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
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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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“For example, saying the P-value measures ‘‘the probability that the difference is due to sampling error’’ or ‘‘chance’’ is logically no different than claiming the P-value is the probability of the null hypothesis, which it is emphatically not (Wasserstein and Lazar 2016; Greenland et al. 2016).”
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“For that reason (and several others, Wasserstein and Lazar (2016)) the ubiquitous significance level of 5 % should not be used uncritically.”
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“As highlighted previously by others (Cumming, 2014; Goodman, 2016) and discussed in a statement by the American Statistical Association (Wasserstein & Lazar, 2016), there are various problems surrounding the use of P -values from traditional null hypothesis significance testing.”
Kelter, R. (2020) · BMC Medical Research Methodology · doi:10.1186/s12874-020-00968-2 · Cited by 100
“Countless papers have criticised the misuse and abuse of p-values in particular in medical research, and official statements of the American Statistical Association (ASA) in 2016 and 2019 byWasserstein & Lazar [3] and Wasserstein et al.”
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“…and replicability of scienti fi c conclusions, ” the Board of Directors of the American Statistical Association (ASA) took the unprecedented step in 2016 of issuing a statement warning against the misuse of “ statistical signi fi cance ” and P -values (Wasserstein and Lazar 2016, p. 129).”
BackgroundHow the Maximal Evidence ofP-Values Against Point Null Hypotheses Depends on Sample Size
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“For some recent discussion on the use and misuse of p-values, see the supplementary material of Wasserstein and Lazar (2016).”
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Matthews, R. (2019) · The American Statistician · doi:10.1080/00031305.2018.1543136 · Cited by 84
“…reached a turning-point in March 2016 with the publication of an unprecedented statement by the American Statistical Association (ASA) stating that p-values are “commonly misused and misinterpreted” (Wasserstein and Lazar 2016) and calling for researchers to move toward a “post p 0.05 era.””
BackgroundInfluentialLier, H., Maegele, M., & Shander, A. (2019) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000004389 · Cited by 82
Laccourreye, O., Fakhry, N., Franco‐Vidal, V., Jankowski, R., Karkas, A. A., Leboulanger, N., Makeieff, M., Malard, O., Michel, J., Righini, C. A., et al. (2020) · European Annals of Otorhinolaryngology Head and Neck Diseases · doi:10.1016/j.anorl.2020.06.015 · Cited by 82
Pérez‐Ruixo, C., Rossenu, S., Zannikos, P., Nandy, P., Singh, J. B., Drevets, W. C., & Ruixo, J. J. P. (2020) · Clinical Pharmacokinetics · doi:10.1007/s40262-020-00953-4 · Cited by 91
Process-based greenhouse climate models: Genealogy, current status, and future directions
Katzin, D., Henten, E. J. V., & van Mourik, S. (2022) · Agricultural Systems · doi:10.1016/j.agsy.2022.103388 · Cited by 90
Why and how we should join the shift from significance testing to estimation
Berner, D., & Amrhein, V. (2022) · Journal of Evolutionary Biology · doi:10.1111/jeb.14009 · Cited by 87
“…decision making, p- values are generally no more than crude indicators of how ‘compatible’ a statistical model is with our observed data, given that all assumptions are correct (Amrhein et al., 2019b; Bayarri & Berger, 2000; Greenland, 2019; Rafi & Greenland, 2020; Wasserstein & Lazar, 2016).”
BackgroundResultDevelopmental predictors of offending and persistence in crime: A systematic review of meta-analyses
Basto-Pereira, M., & Farrington, D. P. (2022) · Aggression and Violent Behavior · doi:10.1016/j.avb.2022.101761 · Cited by 109
Overview of leakage scenarios in supervised machine learning
Sasse, L., Nicolaisen‐Sobesky, E., Dukart, J., Eickhoff, S. B., GOETZ, M. A., Hamdan, S., Komeyer, V., Kulkarni, A. J., Lahnakoski, J. M., Love, B. C., et al. (2025) · Journal Of Big Data · doi:10.1186/s40537-025-01193-8 · Cited by 134
“…applied sciences, owing to misunderstanding and –intentional or unintentional– misuse of p -values from null hypothesis significance testing [32, 78], misunderstandings and malpractice in ML can lead to its own replication crisis [25, 36] with severe negative financial and societal…”
BackgroundThe misdirection of public policy: comparing and combining standardised effect sizes
Simpson, A. P. (2017) · Journal of Education Policy · doi:10.1080/02680939.2017.1280183 · Cited by 83
“The NHST process is controversial (Carver 1978; Nickerson 2000) and the American Statistical Association has recently released guidelines to try to ensure that NHST and the associated probability (p-value) are treated appropriately by researchers (Wasserstein and Lazar 2016).”
