleau, F., Collins, P. G. S., Smarandache, A., Pirracchio, R., Gakuba, C., Boutron, I., Busse, J. W., Devereaux, P. J., & Manach, Y. L. (2018) · Critical Care Medicine · doi:10.1097/ccm.0000000000003527 · Cited by 41
Nadig, A., Flanagan, T. D., White, K., & Bhatnagar, S. (2018) · Autism Research · doi:10.1002/aur.2027 · Cited by 47
The dark side of the force: Multiplicity issues in network meta‐analysis and how to address them
Efthimiou, O., & White, I. R. (2019) · Research Synthesis Methods · doi:10.1002/jrsm.1377 · Cited by 39
“The concept of statistical significance, however, has attracted a lot of criticism lately.(10,11) For example, as discussed by Gelman and colleagues,(12,13) it is rather unlikely that any relative treatment effect between different interventions would be exactly zero in the real world (although they might be practical…”
BackgroundSiegwald, L., Caboche, S., Even, G., Viscogliosi, É., Audebert, C., & Chabé, M. (2019) · Microorganisms · doi:10.3390/microorganisms7100393 · Cited by 41
“Likewise, robust statistical tools are used to interpret the results and extract relevant biological features, and a lot of warnings have been raised around their interpretation [4,5].”
MethodProjecting the future of rainfall extremes: Better classic than trendy
Iliopoulou, T., & Koutsoyiannis, D. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.125005 · Cited by 45
Statistical fragility of randomized clinical trials in shoulder arthroplasty
McCormick, K. L., Tedesco, L. J., Swindell, H. W., Forrester, L. A., Jobin, C. M., & Levine, W. N. (2020) · Journal of Shoulder and Elbow Surgery · doi:10.1016/j.jse.2020.10.028 · Cited by 40
The fragility index can be used for sample size calculations in clinical trials
Baer, B. R., Gaudino, M. F. L., Fremes, S. E., Charlson, M. E., & Wells, M. T. (2021) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2021.08.010 · Cited by 45
Greenland, S. (2023) · Scandinavian Journal of Statistics · doi:10.1111/sjos.12645 · Cited by 36
“…of contextually relevant discrepancy measures [Amrhein et al., 2019a, 2019b; Amrhein & Greenland, 2022; Greenland et al., 2016, 2022, 2023; Hurlbert & Lombardi, 2009; McShane et al., 2019; Rafi & Greenland, 2020; Rothman et al., 2008, Ch. 10; Wasserstein & Lazar, 2016; Wasserstein et al., 2019].”
Komaroff, E. (2020) · Journal of Statistical Theory and Practice · doi:10.1007/s42519-020-00115-6 · Cited by 44
Min, J., Kim, S., Shin, I., Park, Y.-B., & Lim, Y.-W. (2021) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2021.05.001 · Cited by 40
Pick, J. L., Kasper, C., Allegue, H., Dingemanse, N. J., Dochtermann, N. A., Laskowski, K. L., Lima, M. R., Schielzeth, H., Westneat, D. F., WRIGHT, J. M., et al. (2023) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.14200 · Cited by 43
Villoz, F., Filippini, T., Ortega, N., Kopp‐Heim, D., Voortman, T., Blum, M. R., Giovane, C. D., Vinceti, M., Rodondi, N., & Chocano-Bedoya, P. O. (2023) · Advances in Nutrition · doi:10.1016/j.advnut.2023.100160 · Cited by 41
“We have focused our description and interpretation of the results on assessing the size of point estimates and their statistical precision (CIs) measures without P value fi xed cutpoints [28 – 30].”
BackgroundA New Look at P Values for Randomized Clinical Trials
van Zwet, E. W., Gelman, A., Greenland, S., Imbens, G. W., Schwab, S., & Goodman, S. N. (2023) · NEJM Evidence · doi:10.1056/evidoa2300003 · Cited by 47
Four principles for improved statistical ecology
Popovic, G. C., Mason, T. J., Drobniak, S. M., Marques, T. A., Potts, J., Joo, R., Altwegg, R., Burns, C. C. I., Mccarthy, M. A., Johnston, A., et al. (2024) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.14270 · Cited by 59
“A p - value is not the probability that the null hypothesis is true, nor is it an indicator of the size of the effect, nor the probability that the data were produced by ran - dom chance alone, among other misinterpretations (Wasserstein & Lazar, 2016 ).”
