The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index; none of the 1 sources its claims cite is checked for support yet.
The ASA Statement on p -Values: Context, Process, and Purpose
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24 Own interpretation · 2 No basis given · 1 No full text of the sources
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The widespread use of”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Statistical significance is not equivalent to scientific, human, or economic significance.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, a p-value near 0.05 taken by itself offers only weak evidence against the null hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, identical estimated effects will have different p-values if the precision of the estimates differs.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A p-value provides one approach to summarizing the incompatibility between a particular set of data and a proposed model for the data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Conducting multiple analyses of the data and reporting only those with certain p-values (typically those passing a significance threshold) renders the reported p-values essentially uninterpretable.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Whenever a researcher chooses what to present based on statistical results, valid interpretation of those results is severely compromised if the reader is not informed of the choice and its basis.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The smaller the p-value, the greater the statistical incompatibility of the data with the null hypothesis, if the underlying assumptions used to calculate the p-value hold.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Valid scientific conclusions based on p-values and related statistics cannot be drawn without at least knowing how many and which analyses were conducted, and how those analyses (including p-values) were selected for reporting.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 10
- It may state two separate claims as one. 10
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This has led to some scientific journals discouraging the use of p-values, and some scientists and statisticians recommending their abandonment, with some arguments essentially unchanged since p-values were first introduced.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The statistical community has been deeply concerned about issues of reproducibility and replicability of scientific conclusions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While the p-value can be a useful statistical measure, it is commonly misused and misinterpreted.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A conclusion does not immediately become”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All these measures and approaches rely on further assumptions, but they may more directly address the size of an effect (and its associated uncertainty) or whether the hypothesis is correct.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The validity of scientific conclusions, including their reproducibility, depends on more than the statistical methods themselves.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is a statement about data in relation to a specified hypothetical explanation, and is not a statement about the explanation itself.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Researchers should recognize that a p-value without context or other evidence provides limited information.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Likewise, a relatively large p-value does not imply evidence in favor of the null hypothesis; many other hypotheses may be equally or more consistent with the observed data.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This incompatibility can be interpreted as casting doubt on or providing evidence against the null hypothesis or the underlying assumptions.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. P-values can indicate how incompatible the data are with a specified statistical model.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Appropriately chosen techniques, properly conducted analyses and correct interpretation of statistical results also play a key role in ensuring that conclusions are sound and that uncertainty surrounding them is represented properly.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 1. Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Misunderstanding or misuse of statistical inference is only one cause of the”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > Abstract
What the sources say
- Not checked — no full text of the sourcecites Peng 2015 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Smaller p-values do not necessarily imply the presence of larger or more important effects, and larger p-values do not imply a lack of importance or even lack of effect.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In view of the prevalent misuses of and misconceptions concerning p-values, some statisticians prefer to supplement or even replace p-values with other approaches.”
§ The ASA's Statement on p-Values: Context, Process, and Purpose In > 4. Other Approaches
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
There is widespread consensus in the statistical community on the principles articulated in the ASA statement.
“according to widespread consensus in the statistical community”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While the large scale of the Tabula Muris Senis dataset provides substantial power to predict subtle changes in LR interactions, the biological complexity, dependencies among communication pairs, and multiple testing burden require that these p-values be interpreted within a broader biological and statistical context [33].”
From Quantitative profiling of lifespan-dependent cell-cell communication potential reveals dynamic ligand-receptor network shifts across mouse tissues (2026) · cites this paper as [33]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These types of incorrect descriptions contribute to confirmation bias, overinterpretation of results, and reporting correlation as implied causation (Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“This is especially true of relatively large-sample-size studies (as most learning analytics studies are), which are likely to obtain statistically significant findings in relatively small variations in measures such as GPA (Field 2017; Salkind 2016 Wasserstein and Lazar 2016).”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Wasserstein and Lazar 2016
In the citing paper
“In 2016, the American Statistical Association released a statement on statistical significance and the P value with six principles underlying the proper use and interpretation of this statistical tool (77).”
From Misrepresentation and distortion of research in biomedical literature (2018) · cites this paper as [77]
In the citing paper
“Although we also present p values for exploratory analyses, we refrain from labeling any of them as statistically significant, following best-practice recommendations for statistical analysis [43].”
From Comparing quality of reporting between preprints and peer-reviewed articles in the biomedical literature (2020) · cites this paper as [43]
In the citing paper
“Contrary to IJE author recommendations and recent guidance from the American Statistics Society, 16 Gao et al. largely base their conclusions on findings with a P -value equivalent to < 0.05 after multiple testing.”