MethodCharacterization of Evanescent Field Gas Sensor Structures Based on Silicon Photonics
Ranacher, C., Consani, C., Vollert, N., Tortschanoff, A., Bergmeister, M., Grille, T., & Jakoby, B. (2018) · IEEE photonics journal · doi:10.1109/jphot.2018.2866628 · Cited by 85
“The hypothesis test returns the so called p-value [22], which refers to the probability of the effect observed in the given sample under the assumed model and the validity of the null hypothesis.”
BackgroundPervasive Discrimination and Allostatic Load in African American and White Adults
Dyke, M. E. V., Baumhofer, N. K., Slopen, N. B., Mujahid, M. S., Clark, C., Williams, D. R., & Lewis, T. T. (2020) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000788 · Cited by 84
“given our original hypothesis, and emerging consensus across fields for the importance of effect sizes over p-values;(53-55) as well as 2) conceptual arguments for the importance of stratifying by race in order to account for differential confounding of associations of interest within each racial group (56).”
Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction
Choi, Y. S., Ahn, S. S., Chang, J. H., Kang, S., Kim, E. H., Kim, S. H., Jain, R., & Lee, S. (2020) · European Radiology · doi:10.1007/s00330-020-06737-5 · Cited by 79
Selenium and immune function: a systematic review and meta-analysis of experimental human studies
Filippini, T., Fairweather‐Tait, S. J., & Vinceti, M. (2022) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2022.11.007 · Cited by 82
Chen, W., Li, Z., Zhao, Y., Chen, Y., & Huang, R. (2023) · Chinese Medical Journal · doi:10.1097/cm9.0000000000002839 · Cited by 83
“[10,11] The easyGBD package and the R software (R Core Team, version 4.2.1, Vienna, Austria) were used for all statistical studies.”
MethodInfluentialThe impact of sample size on the reproducibility of voxel-based lesion-deficit mappings
Lorca‐Puls, D. L., Gajardo‐Vidal, A., White, J., Seghier, M. L., Leff, A. P., Green, D. W., Crinion, J., Ludersdorfer, P., Hope, T. M. H., Bowman, H., et al. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.03.014 · Cited by 86
“As such, they cannot convey the same information provided by point and interval estimates of effect sizes (Steward, 2016; Wasserstein and Lazar, 2016), particularly since the relationship between p values and effect sizes is non-linear (Hentschke and Stuttgen, 2011; Simonsohn et al.”
BackgroundTime for a change: a tutorial for comparing multiple classifiers through Bayesian analysisPreprint
Benavoli, A., Giorgio Corani, A., Demšar, J., & Marco Zaffalon, A. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.04316 · Cited by 324
“l Psychology, has banned the use of NHSTs and related statistical procedures (Tramow and Marks, 2015). Similarly, the American Statistical Association has recently made a statement against p-values (Wasserstein and Lazar, 2016). We believe that also in machine learning is time to move on from NHST and p-values. In thi…”
BackgroundMethodGlover, S., Bibby, E., & Tuomi, E. (2020) · Experimental Brain Research · doi:10.1007/s00221-020-05756-4 · Cited by 83
Suzuki, H., Yamashiro, D., Ogawa, S., Kobayashi, M., Cho, D., Iizuka, A., Tsukamoto‐Yasui, M., Takada, M., Isokawa, M., Nagao, K., et al. (2020) · Frontiers in Nutrition · doi:10.3389/fnut.2020.586166 · Cited by 81
Sow, M. D., Gac, A. L., Fichot, R., Lanciano, S., Delaunay, A., Jan, I. L., Lesage-Descauses, M.-C., Citerne, S., Caïus, J., Brunaud, V., et al. (2021) · New Phytologist · doi:10.1111/nph.17555 · Cited by 83
“Statistical tests were performed and P -values were calculated according to the methods described by Wasserstein & Lazar (2016).”
MethodKnowledge Spillovers, Entrepreneurial Ecosystems and the Geography of High Growth Firms
Fotopoulos, G. (2022) · Entrepreneurship Theory and Practice · doi:10.1177/10422587221111732 · Cited by 87
Interaction effect: Are you doing the right thing?
