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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Ery Arias-castro, A. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1603.05947
“uential people in the field via publications and presentations at conferences. Blame it on the P-values? With the bad reputation that P-values are getting and the long-standing controversy around them [10, 11, 16, 17], one may wonder if all this can also be blamed on them. For example, one may wonder if the use of alte…”
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“The American Statistical Association (ASA) in March 2016 released a statement with guidelines for the interpretation of statistical significance and p-values, and their place in sound scientific research practice (Wasserstein & Lazar, 2016).”
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Vsevolozhskaya, O. A., Ruiz, G., & Zaykin, D. V. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.01664
“btain the CDF of the prediction distribution for the replication statistic, T rep, as F p(x) = XB j Pr(2 j jT obt) Z x 0 f(T rep j j;df 1;df 2)dT rep = XB j Pr(2 j jT obt)F(T rep = xj j;df 1;df 2): (9) Then, the Mixture Bayes interval endpoints are derived from the quantiles of this CDF, that are given by F 1 p (x). P…”
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“regarding the importance of statistical significance as this alone can not be used for proving a specific hypothesis or measuring the importance of the result (Wasserstein and Lazar, 2016).”
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A Note on the Connection between Likelihood Inference, Bayes Factors, and P-Values
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“Concern over the use, and misuse, of what is perhaps the most widely taught statistical practice has led the American Statistical Association to craft a statement on behalf of its members [1].”
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Cheng, E., & Mitra, S. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-802459-1.00010-5
Barr, T. L., Gionis, V., & Giersch, R. (2017) · Springer series in translational stroke research · doi:10.1007/978-3-319-45345-3_11
A Reviewer's Guide to an Evaluation of the Scientific Literature
Kavic, M. S. (2017) · Photomedicine and Laser Surgery · doi:10.1089/pho.2016.4232
Data Analysis: a (not so) silent revolution
von Toussaint, U. (2017) · Europhysics news · doi:10.1051/epn/2017101
NEURAL NETWORKS FOR STOCK MARKET OPTION PRICING
Sannikov, S. A. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201701.021-026
Chamber treatment of detail surfaces by unfixed polishing material
Skryabin, V. A. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201701.041-051
Probability that p-value provides misleading evidence cannot be controlled by sample sizePreprint
Grendár, M., & Judge, G. G. (2017) · doi:10.7287/peerj.preprints.2869v1
“The recent ASA statement (Wasserstein & Lazar, 2016) stresses that the p-value ’does not provide a good measure of evidence regarding a model or hypothesis’.”
BackgroundCáceres, A., & González, J. R. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/125450
“Research guidelines from leading journals and the American Statistician Association urge for the need of con(cid:28)rmation studies and accurate statistical reporting (www.nih.gov/about/reporting-preclinical-research.htm) (Wasserstein and Lazar, 2016; Mogil and Macleod, 2017).”
