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]
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Engler, J., Zimmermann, H., Lang, D. J., Feller, R. L., & von Wehrden, H. (2019) · Sustainability Science · doi:10.1007/s11625-019-00663-2 · Cited by 5
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Grady, C. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-849905-4.00002-2 · Cited by 3
The Chapman-Richards Distribution and its Relationship to the Generalized Beta
Gove, J. H., Lynch, T. B., & Ducey, M. J. (2019) · Forest Ecosystems · doi:10.1186/s40663-019-0184-0 · Cited by 3
Teo, A., Randall, L. M., Madanitsa, M., Mwapasa, V., Kalilani‐Phiri, L., Khairallah, C., Buffet, C., Karahalios, A., Narum, D. L., ter Kuile, F. O., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-44340-x · Cited by 3
Abu, H. O., & Goldberg, R. J. (2019) · The American Journal of Medicine · doi:10.1016/j.amjmed.2019.05.054 · Cited by 3
Kelley, G. A., Kelley, K. S., & Stauffer, B. L. (2019) · Journal of Investigative Medicine · doi:10.1136/jim-2019-001069 · Cited by 3
Put the blame on the formula: an incredible (but real) tale from the top of modern science
Giuliani, A. (2019) · Organisms. Journal of Biological Sciences · doi:10.13133/2532-5876_5.5 · Cited by 3
“This absurd and irrational behaviour prompted the American Statistical Society to produce a document (Wasserstein and Lazar 2016) restating 80 years old basic statistics concepts to provide six ‘Principles to Improve the Conduct and Interpretation of Quantitative Science’.”
BackgroundThe Process of Patient Engagement in Outpatient Cardiac Rehabilitation Programs
Jahandideh, S., Kendall, E., Low‐Choy, S., Donald, K., Jayasinghe, R., & Barzegari, E. (2019) · Behaviour Change · doi:10.1017/bec.2019.14 · Cited by 3
“We view these values with caution, since a chi-squared test, like all null hypothesis tests, has a high tendency to indicate significance with increasing sample size (J Hair Jr. et al., 2010; Wasserstein & Lazar, 2016).”
BackgroundMethodEndurance training in young athletes: What happens in childhood, stays in childhood?
Guasch, E., & Mont, L. (2019) · European Journal of Preventive Cardiology · doi:10.1177/2047487319871649 · Cited by 3
Studying Primates: How to Design, Conduct and Report Primatological Research
Setchell, J. M. (2019) · Durham Research Online (Durham University) · Cited by 3
Trkulja, V., & Hrabač, P. (2019) · Croatian Medical Journal · doi:10.3325/cmj.2019.60.469 · Cited by 3
The fragility index applied to liver-related trials
Meyer, C. L., Heavener, T. E., & Vassar, M. B. (2019) · Indian Journal of Gastroenterology · doi:10.1007/s12664-019-00996-x · Cited by 3
An atlas of evidence-based phenotypic associations across the mouse phenome
Tanaka, N., & Masuya, H. (2020) · Scientific Reports · doi:10.1038/s41598-020-60891-w · Cited by 3
Detecting test fraud using Bayes factors
Sinharay, S., & Johnson, M. (2020) · Behaviormetrika · doi:10.1007/s41237-020-00113-9 · Cited by 3
How feasible is it to abandon statistical significance? A reflection based on a short survey
Díaz-Quijano, F. A., Calixto, F. M., & da Silva, J. M. N. (2020) · BMC Medical Research Methodology · doi:10.1186/s12874-020-01030-x · Cited by 3
Does more or new data mean that a nonsignificant result will become significant?
Pandis, N. (2020) · American Journal of Orthodontics and Dentofacial Orthopedics · doi:10.1016/j.ajodo.2020.04.015 · Cited by 3
Gerstman, B. B. (2020) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5101 · Cited by 3
Tu, Y., Williams, G. M., de Waterman, A. M. C., Toelle, B. G., Guo, Y., Denison, L. S., Babu, G. R., Yang, B., Dong, G., Jalaludin, B. B., et al. (2020) · Environmental Pollution · doi:10.1016/j.envpol.2020.116330 · Cited by 3
To P or not to P, that is the question: Four expert opinions on the P value controversy
Blackstone, E. H. (2020) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2020.12.091 · Cited by 3
Replicability of studies following a dual‐criterion design
Rosenkranz, G. K. (2021) · Statistics in Medicine · doi:10.1002/sim.9014 · Cited by 3
Bohle, L. F., Valencia, E., Ross, G., Davlyatova, D., Yarbaeva, S. N., Kasymova, Z. A., & Prytherch, H. (2021) · BMC Medical Education · doi:10.1186/s12909-021-02749-x · Cited by 3
“Following expert recommendation on the use of statistical significance [36], we report effect sizes using the eta-square coefficient.”