Garofalo, S., Giovagnoli, S., Orsoni, M., Starita, F., & Benassi, M. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271668 · Cited by 96
Paton, M., Chan, S., Neto, A. S., Tipping, C. J., Stratton, A., Lane, R., Romero, L., Broadley, T., & Hodgson, C. L. (2024) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(24)00011-0 · Cited by 81
Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond
Wiens, S., & Nilsson, M. E. (2016) · Educational and Psychological Measurement · doi:10.1177/0013164416668950 · Cited by 87
“Null hypothesis significance testing (NHST) has a long tradition in psychology, but there are recurrent concerns about its use (Chavalarias, Wallach, Li, & Ioannidis, 2016; Hunter, 1997; Nuzzo, 2014; Trafimow, 2014; Trafimow & Marks, 2015; Wasserstein & Lazar, 2016).”
BackgroundCargo-cult Statistics and Scientific Crisis
Stark, P. B., & Saltelli, A. (2018) · Significance · doi:10.1111/j.1740-9713.2018.01174.x · Cited by 84
Dasgupta, I., Thomas, G. N., Clarke, J. L., Sitch, A. J., Martín, J., Bieber, B. A., Hecking, M., Karaboyas, A., Pisoni, R. L., Port, F. K., et al. (2019) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.08240718 · Cited by 80
Randomized Controlled Trial for the Effect of Vitamin D Supplementation on Vascular Stiffness in CKD
Levin, A., Tang, M., Perry, T., Zalunardo, N., Beaulieu, M., Dubland, J. A., Zerr, K., & Djurdjev, O. (2017) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.10791016 · Cited by 80
The Biomechanical and Energetic Advantages of a Mediolaterally Wide Pelvis in Women
Wall‐Scheffler, C. M., & Myers, M. J. (2017) · The Anatomical Record · doi:10.1002/ar.23553 · Cited by 79
Religion and health in Europe: cultures, countries, context
VanderWeele, T. J. (2017) · European Journal of Epidemiology · doi:10.1007/s10654-017-0310-7 · Cited by 79
Rowe, S. M., Godden, S., Nydam, D. V., Gorden, P. J., Lago, A., Vasquez, A. K., Royster, E., Timmerman, J. A., & Thomas, M. J. (2020) · Journal of Dairy Science · doi:10.3168/jds.2019-17728 · Cited by 80
Reducing food waste in hotel kitchens based on self-reported data
Leverenz, D., Hafner, G., Moussawel, S., Kranert, M., Goossens, Y., & Schmidt, T. (2020) · Industrial Marketing Management · doi:10.1016/j.indmarman.2020.08.008 · Cited by 81
Radke, E. G., Wright, J. M., Christensen, K., Lin, C. J., Goldstone, A. E., Lemeris, C., & Thayer, K. A. (2022) · Environmental Health Perspectives · doi:10.1289/ehp11185 · Cited by 78
Handling Multiplicity in Neuroimaging Through Bayesian Lenses with Multilevel Modeling
Chen, G., Xiao, Y., Taylor, P. A., Rajendra, J. K., Riggins, T., Geng, F., Redcay, E., & Cox, R. W. (2019) · Neuroinformatics · doi:10.1007/s12021-018-9409-6 · Cited by 79
Payne, M. S., Newnham, J. P., Doherty, D. A., Furfaro, L. L., Pendal, N. L., Loh, D. E., & Keelan, J. A. (2020) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2020.08.034 · Cited by 75
Confidence crisis of results in biomechanics research
Knudson, D. V. (2017) · Sports Biomechanics · doi:10.1080/14763141.2016.1246603 · Cited by 81
“The controversy between null-hypothesis significance testing and magnitude-based statistical inference (Hopkins, Marshall, Batterham, & Hanin, 2009; Wasserstein & Lazar, 2016; Welsh & Knight, 2015) means that uniform standards for statistical analysis can be difficult to determine.”
BackgroundLanier, M., Waddell, T. F., Elson, M., Tamul, D. J., Ivory, J., & Przybylski, A. K. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.06.015 · Cited by 79
“The American Statistical Association has even issued a statement on how p -values should be used, in part, because of their widespread misuse (Wasserstein & Lazar, 2016).”