From Commentary: Two-sample Mendelian randomization: opportunities and challenges (2016) · cites this paper as [16]
In the citing paper
“Following guidance,50 we focused on 95% CIs, rather than statistical significance. For example, unlike conventional interpretations, we did not outright interpret an effect estimate “non‐significant” if the lower or upper bound of the 95% CI was slightly above/below the null value; we interpreted them as “suggestive” of an effect.”
From Third‐wave cognitive behaviour therapies for weight management: A systematic review and network meta‐analysis (2020) · cites this paper as [50]
Citations
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“…are performed on the data, but only the ones with a p-value below a certain threshold are reported, both validity and replicability of the finding might be compromised, contributing to a spurious excess of statistically significant results in the published literature (Wasserstein & Lazar, 2016).”
MethodResultLekan, D. A., McCoy, T. P., Jenkins, M., Mohanty, S. D., Manda, P., & Yasin, R. (2021) · Research in Gerontological Nursing · doi:10.3928/19404921-20210115-03 · Cited by 11
“A two-sided p value 0.05 was con- sidered statistically signifi cant and is reported along with eff ect size (AOR) and its precision (95% CI) (Wasserstein & Lazar, 2016).”
MethodInfluentialBayesian interpretation of p values in clinical trials
Ferguson, J. P. (2021) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2020-111603 · Cited by 11
Assessment and significance of the frequency domain for trends in annual peak streamflow
Konrad, C. P., & Restivo, D. (2021) · Journal of Flood Risk Management · doi:10.1111/jfr3.12761 · Cited by 10
“Using less significant tests for trends requires an ideological shift tolerating less certainty about nonstationarity but also demanding more evidence of stationarity (Wasserstein & Lazar, 2016).”
BackgroundMicheni, L. N., Kassaza, K., Kinyi, H. W., Ntulume, I., & Bazira, J. (2022) · Scientific Reports · doi:10.1038/s41598-022-05591-3 · Cited by 11
Pak, C., Cotter, K., & Thorson, K. (2022) · Communication Methods and Measures · doi:10.1080/19312458.2022.2037537 · Cited by 10
“This is due to recent discussion that articulated the danger of the widely adopted research practice of focusing too narrowly on p-values (Wasserstein & Lazer, 2016) and the growing opportunities for measuring effect sizes that are directly valid to the real world due to the advancements of…”
BackgroundSjöholm, H., Hägg, S., Nyberg, L., et al. (2022) · SAGE Open Medicine · doi:10.1177/20503121221088093 · Cited by 10
Application of Bayesian Methods to Help Interpret the VANCO Trial Results
O’Hara, N. N., Castillo, R. C., Carlini, A. R., Joshi, M. G., Murray, C. K., Allen, L., Huang, Y., Gary, J. L., Bosse, M. J., Obremskey, W. T., et al. (2022) · Journal of Orthopaedic Trauma · doi:10.1097/bot.0000000000002458 · Cited by 11
Waite, M. R., Heslin, K., Cook, J. A., et al. (2023) · Journal of Substance Use and Addiction Treatment · doi:10.1016/j.josat.2022.208933 · Cited by 10
Miyamura, K., Nawa, N., Isumi, A., Doi, S. K., Ochi, M., & Fujiwara, T. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1051592 · Cited by 11
Bonamente, M. (2023) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stad463 · Cited by 10
“Hypothesis testing is a process whose outcome is that of either discarding a null hypothesis at a given level of significance, or merely failing to discard it (see, e.g., the recent statemente by the American Statistical Association on 𝑝 values and hypothesis testing, Wasserstein & Lazar 2016).”