MethodBoujenah, J. (2021) · Journal of Gynecology Obstetrics and Human Reproduction · doi:10.1016/j.jogoh.2021.102231 · Cited by 3
de Extremadura, U., Molleda, C. B., Mercedes-Acosta, J., Domingo, U. A. D. S., Álvarez-García, D., de Oviedo, U., Almonte-Mata, M., Domingo, U. A. D. S., Rodríguez‐Díaz, F. J., & de Oviedo, U. (2021) · Papeles de Población · doi:10.22185/24487147.2021.108.18 · Cited by 3
Moving to a world beyond p-value < 0.05: a guide for business researchers
Kim, J. H. (2021) · Reviews of Management Sciences · doi:10.1007/s11846-021-00504-6 · Cited by 4
“The American Statistical Association (ASA) has recently issued two statements on the “p-value 0.05” criterion for statistical significance widely used in many fields of science: see Wasserstein and Lazar (2016) and Wasserstein et al.”
BackgroundInfluentialKruger, C., Schutte, W. D., & Verster, T. (2021) · Risks · doi:10.3390/risks9110204 · Cited by 3
B‐value and empirical equivalence bound: A new procedure of hypothesis testing
Zhao, Y., Caffo, B. S., & Ewen, J. B. (2022) · Statistics in Medicine · doi:10.1002/sim.9298 · Cited by 3
“In 2016, the American Statistical Association announced a policy statement on P -values (Wasserstein and Lazar, 2016).”
BackgroundInvestigating Large-Scale Network with Unified Granger Causality Analysis
Hu, Z., Li, F., Cheng, M., & Lin, Q. (2022) · Computational and Mathematical Methods in Medicine · doi:10.1155/2022/6962359 · Cited by 3
Computing the fragility index for randomized trials and meta-analyses using Stata
Linden, A. (2022) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x221083856 · Cited by 3
de Koning, J. J., & Noordhof, D. A. (2019) · International Journal of Sports Physiology and Performance · doi:10.1123/ijspp.2019-0419 · Cited by 3
Statistical Analysis Methods Applied to Early Outpatient COVID-19 Treatment Case Series Data
Gkioulekas, E., McCullough, P. A., & Zelenko, V. (2022) · COVID · doi:10.3390/covid2080084 · Cited by 2
The soft tyranny of p‐values in quantitative research: New considerations for leadership researchers
Soria, K. M. (2022) · New Directions for Student Leadership · doi:10.1002/yd.20521 · Cited by 3
Getting to grips with open science
Bartlett, J. E., & Eaves, J. (2018) · PsyPag Quarterly · doi:10.53841/bpspag.2019.1.109-5.85 · Cited by 3
Statistical points and pitfalls
Leppink, J., O’Sullivan, P., & Winston, K. (2016) · Perspectives on Medical Education · doi:10.1007/s40037-015-0246-0 · Cited by 3
The Effects of Dr. Oz on Health Behaviors and Attitudes
Crouch, E. L., Dickes, L., Davis, A., et al. (2016) · American Journal of Health Education · doi:10.1080/19325037.2016.1219283 · Cited by 3
“05 is an arbitrary threshold and scientific conclusions should not be based only on whether a P value passes this threshold.(24) Table 1.”
BackgroundNguyen, S. P., Pham, U. H., Nguyen, T. D., et al. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-49046-5_45 · Cited by 3
The probability of probability and research truths
Fatovich, D. M., & Phillips, M. R. (2017) · Emergency Medicine Australasia · doi:10.1111/1742-6723.12740 · Cited by 3
“In 2016, the American Statistical Association published a statement on Pvalues that reiterate these concerns, including that a P-value, or statistical significance, does not measure the size of an effect or the importance of a result; a P-value by itself does not provide a good measure of evidence regarding a model or…”
BackgroundMagnitud del tamaño del efecto y su importancia en la investigación pediátrica.
Caycho‐Rodríguez, T. (2017) · Acta Pediátrica de México · doi:10.18233/apm38no2pp134-1361366 · Cited by 3
PROBLEMS OF INFORMAT ION SECURITY: INTERNET OF THINGS
Shikov, S. A. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201701.027-040 · Cited by 3
Piegorsch, W. W. (2017) · Biometrical Journal · doi:10.1002/bimj.201700031 · Cited by 3
Guo, Q., & Ganapathysubramanian, B. (2017) · Wind Energy · doi:10.1002/we.2108 · Cited by 3
Buying a significant result: Do we need to reconsider the role of the P value?