BackgroundSad or Happy? The Effects of Emotions on Stated Preferences for Environmental Goods
Hanley, N. D., Boyce, C. J., Czajkowski, M., Tucker, S. J., NOUSSAIR, C. N., & Townsend, M. (2016) · Environmental and Resource Economics · doi:10.1007/s10640-016-0048-9 · Cited by 46
“This is one of the reasons why some recommend against using p-values for such a purpose (Wasserstein and Lazar 2016).”
The role of day-to-day emotions, sleep, and social interactions in pediatric anxiety treatment
Wallace, M. L., McMakin, D. L., Tan, P. Z., Rosen, D. K., Forbes, E. E., Ladouceur, C. D., Ryan, N. D., Siegle, G. J., Dahl, R. E., Kendall, P. C., et al. (2016) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.12.012 · Cited by 39
“Given the exploratory nature of our work, we followed recommendations by the American Statistical Association and focused on effect sizes (ESs) rather than p-values (Wasserstein & Lazar, 2016).”
MethodMachado, J., Szabo, C. I., Santos, J. P., Amaro, P. M. D. G., Guerra, M., Gumberidze, A., Bian, G., Isac, J.-M., & Indelicato, P. (2018) · Physical Review A · doi:10.1103/physreva.97.032517 · Cited by 39
Rubin, M. (2017) · Review of General Psychology · doi:10.1037/gpr0000135 · Cited by 32
“…which the smaller the p value, the less likely it is that the observed data would occur if the null hypothesis was true (Amrhein, Korner-Nievergelt, & Roth, 2017; Biau, Jolles, & Porcher, 2010; Bradley & Brand, 2016; Falissard, 2012; Haig, 2017; Hubbard & Bayarri, 2003; Wasserstein & Lazar, 2016).”
BackgroundResultUsing State Administrative Data to Identify Social Complexity Risk Factors for Children
Arthur, K. C., Lucenko, B. A., Sharkova, I., Xing, J., & Mangione-Smith, R. (2018) · Annals of Family Medicine · doi:10.1370/afm.2134 · Cited by 37
Sato, K., Iwamoto, T., Matsumura, N., et al. (2018) · Journal of Bone and Joint Surgery · doi:10.2106/jbjs.17.01035 · Cited by 39
Sharma, P. N., Morgeson, F. V., Mithas, S., & Aljazzaf, S. (2018) · Government Information Quarterly · doi:10.1016/j.giq.2018.07.003 · Cited by 51
The case against categorical risk estimates
Scurich, N. (2018) · Behavioral Sciences & the Law · doi:10.1002/bsl.2382 · Cited by 40
Kim, J. H., & Choi, I. (2017) · Econometrics · doi:10.3390/econometrics5030041 · Cited by 38
“This point is in line with the concerns raised by the American Statistical Association (Wasserstein and Lazar 2016), with a statement that “Widespread use of ‘statistical significance’ (generally interpreted as ‘p 0.05’) as a license for making a claim that a scientific finding (or implied truth)…”
InfluentialTree and stand level estimations of Abies alba Mill. aboveground biomass
Jagodziński, A. M., Dyderski, M. K., Gęsikiewicz, K., & Horodecki, P. (2019) · Annals of Forest Science · doi:10.1007/s13595-019-0842-y · Cited by 40
A CS1 Spatial Skills Intervention and the Impact on Introductory Programming Abilities
Bockmon, R., Cooper, S., Koperski, W., Gratch, J. S., Sorby, S., & Dorodchi, M. (2020) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3328778.3366829 · Cited by 39
“used a non-parametric Kruskal-Wallis or a non-parametric oneway analysis of variance test (ANOVA) with associated p-value to determine the significance of the results [52].”