BackgroundColwell, R. K., Rangel, T. F., Fučíková, K., Sustaita, D., Yanega, G. M., & Rico‐Guevara, A. (2023) · The American Naturalist · doi:10.1086/726036 · Cited by 13
Early versus late contact with the youth justice system: opportunities for prevention and diversion
Malvaso, C., Magann, M., Santiago, P. H. R., Montgomerie, A., Delfabbro, P., Day, A., Pilkington, R. M., & Lynch, J. W. (2023) · Current Issues in Criminal Justice · doi:10.1080/10345329.2023.2214973 · Cited by 9
“This is consistent with recommendations from the American Statistical Association (Wasserstain & Lazar, 2016). p -values and con fi dence intervals are highly dependent on sample size, so interpretation of the magnitude of di ff erences should be based on substantive judgement of the magnitude, not ‘…”
MethodGonzález‐Del‐Hoyo, M., Mas-Lladó, C., Siquier-Padilla, J., Peña, L. B., Coughlan, J. J., Peral, V., & Rosselló, X. (2023) · European Heart Journal - Quality of Care and Clinical Outcomes · doi:10.1093/ehjqcco/qcad034 · Cited by 10
Understanding the true significance of a P value
Althouse, A. D., & Soman, P. (2016) · Journal of Nuclear Cardiology · doi:10.1007/s12350-016-0605-1 · Cited by 10
“The American Statistical Association recently released a statement addressing the widespread abuse and misunderstanding of P values.(2) The purpose of this communication is to relay the sentiments in the ASA statement while simultaneously providing some specific context for cardiovascular researchers.”
BackgroundInterpretation of logistic regression and propensity score analysis
Obayashi, H. (2016) · Tenri Medical Bulletin · doi:10.12936/tenrikiyo.19-008 · Cited by 11
Berk, M., Kroll, H.-M., Schubert, O., Buschardt, B., & Straub, D. (2017) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2017-01-0050 · Cited by 12
“The American Statistical Association (ASA) recently issued a warning about pvalues of NHST due to their misuse and misinterpretation [20]: “Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.”
BackgroundKrausman, P. R. (2017) · Journal of Wildlife Management · doi:10.1002/jwmg.21253 · Cited by 10
An objective Bayes perspective on p‐values
Held, L. (2017) · Biometrical Journal · doi:10.1002/bimj.201700068 · Cited by 10
“However, the vast majority of medical research is still based on dichotomizing p-values at 0.05, which was the main trigger to develop the ASA’s Statement on p-values (Wasserstein and Lazar, 2016).”
BackgroundInfluentialHájíčková, M., Plichta, R., Volařík, D., et al. (2017) · New Forests · doi:10.1007/s11056-017-9596-2 · Cited by 10
Uses and Misuses of the P Value in Reporting Results of Orthopaedic Research Studies
Katz, J. N., & Elena, L. (2017) · Journal of Bone and Joint Surgery · doi:10.2106/jbjs.17.00318 · Cited by 10
Big-Data-Ansätze in der Psychiatrie: Beispiele aus der Depressionsforschung
Bzdok, D., Karrer, T. M., Habel, U., & Schneider, F. W. (2017) · Der Nervenarzt · doi:10.1007/s00115-017-0456-2 · Cited by 11
Computational identification of harmful mutation regions to the activity of transposable elements
Jin, L., McQuillan, I., & Li, L. (2017) · BMC Genomics · doi:10.1186/s12864-017-4227-z · Cited by 10
“This is a measure of significance in terms of the false positive rate [25].”
BackgroundNull Hypotheses, Interval Estimation, and Bayesian Analysis
Shin, J. J., & Zurakowski, D. (2017) · Otolaryngology · doi:10.1177/0194599817728898 · Cited by 11
“Null hypothesis testing is a broadly accepted technique that is most acceptable when the true meaning of the standard P value is delineated and its limitations understood.(2) The Bayesian approach is well known in the context of diagnostic testing and is often the expected method of assessment in related studies.”
BackgroundMethodMertens, U. K., Voß, A., & Radev, S. T. (2018) · PLoS ONE · doi:10.1371/journal.pone.0193981 · Cited by 10
“Furthermore, the p -value is often misinterpreted (e.g. as the probability of the null hypthesis being true) [8].”
BackgroundThe role of Statistics in the era of big data: Crucial, critical and under-valued
Scott, E. M. (2018) · Statistics & Probability Letters · doi:10.1016/j.spl.2018.02.050 · Cited by 10
Epipaleolithic human appendicular remains from Ein Gev I, Israel
Trinkaus, E. (2018) · Comptes Rendus Palevol · doi:10.1016/j.crpv.2018.03.002 · Cited by 10
Lin, J., Lin, X., Hu, C., et al. (2018) · Laser Physics Letters · doi:10.1088/1612-202x/aad127 · Cited by 10
The selection of directional sectors for the analysis of extreme wind speed
Folgueras, P., Solari, S., & Losada, M. Á. (2019) · Natural hazards and earth system sciences · doi:10.5194/nhess-19-221-2019 · Cited by 10
On the Apparently Inappropriate Use of Multiple Hypothesis Testing in Earthquake Prediction Studies
Kato, M. (2019) · Seismological Research Letters · doi:10.1785/0220180378 · Cited by 10
P -Value Worship: Is the Idol Significant?