Jiroutek, M. R., & Turner, J. R. (2017) · Journal of Clinical Hypertension · doi:10.1111/jch.13021 · Cited by 3
Results of the study of damage to small seeds from the disk sowing apparatus
Ovchinnikov, V. A. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201702.190-197 · Cited by 3
Барашков, Н. А., & ПИСАРЕНКО, П. (2016) · Grain Products and Mixed Fodder’s · doi:10.15673/gpmf.v63i3.219 · Cited by 3
Statistics for Use in Discrimination Testing
Castura, J. C., & Franczak, B. C. (2017) · Elsevier eBooks · doi:10.1016/b978-0-08-101009-9.00002-2 · Cited by 3
The Perception of Emotion in the Singing Voice
Parada‐Cabaleiro, E., Baird, A., Batliner, A. M., et al. (2017) · doi:10.1145/3144749.3144756 · Cited by 3
Experimental Planning and Execution
Mullane, K., Curtis, M. J., & Williams, M. J. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-804725-5.00002-1 · Cited by 3
Blockeel, H. (2017) · International Journal of Data Science and Analytics · doi:10.1007/s41060-017-0081-y · Cited by 3
“In fact, warnings have been issued for over half a century [6,13], and yet scientists keep having to repeat them [18,24].”
BackgroundInhibitory Effect of Sulforaphane on Secretory Group IIA Phospholipase A2
Lee, Y., Lee, W., Kim, J., et al. (2018) · International Journal of Pharmacology · doi:10.3923/ijp.2018.187.193 · Cited by 3
Rescuing Suboptimal Patient-Reported Outcome Instrument Data in Clinical Trials: A New Strategy
Yang, C., & Vrana, K. E. (2018) · Healthcare · doi:10.3390/healthcare6010027 · Cited by 3
“, [21]), including the American Statistical Association (ASA) statement on p-values [22].”
BackgroundPractical Issues on Energy-Growth Nexus Data and Variable Selection With Bayesian Analysis
Tiwari, A. K., Forte, A., García‐Donato, G., & Menegaki, A. N. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812746-9.00006-7 · Cited by 4
A Statistical Model to Investigate the Reproducibility Rate Based on Replication Experiments
Pauli, F. (2018) · International Statistical Review · doi:10.1111/insr.12273 · Cited by 3
Ants on Clerodendrum infortunatum: Disentangling Effects of Larceny and Herbivory
Mukhopadhyay, A., & Quader, S. (2018) · Environmental Entomology · doi:10.1093/ee/nvy090 · Cited by 3
Caldwell, A. C. (2018) · Annalen der Physik · doi:10.1002/andp.201700457 · Cited by 5
Lowering the P Value Threshold
Barach, P. R., Thomas, R., & Lipshultz, S. E. (2018) · JAMA · doi:10.1001/jama.2018.8717 · Cited by 3
Want to make Behavioural Research more Replicable? Promote Single Paper Meta-Analysis
McShane, B. B., & Böckenholt, U. (2018) · Significance · doi:10.1111/j.1740-9713.2018.01214.x · Cited by 3
A Survey About Dental Instruments at the Primary Health Care in Brazil
Lopes, J., Palmier, A. C., Werneck, M. A. F., Machado, A. T. G. D. M., & de Abreu, M. H. N. G. (2018) · Brazilian Dental Journal · doi:10.1590/0103-6440201801969 · Cited by 3
“The decision to not perform statistical tests and hence to not show p values was also due to the number of evaluated OHTs, which could lead to the identification of statistical associations even where there were no relevant differences between groups (13).”
BackgroundPotential Unintended Effects of Medicare’s Bundled Payments for Care Improvement Program
Bilinski, A., & Hatfield, L. A. (2019) · JAMA · doi:10.1001/jama.2018.18158 · Cited by 3
Davies, L. (2017) · Statistica Sinica · doi:10.5705/ss.202016.0507 · Cited by 3
Beyond statistical significance
Chander, N. (2019) · The Journal of Indian Prosthodontic Society · doi:10.4103/jips.jips_207_19 · Cited by 3
Usami, S. (2019) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12181 · Cited by 3
Lee, J., Kubik, M., & Fulkerson, J. A. (2019) · The Journal of School Nursing · doi:10.1177/1059840519875506 · Cited by 3
“Bivariate analyses were used to inform the selection of independent variables to include in the regression model using a less conservative p .1 criterion given the small sample size and exploratory design of the study (Wasserstein & Lazar, 2016).”