BackgroundKhadaroo, R. G., Warkentin, L. M., Wagg, A., Padwal, R. S., Clement, F. M., Wang, X., Buie, W. D., & Holroyd-Leduc, J. M. (2020) · JAMA Surgery · doi:10.1001/jamasurg.2019.6021 · Cited by 79
Vladimirov, N., Wang, C., Höckendorf, B., Pujala, A., Tanimoto, M., Mu, Y., Yang, C.-T., Wittenbach, J. D., Freeman, J., Preibisch, S., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0221-x · Cited by 76
A Manager and an AI Walk into a Bar: Does ChatGPT Make Biased Decisions Like We Do?Preprint
Chen, Y., Kirshner, S. N., Ovchinnikov, A. S., et al. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4380365 · Cited by 76
Is Most Published Research Really False?
Leek, J. T., & Jager, L. R. (2016) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-060116-054104 · Cited by 77
Tasks, interaction and role perception of management accountants: evidence from Germany
Rieg, R. (2018) · Journal of Management Control · doi:10.1007/s00187-018-0266-0 · Cited by 78
Chen, Z., Liu, P., Zhang, C., & Feng, T. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz278 · Cited by 80
A method for calculating the fragility index of continuous outcomes
Caldwell, J.-M. E., Youssefzadeh, K. A., & Limpisvasti, O. (2021) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2021.02.023 · Cited by 80
Xiang, K., Xu, Z., Hu, Y., He, Y.-S., Dan, Y., Wu, Q., Fang, X.-H., & Pan, H. (2021) · Chemosphere · doi:10.1016/j.chemosphere.2021.130342 · Cited by 78
Alsaqr, A. M. (2021) · African vision and eye health · doi:10.4102/aveh.v80i1.612 · Cited by 74
A Scoping Review of Artificial Intelligence for Precision Nutrition
Wu, X., Oniani, D., Shao, Z., Arciero, P. J., Sivarajkumar, S., Hilsman, J., Mohr, A. E., Ibe, S., Moharir, M., Li, L.-J., et al. (2025) · Advances in Nutrition · doi:10.1016/j.advnut.2025.100398 · Cited by 89
“The P value ( n ¼ 7) assesses the statistical signi fi - cance of the predictions [118].”
A Call for Openness in Research Reporting: How to Turn Covert Practices Into Helpful Tools
Schwab, A., & Starbuck, W. H. (2016) · Academy of Management Learning and Education · doi:10.5465/amle.2016.0039 · Cited by 80
“Wasserstein and Lazar (2016) reported that George Cobb had challenged a forum in the American Statistical Association with two question-answer pairs: “Question: Why do so many colleges and grad schools teach p = .05?”
BackgroundThe virtuous cycle of human genetics and mouse models in drug discovery
Nadeau, J. H., & Auwerx, J. H. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0009-9 · Cited by 78
How robust are clinical trials in heart failure?
Docherty, K. F., Campbell, R. T., Jhund, P. S., Petrie, M. C., & McMurray, J. J. V. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw427 · Cited by 75
Casals, M., Gangolells, M., Macarulla, M., et al. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.109753 · Cited by 74
“However and as stated by the American Statistical Association [40] , 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.”
BackgroundRole of Glutathione in Buffering Excess Intracellular Copper in Streptococcus pyogenes
Stewart, L. J., Ong, C.-L. Y., Zhang, M. M., Brouwer, S., McIntyre, L., Davies, M. R., Walker, M. J., McEwan, A. G., Waldron, K. J., & Djoko, K. Y. (2020) · mBio · doi:10.1128/mbio.02804-20 · Cited by 72
A Body Shape Index (ABSI), hip index, and risk of cancer in the UK Biobank cohort
Christakoudi, S., Tsilidis, K. K., Εvangelou, Ε., & Ríboli, E. (2021) · Cancer Medicine · doi:10.1002/cam4.4097 · Cited by 72
Lopez, B. T., Rangel, C., & Fernández, M. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.06.025 · Cited by 75
Grünwald, P., de Heide, R., & Koolen, W. M. (2024) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1093/jrsssb/qkae011 · Cited by 240
Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses
Blume, J. D., McGowan, L. D., Dupont, W. D., & Greevy, R. A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0188299 · Cited by 77
Fricker, R. D., Burke, K., Han, X., & Woodall, W. H. (2019) · The American Statistician · doi:10.1080/00031305.2018.1537892 · Cited by 79
“Furthermore, after this review, we also feel it is important to re-emphasize Spiegelhalter’s comments on the ASA Statement on p-Values (Wasserstein and Lazar 2016) in “Too familiar to ditch:” . . .many point out that the problem lies not so much with p-values in themselves as with the willingness…”
BackgroundSeaman, K. L., Smith, C. T., Juarez, E. J., Dang, L. C., Castrellon, J. J., Burgess, L. L., Juan, M. D. S., Kundzicz, P. M., Cowan, R. L., Zald, D. H., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24585 · Cited by 70
“What has been the standard p-value heavy approach has been criticized by statisticians e.g. (Wasserstein & Lazar, 2016).”