Dettori, J. R., Norvell, D. C., & Chapman, J. R. (2019) · Global Spine Journal · doi:10.1177/2192568219838538 · Cited by 10
The costs and benefits of decentralization and centralization of ant colonies
Burns, D. D. R., Pitchford, J. W., Parr, C. L., et al. (2019) · Behavioral Ecology · doi:10.1093/beheco/arz138 · Cited by 10
Chow, S., & Huang, Z. (2019) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2019.1657137 · Cited by 10
“It can be verified that underH0, P follows the uniform distribution between 0 and 1 (Wasserstein and Lazar 2016).”
BackgroundGarcés, C., Niklitschek, E. J., Plaza, G., et al. (2019) · Fisheries Oceanography · doi:10.1111/fog.12455 · Cited by 10
Bickel, D. R. (2020) · The American Statistician · doi:10.1080/00031305.2020.1816214 · Cited by 10
“The American Statistical Association’s call to emphasize effect size estimation (Wasserstein and Lazar, 2016) does not necessarily warrant reporting conventional effect size estimates without modification (van den Bergh et al., 2019).”
BackgroundMethodStatistical Accuracy in Rheumatology Research
Benlidayı, İ. C. (2019) · Mediterranean Journal of Rheumatology · doi:10.31138/mjr.30.4.207 · Cited by 10
Social Inequalities in Student Employment and the Local Labour Market
Jacob, M., Gerth, M., & Weiss, F. (2020) · KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie · doi:10.1007/s11577-020-00661-8 · Cited by 10
Ten Common Statistical Errors from All Phases of Research, and Their Fixes
Borg, D. N., Lohse, K. R., & Sainani, K. L. (2020) · PM&R · doi:10.1002/pmrj.12395 · Cited by 10
Methodological Challenges in Social Science: Making Sense of Polarized and Competing Research Claims
Robb, A. (2020) · Family Court Review · doi:10.1111/fcre.12474 · Cited by 10
Goldman, M., & Rodriguez, N. (2020) · Race and Justice · doi:10.1177/2153368720924769 · Cited by 10
PL-search: a profile-link-based search method for protein remote homology detection
Jin, X., Liao, Q., & Liu, B. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa051 · Cited by 10
Sahoo, S., Derwin, K. A., Zajichek, A., et al. (2020) · Journal of Shoulder and Elbow Surgery · doi:10.1016/j.jse.2020.08.003 · Cited by 10
Nishiki, S., Arima, Y., Yamagishi, T., Hamada, T., Takahashi, T., Sunagawa, T., Matsui, T., Oishi, K., & Ohnishi, M. (2020) · International Journal of STD & AIDS · doi:10.1177/0956462420945928 · Cited by 10
Cen, Y., Zhang, C., Cen, G., Zhang, Y., & Zhao, C. (2020) · Information · doi:10.3390/info11110495 · Cited by 11
“Therefore, Pearson correlation coefficient analysis [15] was adopted to observe the correlation between different features, and the p-value [16] was used to measure the related level.”
MethodRosasco, J., Hanson, Z., Kramer, J., Steele, L., Beachy, B. R., Gothard, M. D., Ahmed, R. A., & McCarroll, M. L. (2020) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2020.0245 · Cited by 10
Towards a New Paradigm for Statistical Evidence in the Use of p-Value
Bhatti, M. I., & Kim, J. H. (2020) · Econometrics · doi:10.3390/econometrics9010002 · Cited by 12
“As an example, we quote a statement made by the American Statistical Association (Wasserstein and Lazar 2016) and the presidential address given by the American Finance Association (Harvey 2017).”
MethodHill’s Temporality Criterion: Reverse Causation and Its Radiation Aspect
Koterov, A. N., Ushenkova, L. N., & Biryukov, A. P. (2020) · Biology Bulletin · doi:10.1134/s1062359020120031 · Cited by 10
Turner, A. N., Parmar, N., Jovanovski, A., & Hearne, G. (2021) · Strength and conditioning journal · doi:10.1519/ssc.0000000000000625 · Cited by 10
“This seems to be an area of interest given the confusion in the best method to do this, from the implementation of p-values (11,22) to reporting effect sizes, confidence intervals (4,5), and the utility of analyses incorporating concepts such as the smallest worthwhile change (12) and minimal difference (24).”