BackgroundFietz, A. V., & Grüner, S. (2017) · Journal of Consumer Protection and Food Safety · doi:10.1007/s00003-017-1108-y
Plausibilität von Modellen und von Hypothesen
Bättig, D. (2017) · Springer eBooks · doi:10.1007/978-3-662-54220-0_15
When More Isn't Better: Visits for Hypertension
Goldberg, E. M., Levy, P. D., & McNaughton, C. D. (2017) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2016.11.008
“Rampant misunderstandings about the meaning of statistical significance and P values prompted a recent statement by the American Statistical Association.18 A P value says nothing about whether the hypothesis being tested was true or not or about the probability that the “true value” is within the 95% confidence interv…”
BackgroundShiryayev, V. D., & Bikmurzina, R. R. (2017) · Mordovia University Bulletin · doi:10.15507/0236-2910.027.201702.239-249
Derecho Y Annlisis Del Comportamiento (Law & Behavioral Analysis)Preprint
Acciarri, H. A. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2949035
A Response to Predictors of Heart Disease Knowledge Among Older and Younger Asian Indian Adults
Sattar, A. (2017) · Journal of Immigrant and Minority Health · doi:10.1007/s10903-017-0614-4
A meta-learning approach for evaluating the effect of software development policies
Stewart, J. A. (2017)
Estimating Rationality in Economics: A History of Statistical Methods in Experimental EconomicsPreprint
Vallois, N., & Jullien, D. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2990987
Trzpiot, G. (2016)
Response to: “Maternal infection can cause spontaneous abortion”
Bérard, A., Muanda, F. T., & Sheehy, O. (2017) · Canadian Medical Association Journal · doi:10.1503/cmaj.733251
Regulation of NKX2-5 in blood vessels
Dritsoula, A. (2017) · UCL Discovery (University College London)
Medical Statistics: For Beginners, 1st ed
Dai, F. (2017) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000002420
Resolução temporal de videogames de ação e seus efeitos em tarefas visuais
Tiraboschi, G. A. (2017) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.59.2017.tde-20062017-181443
Experiences with Using Bayes Factors for Regression Analysis in Biostatistical Setting
Ferenci, T., & Kovács, L. (2017) · Periodica Polytechnica Electrical Engineering and Computer Science · doi:10.3311/ppee.9898
Interruptional Activity and Simulation of Transposable Elements
Jin, L. (2017) · University Library - University of Saskatchewan (University of Saskatchewan)
CORR Insights®: Are Barbed Sutures Associated With 90-day Reoperation Rates After Primary TKA?
Novicoff, W. M. (2017) · Clinical Orthopaedics and Related Research · doi:10.1007/s11999-017-5504-5
Significance is not sufficient
Momoli, F., & Schweitzer, M. E. (2017) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25864
Schiavo, L., Bailly, L., & Iannelli, A. (2017) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2017.09.001
Data Interpretation in Laboratory Medicine
Tormey, C. A., Gehrie, E. A., Pham, H. P., Bucy, R. P., Lorenz, R. G., Zheng, X. L., & Hendrickson, J. E. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-803999-1.00021-3
Stevens, M. (2017) · London School of Economics and Political Science Theses Online (London School of Economics and Political Science) · doi:10.21953/lse.gah9haxnpfy5
Bradley, M. T., & Brand, A. (2017) · The Journal of General Psychology · doi:10.1080/00221309.2017.1381496
“Undoubtedly, NHST and p-values remain hot and contentious topics (Huber, 2016; Wasserstein & Lazar, 2016), and this is reflected in the increase in the use of Bayesianmethods (Andrews & Baguley, 2013).”
BackgroundLista, L. (2017) · Lecture notes in physics · doi:10.1007/978-3-319-62840-0_10
Comments and Suggestions on Defining and Using P-Values and Null Hypothesis Tests
Marshall, D. B., & Lindsay, K. G. (2017) · American Review of Mathematics and Statistics · doi:10.15640/arms.v5n1a1
The science in the p-value: need for a rethinking
Ramanathan, M. (2017) · Indian Journal of Medical Ethics · doi:10.20529/ijme.2017.088
“2012 Apr-Jun; 9(2):76 [cited 2017 Aug 29].”
BackgroundBadenes‐Ribera, L., Navarro, M. D. F., & Campos, A. B. (2017) · International Journal of Developmental and Educational Psychology Revista INFAD de psicología · doi:10.17060/ijodaep.2017.n1.v2.870
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Fietz, A. V., & Grüner, S. (2017) · Agricultural and Food Economics · doi:10.1186/s40100-017-0093-x
“Note that it would be an error to conclude that we found any evidence of no effect (cf. Hirschauer et al. 2016, Wasserstein and Lazar 2016).”
BackgroundStatistical selection of biological models for genome-wide association analyses
Bi, W., Kang, G., & Pounds, S. B. (2017) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2017.8217642
“However, the p-value only measures evidence against the null hypothesis but does not assist investigators in identifying a specific biological model [8].”