MethodAssociation Between Polygenic Risk Score and Risk of Myopia
Mojarrad, N. G., Plotnikov, D., Williams, C., & Guggenheim, J. A. (2019) · JAMA Ophthalmology · doi:10.1001/jamaophthalmol.2019.4421 · Cited by 75
Jet collimation in NGC 315 and other nearby AGN
Boccardi, B., Perucho, M., Casadio, C., et al. (2021) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202039612 · Cited by 73
Güllich, A., Barth, M., Macnamara, B. N., & Hambrick, D. Z. (2023) · Sports Medicine · doi:10.1007/s40279-023-01840-1 · Cited by 75
“05 was not appropriate for the present analyses (see [43, 44]).”
BackgroundDisengaging from statistical significance
Rothman, K. J. (2016) · European Journal of Epidemiology · doi:10.1007/s10654-016-0158-2 · Cited by 74
P Values: From Suggestion to Superstition
Concato, J., & Hartigan, J. A. (2016) · Journal of Investigative Medicine · doi:10.1136/jim-2016-000206 · Cited by 72
Solla, F., Tran, A., Bertoncelli, D., Musoff, C., & Bertoncelli, C. M. (2018) · Clinical Spine Surgery A Spine Publication · doi:10.1097/bsd.0000000000000695 · Cited by 77
Patorno, E., Hernández–Dı́az, S., Huybrechts, K. F., Desai, R. J., Cohen, J. M., Mogun, H., & Bateman, B. T. (2020) · PLoS Medicine · doi:10.1371/journal.pmed.1003322 · Cited by 75
“We focused on estimating magnitude of effects in preference to dichotomizing the results as statistically significant or not [22].”
BackgroundHuybrechts, K. F., Straub, L., Karlsson, P., Pazzagli, L., Furu, K., Gissler, M., Hernández–Dı́az, S., Nørgaard, M., Zoëga, H., Bateman, B. T., et al. (2022) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2022.4109 · Cited by 71
Pazol, K., Robbins, C. L., Black, L. I., Ahrens, K. A., Daniels, K. M., Chandra, A., Vahratian, A. M., & Gavin, L. E. (2017) · MMWR Surveillance Summaries · doi:10.15585/mmwr.ss6620a1 · Cited by 75
“This is typically a conservative approach that might fail to note differences between estimates more often than formal statistical testing (33) and was selected to account for precision of estimates while also highlighting large differences (34).”
BackgroundThe continuing misuse of null hypothesis significance testing in biological anthropology
Smith, R. J. (2018) · American Journal of Physical Anthropology · doi:10.1002/ajpa.23399 · Cited by 76
The Role of Expert Judgment in Statistical Inference and Evidence-Based Decision-Making
Brownstein, N. C., Louis, T. A., O’Hagan, A., & Pendergast, J. (2019) · The American Statistician · doi:10.1080/00031305.2018.1529623 · Cited by 91
Neto, F. G. D. O., Torkar, R., FELDT, R. H., Gren, L., Furia, C. A., & Huang, Z. (2019) · Journal of Systems and Software · doi:10.1016/j.jss.2019.07.002 · Cited by 79
“Several research fields have recently come to realize that the focus on p-values is not beneficial [69, 94, 99, 97].”
BackgroundInfluentialEffect Size Reporting Practices in Applied Linguistics Research: A Study of One Major Journal
Wei, R., Hu, Y., & Xiong, J. (2019) · SAGE Open · doi:10.1177/2158244019850035 · Cited by 71
“One major limitation is that the p value depends upon the sample size; in other words, an increased sample size will eventually yield a small enough p value (viz. p being .05 or smaller; Biskin, 1998; Wasserstein & Lazar, 2016).”