BackgroundMethodInfluentialKluxen, F. M., & Jensen, S. M. (2021) · Regulatory Toxicology and Pharmacology · doi:10.1016/j.yrtph.2021.104871 · Cited by 10
Real-world treatment sequencing and healthcare costs among CLL/SLL patients treated with venetoclax
Rogers, K. A., Émond, B., Manceur, A. M., Kinkead, F., Lafeuille, M., Lefèbvre, P., & Huang, Q. (2021) · Current Medical Research and Opinion · doi:10.1080/03007995.2021.1929894 · Cited by 10
Babtain, F. A., Atteyah, D., Milyani, H. A., et al. (2021) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2021.108229 · Cited by 10
“We calculated the 95% confidence intervals, and interpreted the p-values according to the American statistical association guidelines [15].”
A new electivity index for diet studies that use count data
Kimmerer, W., & Slaughter, A. M. (2021) · Limnology and Oceanography Methods · doi:10.1002/lom3.10446 · Cited by 11
“However, while Pearre (1982) used contingency tables to test for statistical significance, we are less interested in significance (Wasserstein and Lazar 2016; Smith 2020) than in the uncertainty in estimated indices, and have therefore developed methods discussed below to provide confidence…”
MethodDavenport, F., Shukla, S., Turner, W., et al. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/ac15cc · Cited by 10
Effect sizes for contrasts of estimated marginal effects
Shaw, B. P. (2022) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x221083901 · Cited by 10
Cowled, B., Hillman, A., Ward, M. P., Clutterbuck, H., Doyle, M., WARE, J. W., Thomas, M., Plain, K. M., Barwell, R., Laurence, M., et al. (2022) · Australian Veterinary Journal · doi:10.1111/avj.13165 · Cited by 9
Ernst, E., & Smith, K. (2018) · Springer eBooks · doi:10.1007/978-3-319-69941-7_2 · Cited by 9
Emerson, E., Aitken, Z., Totsika, V., King, T. L., Stancliffe, R. J., Hatton, C., Llewellyn, G. M., Hastings, R. P., & Kavanagh, A. M. (2022) · Health & Social Care in the Community · doi:10.1111/hsc.13882 · Cited by 10
“…limitations associated with a sole reliance on null hypothesis significance testing to identify results that may be of social or policy relevance (Wasserstein & Lazar, 2016), we also draw attention in the text to results with notable effect sizes that are not statistically significant (p <…”
BackgroundDisclosure Avoidance and the 2020 Census: What Do Researchers Need to Know?
Groshen, E. L., & Goroff, D. L. (2022) · Harvard Data Science Review · doi:10.1162/99608f92.aed7f34f · Cited by 10
Stressor gradient coverage affects interaction identification
Segurado, P., Gutiérrez‐Cánovas, C., Ferreira, T., et al. (2022) · Ecological Modelling · doi:10.1016/j.ecolmodel.2022.110089 · Cited by 10
Environmental pollution impacts: Are p values over-valued?
Agathokleous, E. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.157807 · Cited by 10
Hullot, M., Merceron, G., & Antoine, P. (2023) · Peer Community Journal · doi:10.24072/pcjournal.222 · Cited by 10
Liu, P. L., Chang, A., Liu, M. T., Ye, J. F., Jiao, W., Ao, H. S., Hu, W., Xu, K., & Zhao, X. (2023) · BMC Public Health · doi:10.1186/s12889-023-15069-0 · Cited by 10
Amanzio, M., Cipriani, G. E., Bartoli, M., Canessa, N., Borghesi, F., Chirico, A., & Cipresso, P. (2023) · Scientific Reports · doi:10.1038/s41598-023-33513-4 · Cited by 11
The Fragility Index of randomized controlled trials in pediatric anesthesiology
Hayes, J., Zuercher, M., Gai, N., Chowdhury, A. R., & Aoyama, K. (2023) · Canadian Journal of Anesthesia/Journal canadien d anesthésie · doi:10.1007/s12630-023-02513-3 · Cited by 11
Considerations for the design, analysis and presentation of in vivo studies
Ranstam, J., & Cook, J. A. (2016) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2016.06.023 · Cited by 10
“terpretations, (1) statistically significant and important difference, (2) statistically”
BackgroundNew apheresis indications in hematological disorders
Pham, H. P., & Schwartz, J. E. (2016) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000288 · Cited by 10
Poltavskiy, E. A., Spence, J. D., Kim, J., & Bang, H. (2016) · Online Journal of Public Health Informatics · doi:10.5210/ojphi.v8i2.6643 · Cited by 10
“When a number of p-values probably the most popular statistical measure in research are computed, a simple ‘p-value plot’ together with AUC could be helpful for assessing overall randomness in associations [8,30,31].”