MethodHardness-Aware Deep Metric Learning
Zheng, W., Lu, J., & Zhou, J. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2980231 · Cited by 39
“We then calculated the p-value [52] of each test as shown in Tables 3 and 4.”
MethodYadav, S., Narayanan, J. A., Sinha, N., et al. (2020) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-020-05644-9 · Cited by 39
Bertolini, R., Finch, S. J., & Nehm, R. H. (2021) · Journal of Science Education and Technology · doi:10.1007/s10956-020-09888-8 · Cited by 44
Verswijveren, S. J. J. M., Lamb, K. E., Fernández, J. A. M., WINKLER, E. A. H., Leech, R. M., Timperio, A. F., Salmon, J., Daly, R. M., Cerin, E., Dunstan, D. W., et al. (2021) · Journal of sport and health science/Journal of Sport and Health Science · doi:10.1016/j.jshs.2021.03.004 · Cited by 40
Diabetes as a Prognostic Factor in Frozen Shoulder: A Systematic Review
Dyer, B. P., Burton, C. L., Rathod‐Mistry, T., Bucknall, M., & van der Windt, D. (2021) · Archives of Rehabilitation Research and Clinical Translation · doi:10.1016/j.arrct.2021.100141 · Cited by 39
“A limitation of this approach is that, if interpreted alone, the vote counting of statistically significant associations does not take sample sizes, association sizes, and measures of spread into account.(48,49) We attempted to overcome this issue by using forest plots to visualize association size and direction and”
Fragility indices for only sufficiently likely modifications
Baer, B. R., Gaudino, M. F. L., Charlson, M. E., Fremes, S. E., & Wells, M. T. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2105254118 · Cited by 40
Pitre, T., Kiflen, M., Helmeczi, W., Dionne, J. C., Rewa, O. G., Bagshaw, S. M., Needham-Nethercott, N., Alhazzani, W. A., Zeraatkar, D., & Rochwerg, B. N. (2022) · Critical Care Medicine · doi:10.1097/ccm.0000000000005595 · Cited by 42
“In general, p values are limited in their ability to inform the usefulness of an estimate, a well known but underrecognized component of statistical interpretation (14).”
BackgroundWhen null hypothesis significance testing is unsuitable for research: a reassessmentPreprint
Szűcs, D., & Ioannidis, J. P. A. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/095570 · Cited by 39
Hantula, D. A. (2019) · Perspectives on Behavior Science · doi:10.1007/s40614-019-00194-2 · Cited by 40
Impact of sex hormone-binding globulin on the human phenome
Arathimos, R., Millard, L. A. C., Bell, J. A., Relton, C. L., & Suderman, M. J. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddz269 · Cited by 39
Inclusion of Effect Size Measures and Clinical Relevance in Research Papers
Davis, S., Johnson, A. H., Lynch, T., Gray, L. E., Pryor, E. R., Azuero, A., Soistmann, H. C., Phillips, S. R., & Rice, M. H. (2020) · Nursing Research · doi:10.1097/nnr.0000000000000494 · Cited by 38
“Misuseofp-values led the American Statistical Association to release a statement clarifying the purpose and appropriate use and interpretation of p-values in research (Wasserstein & Lazar, 2016; Wasserstein et al., 2019).”
MethodCSR and firm profitability: Evidence from a meta‐regression analysis
Hirsch, S., Petersen, T., Koppenberg, M., & Hartmann, M. (2022) · Journal of Economic Surveys · doi:10.1111/joes.12523 · Cited by 49
Martel, M., & Glover, S. (2022) · Behavioural Brain Research · doi:10.1016/j.bbr.2022.114125 · Cited by 38
Developing a scale is not enough: on the importance of nomological validity
Köck, F., Berbekova, A., Assaf, A. G., & Josiassen, A. (2024) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-07-2023-1078 · Cited by 39
LFK index does not reliably detect small‐study effects in meta‐analysis: A simulation study
Schwarzer, G., Rücker, G., & Semaca, C. (2024) · Research Synthesis Methods · doi:10.1002/jrsm.1714 · Cited by 41
“30,31 As an alternative, statistical methods to measure the extent of bias or adjust for bias in meta-analysis are available.”