Backgroundp-Values for CredibilityPreprint
Held, L. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1712.03032
“…familiar and useful to ditch” David Spiegelhalter (2017) Standard P -values for point null hypotheses still dominate most of the applied literature (Greenland and Poole, 2013), despite the fact that they are commonly misused and misunderstood (Wasserstein and Lazar, 2016; Matthews et al., 2017).”
Background数理社会学ワンステップアップ講座 統計学・計量社会学をどう教えるか：
博史, 神. (2017) · 理論と方法 · doi:10.11218/ojjams.32.177
A gentle reminder about p -values: What are we actually teaching?
Jones, M. A., & de Valpine, M. G. (2018) · Nurse Education Today · doi:10.1016/j.nedt.2018.01.001
Detecting weak signals by combining small P-values in observational studies with multiple testingPreprint
Hu, F., Vsevolozhskaya, O. A., & Zaykin, D. V. (2018) · arXiv (Cornell University)
Michaels, R. A. (2018) · Environmental Claims Journal · doi:10.1080/10406026.2017.1422660
“He has served numerous corporate clients, the U.S. Congressional Office Wasserstein and Lazar (2016): “Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.”
BackgroundInfluentialGoméni, R., Bressolle, F., & D, M. F. M. (2018) · The Journal of Clinical Pharmacology · doi:10.1002/jcph.1074
La investigación biomédica en la encrucijada y vías de salida
Pons, J. M. V., & Adam, P. (2018) · Medicina Clínica · doi:10.1016/j.medcli.2017.12.013
Hirata, T., Noguchi, D., & Araki, H. (2017) · Japanese Journal of Farm Work Research · doi:10.4035/jsfwr.52.133
Reply - Aortic Reservoir Pressure - not overstretching but testing
Cameron, J. D., Parker, K. H., Narayan, O. P., et al. (2018) · Journal of Hypertension · doi:10.1097/hjh.0000000000001685
Method of Relative Magnitudes for Calculating Magnetic Fluxes in Electrical Machine
Zakharzhevskii, O. A. (2018) · Mordovia University Bulletin · doi:10.15507/0236-2910.028.201801.062-076
Exceedance probability for parameter estimatesPreprint
Segal, B. D. (2018) · arXiv (Cornell University)
The p-value Case, a Review of the Debate: Issues and Plausible Remedies
Pauli, F. (2018) · Springer proceedings in mathematics & statistics · doi:10.1007/978-3-319-73906-9_9
Beyond p-values: Utilizing Multiple Estimates to Evaluate EvidencePreprint
Valentine, K. D., Buchanan, E. M., Scofield, J. E., & Beauchamp, M. T. (2017) · doi:10.31219/osf.io/9hp7y
Antibody-based bead arrays for high-throughput protein profiling in human plasma and serum
Drobin, K. (2018) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Einführung in die schließende Statistik
Dreiseitl, S. (2018) · Springer eBooks · doi:10.1007/978-3-662-56733-3_9
Sozu, T., Musashi, Y., & Nakayama, T. (2018) · Japanese Journal of Biometrics · doi:10.5691/jjb.38.141
The ASA Statement and P -values in Epidemiologic Research
Sato, T. (2018) · Japanese Journal of Biometrics · doi:10.5691/jjb.38.109
“答 なぜなら彼らが大学，大学院でそう教わったからである． この悪循環に憂慮した ASA理事会は，その後の活発なディスカッションを受けて，統計を専門と しない研究者，実務家，サイエンスライター向けの声明を公表することとした（Wasserstein and Lazar, 2016）． この声明では，定量的研究の実施とその解釈を改善するための，P 値の適正な使用と解釈に関 する以下にしめす 6つの原則がまとめられている． 1.”