MethodThompson, W., Garry, A., Taylor, J. R., & Radell, M. L. (2020) · Psychology Learning & Teaching · doi:10.1177/1475725719877590 · Cited by 4
“For supplemental readings, we recommend articles such as Goodman (1999b), Wasserstein and Lazar (2016), and Ly et al. (2018).”
BackgroundMethodWhere Will Statistical Sciences for Clinical Pharmacology Be in 2030?
Smith, B. P. (2019) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1635 · Cited by 3
“I cannot leave the discussion of P values without acknowledging that the American Statistical Association has recently written position papers on both P values and statistical significance.(5,6) You will see if you read these and the corresponding commentaries that there are many opinions.”
BackgroundStatistical significance in the era of big data
Szreder, M. (2019) · Wiadomości Statystyczne The Polish Statistician · doi:10.5604/01.3001.0013.7583 · Cited by 3
Ruiz, M. J., Dojat, M., & Hupé, J. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14774 · Cited by 3
“Our study thus further shows that common statistical practices based on Null Hypothesis Significance Tests (NHST) are not adequate for scientific inference (Hupé & Dojat, 2015; Wasserstein & Lazar, 2016; Hupé, 2017).”
BackgroundJang, K., & 백영민 (2016) · Korean Journal of Journalism & Communication Studies · doi:10.20879/kjjcs.2016.60.3.002 · Cited by 3
Milani, L., Valtolina, G. G., & Boerchi, D. (2020) · RICERCHE DI PSICOLOGIA · doi:10.3280/rip2020-001009 · Cited by 3
Bickel, D. R. (2023) · Sankhya A · doi:10.1007/s13171-023-00328-4 · Cited by 3
“As seen in Wasserstein and Lazar (2016) and Wasserstein et al. (2019), failed attempts to replicate the results of scientific studies are often attributed to misinterpretations of the p -value.”
Cómo mejorar la comunicación de estadísticos inferenciales en ciencias de la salud
García, A. M. R., & Puga, J. L. (2020) · REVISTA ESPAÑOLA DE COMUNICACIÓN EN SALUD · doi:10.20318/recs.2020.5173 · Cited by 5
Djulbegović, B., Razavi, M., & Hozo, I. (2020) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.13497 · Cited by 3
Seasonal and daily activity patterns of mammals in the colony of great cormorants
Jasiulionis, M., & Balčiauskas, L. (2021) · Mammalia · doi:10.1515/mammalia-2020-0042 · Cited by 3
Sorigué, M., & Kuittinen, O. M. (2021) · Expert Review of Hematology · doi:10.1080/17474086.2021.1943351 · Cited by 4
“However, we would still like to note that p values are overemphasized and often misinterpreted [119].”
BackgroundLajoie, J. L., Ganio, L. M., & Rivers, J. W. (2021) · Journal of Avian Biology · doi:10.1111/jav.02782 · Cited by 3
Unpacking the T: Understanding the Diverse Experiences Trans Students Navigating Schools
Leonardi, B., Farley, A. N., Drager, E. H., & Gonzales, J. S. (2021) · Berkeley Review of Education · doi:10.5070/b810245267 · Cited by 5
Gopal, B., & Cooper, S. (2021) · 2022 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie49875.2021.9637353 · Cited by 3
Conceptual and Theoretical Specifications forAccuracy in Medicine
Montévil, M. (2022) · Human perspectives in health sciences and technology · doi:10.1007/978-3-030-74804-3_3 · Cited by 3
Palinkas, C. M., Koontz, E. L., & Fisher, T. R. (2022) · Estuaries and Coasts · doi:10.1007/s12237-022-01077-7 · Cited by 3
“P values are reported for all tests, although p values do not measure the importance of results (Wasserstein and Lazar 2016), and management decisions should not be based solely on them (Smith 2020).”
BackgroundAfrican American Unemployment and the Disparity in Periviable Births
Catalano, R. A., Karasek, D. A., Bruckner, T. A., Casey, J. A., Saxton, K. B., Ncube, C. N., Shaw, G. M., Elser, H. C., & Gemmill, A. (2021) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-021-01022-7 · Cited by 3
Fneish, F., Ellenberger, D., Frahm, N., Stahmann, A., Fortwengel, G., & Schaarschmidt, F. (2023) · Therapeutic Innovation & Regulatory Science · doi:10.1007/s43441-023-00550-0 · Cited by 3
“For a thorough data interpretation, merely relying on rejection/non-rejection at one significance at level, say 0.05, or merely relying on the presented p -values is discouraged (e.g. ASA statement on p -values, Wasserstein and Lazar 2016) [23].”
Influential
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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