Stang, A., Deckert, M., Poole, C., & Rothman, K. J. (2016) · European Journal of Epidemiology · doi:10.1007/s10654-016-0211-1 · Cited by 36
Ferguson, C. J., & Beresin, E. V. (2017) · Preventive Medicine · doi:10.1016/j.ypmed.2017.02.009 · Cited by 38
Physical activity predicts reduced plasma β amyloid in the Cardiovascular Health Study
Stillman, C. M., López, O. L., Becker, J. T., Kuller, L. H., Mehta, P. D., Tracy, R. P., & Erickson, K. I. (2017) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.397 · Cited by 41
“We report the odds ratios (OR), P-values, and 95% confidence intervals (CI) resulting from these analyses, as modern views of hypothesis testing recommend using a multipronged approach to significance testing in order to decrease the risk of Type I and II errors and represent effects more accurately.(15,16) The result…”
MethodStochasticity in Primary Nucleation: Measuring and Modeling Detection Times
Maggioni, G. M., & Mazzotti, M. (2017) · Crystal Growth & Design · doi:10.1021/acs.cgd.6b01781 · Cited by 41
Conditional equivalence testing: An alternative remedy for publication bias
Campbell, H., & Gustafson, P. (2018) · PLoS ONE · doi:10.1371/journal.pone.0195145 · Cited by 42
“To address this problem, some journal editors have taken radical measures (e.g. Trafimow & Marks (2015)), while the reputation of researchers and the credibility of the science they generate are tarnished (Wasserstein & Lazar, 2016).”
BackgroundLimited dispersal preventsQuercus rubrainvasion in a 14‐species common garden experiment
Jagodziński, A. M., Dyderski, M. K., Horodecki, P., & Rawlik, K. (2017) · Diversity and Distributions · doi:10.1111/ddi.12691 · Cited by 40
“…of significance is an effect of both factors: high variability of dependent variable among tree stands and low number of replications connected with experimental design, and assessment of tree species significance should be based on effect size rather than p - values (Wasserstein & Lazar, 2016).”
BackgroundPerceived strength of forensic scientists’ reporting statements about source conclusions
Thompson, W. C., Grady, R. H., Lai, E. L., & Stern, H. S. (2018) · Law Probability and Risk · doi:10.1093/lpr/mgy012 · Cited by 39
Bruns, S. B., & Stern, D. I. (2018) · Empirical Economics · doi:10.1007/s00181-018-1446-3 · Cited by 39
“1 While misuse and misunderstanding of p -values are widespread (Wasserstein and Lazar 2016), the academic publishing system favors statistically significant results for publication resulting in incentives for individual researchers to search for and select statistically significant results to be…”
BackgroundThe Art of Validating Quantitative Proteomics Data
Handler, D. C. L., Pascovici, D., Mirzaei, M., Gupta, V., Salekdeh, G. H., & Haynes, P. A. (2018) · PROTEOMICS · doi:10.1002/pmic.201800222 · Cited by 36
Carlos-Júnior, L. A., Spencer, M., Neves, D. M., Moulton, T. P., Pires, D. D. O., Castro, C. B., Ventura, C. R. R., Ferreira, C. E. L., SEREJO, C. S., Oigman‐Pszczol, S. S., et al. (2019) · Diversity and Distributions · doi:10.1111/ddi.12896 · Cited by 38
“…in general richness and singularity because this hypothesis was only formulated after observation of the patterns in the data, which increases the chances of finding significance and violates assump‐ tions of most a priori statistical tests, such as ANOVA (Kerr, 1998; Wasserstein & Lazar, 2016).”
BackgroundQuantitative research in tourism and hospitality: an agenda for best-practice recommendations
Assaf, A. G., & Tsionas, E. G. (2019) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-02-2019-0148 · Cited by 43
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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