Matsui, S. (2018) · Japanese Journal of Biometrics · doi:10.5691/jjb.38.127
Informal Comments on the ASA 2016 Statement
Miwa, T. (2018) · Japanese Journal of Biometrics · doi:10.5691/jjb.38.163
Management of nicotine induced anorexia with food cravings
Umair, S. M., Javed, S., & Kapoor, D. (2018) · FOOD SCIENCE RESEARCH JOURNAL · doi:10.15740/has/fsrj/9.1/71-78
A Likelihood-based Alternative to Null Hypothesis Significance TestingPreprint
Adams, N., & O’Reilly, G. M. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.02419
“Null hypothesis significance testing (NHST) has become entrenched as the dominant paradigm of research study interpretation despite possessing a number of short-comings.(1,2) These have been extensively documented over many years, but in particular we highlight the following three limitations of NHST.”
BackgroundParametric versus nonparametric: The fitness coefficient
Mazo, G., & Portier, F. (2020) · Scandinavian Journal of Statistics · doi:10.1111/sjos.12495
“(i) their calculation might require computationally intensive strategies as the bootstrap [21, 24,45]; (ii) interpretation is notoriously dicult [29,38] as emphasized again in a recent ASA statement [52]; (iii) whenever some evidence has been found against the model, no information is delivered to improve inference. I…”
MethodAvoiding Bias Due to Nonrandom Scheduling When Modeling Trends in Home-Field AdvantagePreprint
Karl, A. T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.08059
“Appendix: p-hacking Disclosure The American Statistical Association (ASA) statement on p-values (Wasserstein & Lazar 2016) and the associated commentaries call for a reform in the approach and presentation of statistical analyses.”
BackgroundProfessional Football Participation and Mortality
Smith, B. T., & Siddiqi, A. (2018) · JAMA · doi:10.1001/jama.2018.6701
Wu, F., Ye, Y., & Zhou, X. (2018) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2018.06.027
Delahunt, C. B., Maia, P. D., & Kutz, J. N. (2021) · Brain Sciences · doi:10.3390/brainsci11040462
“We avoid the term “significant” in association with P-values, following the arguments in [44].”
MethodBeyond the Bayes Factor, A New Bayesian Paradigm for Handling Hypothesis Testing
Robert, C. P. (2018) · Springer proceedings in mathematics & statistics · doi:10.1007/978-981-13-1223-6_12
Arvanian, V. L., Petrosyan, H. A., Zou, C., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/382341
Chapter 2: Analysis of Variance and hypothesis testing
McIntosh, M. S., Glaz, B., & Yeater, K. M. (2018) · ACSESS publications · doi:10.2134/appliedstatistics.2016.0009
Causality detection in health econometrics using big data
Chakrabarty, S., & Chakraborty, A. (2018)
The Correct Ways to Use Significance Tests
Sakai, T. (2018) · The Kluwer international series on information retrieval · doi:10.1007/978-981-13-1199-4_5
¿Sería conveniente reducir el valor p considerado significativo?
Saladich, I. G. (2018) · Endocrinología Diabetes y Nutrición · doi:10.1016/j.endinu.2018.09.001
Dove sono le evidenze della terapia "basata sulle evidenze"?
Shedler, J. (2018) · PSICOTERAPIA E SCIENZE UMANE · doi:10.3280/pu2018-003003
Vers un nouveau seuil de la valeur de p ?
Laccourreye, O., & Maisonneuve, H. (2018) · Annales françaises d Oto-rhino-laryngologie et de Pathologie Cervico-faciale · doi:10.1016/j.aforl.2018.01.005
The Role of Statistics Education in the Big Data Era
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Objective Bayesian comparison of order-constrained models in contingency tables
Paroli, R., & Consonni, G. (2019) · Test · doi:10.1007/s11749-019-00650-w
“Although the posterior probability of the null model is conceptually quite different from the p-value (Wasserstein and Lazar 2016), one can see that it generally increases with the p-value correctly reporting higher evidence in favor of the null.”
BackgroundRegionally Enhanced Global (REG) 4D-Var
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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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