BackgroundImplicit Gender Biases in Professional Software Development: An Empirical Study
Wang, Y., & Redmiles, D. (2019) · IEEE/ACM International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS) · doi:10.1109/icse-seis.2019.00009 · Cited by 79
“We follow the ASA’s principles to present and interpret the statistical significance [38].”
MethodPaggio, J. C. D., & Tannock, I. F. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30338-9 · Cited by 75
Exploring factors influencing technology adoption rate at the macro level: A predictive model
Hooks, D., Davis, Z., Agrawal, V., & Li, Z. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101826 · Cited by 74
Machine Learning and Radiogenomics: Lessons Learned and Future Directions
Kang, J., Rancati, T., Lee, S., Oh, J. H., Kerns, S. L., Scott, J. G., Schwartz, R. S., Kim, S. Y., & Rosenstein, B. S. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00228 · Cited by 74
“In ML, poor correction for multiple testing is related to p-hacking or data dredging, which is to continuously run iterations of this method until it fits a pre-conceived notion or hypothesis (131) (see Lessons From Statistics).”
BackgroundMethodThe Limited Role of Formal Statistical Inference in Scientific Inference
Hubbard, R., Haig, B. D., & Parsa, R. A. (2019) · The American Statistician · doi:10.1080/00031305.2018.1464947 · Cited by 71
“attention to problems associated with statistical significance and p-values (Wasserstein 2016; Wasserstein and Lazar 2016) in the context of science’s “reproducibility crisis” (Peng 2015).”
BackgroundKorologou-Linden, R., Bhatta, L., Brumpton, B. M., Howe, L. D., Millard, L. A. C., Kolaric, K., Ben-Shlomo, Y., Williams, D. M., Smith, G. D., Anderson, E. L., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32183-6 · Cited by 71
Significance test for linear regression: how to test without P-values?
Maneejuk, P., & Yamaka, W. (2020) · Journal of Applied Statistics · doi:10.1080/02664763.2020.1748180 · Cited by 70
A hitchhiker’s guide to working with large, open-source neuroimaging datasets
Horien, C. L., Noble, S., Greene, A. S., Lee, K., Barron, D. S., Gao, S., O’Connor, D. A., Salehi, M., Dadashkarimi, J., Shen, X., et al. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-01005-4 · Cited by 70
Improving Sentiment Analysis of Arabic Tweets by One-way ANOVA
Alassaf, M., & Qamar, A. M. (2020) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2020.10.023 · Cited by 70
Zhu, R., Becerik-Gerber, B., Lin, J., et al. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101827 · Cited by 70
Perceived crisis and reforms: Issues, explanations, and remedies.
de Boeck, P. A. L., & Jeon, M. (2018) · Psychological Bulletin · doi:10.1037/bul0000154 · Cited by 71
P-values, p-values everywhere!
Ganesh, S., & Cave, V. M. (2017) · New Zealand Veterinary Journal · doi:10.1080/00480169.2018.1415604 · Cited by 73
Infanger, D., & Schmidt‐Trucksäss, A. (2019) · Statistics in Medicine · doi:10.1002/sim.8293 · Cited by 73
Refining national greenhouse gas inventories
Yona, L., Cashore, B. W., Jackson, R. B., Ometto, J. P., & Bradford, M. A. (2020) · AMBIO · doi:10.1007/s13280-019-01312-9 · Cited by 78
“Applying such technologies will require careful planning to avoid unintended challenges, such as technocratic environmental solutions, the ethics of environmental monitoring (Bakker and Ritts 2018), or an overemphasis on quantitative values (Wasserstein and Lazar 2016).”
Background
Metadata
- Authors
- Wasserstein, R. L., & Lazar, N. A.
- Affiliations
- American Statistical Association, 732 North Washington Street, Alexandria, VA 22314-1943
- American Statistical Association (US)
- ORCID
- Lazar, Nicole A.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 2016-04-02
- Volume
- 70
- Issue
- 2
- Pages
- 129-133
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2293040502
- Semantic Scholar
- 81a65f23474ffceb2481836328608102950da979
- Cited by
- 6,306
- References
- 45
- Citations by year
- 2026: 625 · 2025: 629 · 2024: 575 · 2023: 543 · 2022: 642 · 2021: 676 · 2020: 678 · 2019: 666 · 2018: 596 · 2017: 438 · 2016: 226
- FWCI
- 649.74
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The American Statistician (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- p-values, statistical evidence, p-value interpretation, statistical inference, hypothesis testing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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