MethodCowper, P. A., Peterson, M. J., Pieper, C. F., Sloane, R. J., Hall, K. S. M., McConnell, E. S., Bosworth, H. B., Ekelund, C. C., Pearson, M. P., & Morey, M. C. (2017) · Journal of the American Geriatrics Society · doi:10.1111/jgs.14567 · Cited by 10
Беспалов, В. Г., Alvovsky, I. K., Tochilnikov, G. V., et al. (2017) · International Journal of Hyperthermia · doi:10.1080/02656736.2017.1375161 · Cited by 10
“Food and Drug Administration (FDA) [17].”
Sharpe, R., Abrahams, I., & Fotou, N. (2017) · Research in Science & Technological Education · doi:10.1080/02635143.2017.1355783 · Cited by 10
Skeletal effects of failed parathyroidectomy
Zheng, F., Zhou, H. C., Li, N., et al. (2017) · Surgery · doi:10.1016/j.surg.2017.04.045 · Cited by 10
Correct reporting and interpretation of clinical data
Marks, M., & Rodrigues, J. N. (2017) · Journal of Hand Surgery (European Volume) · doi:10.1177/1753193417733154 · Cited by 10
“Covering this and other issues, the American Statistical Association has published a policy statement on p values (Wasserstein and Lazar, 2016): a small p value often induces the inappropriate conclusion of a large treatment effect.”
BackgroundChildhood maltreatment moderates the effect of combat exposure on cingulum structural integrity
Banihashemi, L., Wallace, M. L., Sheu, L. K., Lee, M., Gianaros, P. J., Mackenzie, R. P., Insana, S., Germain, A., & Herringa, R. J. (2017) · Development and Psychopathology · doi:10.1017/s0954579417001365 · Cited by 10
“In accordance with the American Statistical Association’s recent statement, this report focuses on effect sizes, which is the appropriate method to examine a small sample in order to emphasize the clinical (rather than statistical) significance of our findings (Wasserstein & Lazar, 2016).”
BackgroundMethodTrustability-Based Dynamic Active Learning for Crowdsourced Labelling of Emotional Audio Data
Hantke, S., Abstreiter, A., Cummins, N., & Schuller, B. W. (2018) · IEEE Access · doi:10.1109/access.2018.2858931 · Cited by 10
“5In this paper, we report basics for conventional Null Hypothesis Testing (NHT), but refrain from a full-fledged NHT analysis due to its inherent problems [62]; instead, we employ effect sizes [63].”
MethodFactoring a 2 x 2 contingency table
Luck, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0224460 · Cited by 9
“The renewed warnings from the statistics community about the limitations of statistical significance methodology has created a perplexing situation, given that there is a wide range of opinion on the underlying causes and solutions [55, 56].”
BackgroundStrengthening U.S. Politicians’ Reputation
Antoniades, N., & Mohr, I. (2020) · Society · doi:10.1007/s12115-019-00439-5 · Cited by 10
Millikin, R., Shortreed, M. R., Scalf, M., & Smith, L. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00796 · Cited by 11
Meng, C., Xu, Y., Xu, J., Chancoco, H. D., & Gu, J. H. (2020) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-20-0351 · Cited by 10
“In line with recommendations from the American Statistical Association (61, 62), we presented P values against null hypotheses as continuous variables and avoided using P < 0.05 as a threshold to interpret results as statistically “significant” or “not significant.””
MethodInfluentialUtilizing Statistical Tests for Comparing Machine Learning Algorithms
Hamarashid, H. K. (2021) · Kurdistan Journal of Applied Research · doi:10.24017/science.2021.1.8 · Cited by 10
“You may generate a confidence level for the hypothesis based on the observed sample data by subtracting 1 from the significance level [10].”
BackgroundReplication: Challenges in using Data Logs to Validate Phishing Detection Ability MetricsPreprint
Canfield, C., Davis, A. L., Fischhoff, B., Forget, A., Pearman, S., & Thomas, J. (2017) · OSF Preprints (OSF Preprints) · Cited by 10
Linde, M., & van Ravenzwaaij, D. (2019) · arXiv (Cornell University) · Cited by 8
Ly, A., Stefan, A. M., van Doorn, J. B., et al. (2019) · doi:10.31234/osf.io/dhb7x · Cited by 10
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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