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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“…new (Berger & Wolpert, 1988; Cox, 1958), and some statisticians may even argue that these newly discovered problems are known since decades, the heated discussions ultimately led the American Statistical Association (ASA) to issue an official statement on the situation (Wasserstein & Lazar, 2016).”
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“…an informal definition of a p value as “the probability under a specified statistical model that a statistical summary of the data (e.g., the sample mean difference between two compared groups) would be equal to or more extreme than its observed value” (Wasserstein and Lazar, 2016, our emphasis).”
BackgroundVilaró, M., Cortés, J., Selva-O’Callaghan, A., Urrútia, A., Ribera, J., Cardellach, F., Basagaña, X., Elmore, M., Vilardell, M., Altman, D. G., et al. (2019) · BMC Medical Research Methodology · doi:10.1186/s12874-019-0746-4 · Cited by 38
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Brown, A. W., Altman, D. G., Baranowski, T., Bland, M., Dawson, J., Dhurandhar, N. V., Dowla, S. A., Fontaine, K. R., Gelman, A., Heymsfield, S. B., et al. (2019) · Obesity Reviews · doi:10.1111/obr.12923 · Cited by 38
“05 generally means that if the null hypothesis were true, appropriately calculated test statistics that are equal or greater in magnitude to that observed would occur in fewer than 5% of samples.(71) When many possible analyses of the data are performed, and if the null hypothesis is true, the probability of finding a…”
BackgroundKent, P. M., O’Sullivan, P., Smith, A. J., Haines, T. P., Campbell, A., McGregor, A. H., Hartvigsen, J., O’Sullivan, K., Vickery, A. W., Cañeiro, J. P., et al. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-031133 · Cited by 39
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Statistical Fragility of Surgical and Procedural Clinical Trials in Orthopaedic Oncology
Forrester, L. A., Jang, E. S., Lawson, M. M., Çapi, A., & Tyler, W. K. (2020) · JAAOS Global Research and Reviews · doi:10.5435/jaaosglobal-d-19-00152 · Cited by 39
Watch me go big: CEO narcissism and corporate acquisitions
Aabo, T., Als, M., Thomsen, L., & Wulff, J. N. (2020) · Review of Behavioral Finance · doi:10.1108/rbf-05-2020-0091 · Cited by 42
van Solinge, H., Damman, M., & Hershey, D. A. (2020) · Work Aging and Retirement · doi:10.1093/workar/waaa027 · Cited by 41
“For a discussion of concerns regarding an over-reliance on p-values, the interested reader is directed to a paper by Wasserstein and Lazar (2016).).”
MethodKatiforis, I., Fleming, E. A., Haszard, J., Hape-Cramond, T., Taylor, R., & Heath, A. (2021) · Nutrients · doi:10.3390/nu13020657 · Cited by 35
“It was decided to use box plots to present the data visually rather than presenting results from statistical tests because box plots display all of the data, allowing for transparency when making conclusions about the significance of the results, rather than relying on p-values for interpretation, which have limitatio…”
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Detection of Ventricular Arrhythmia by using Heart rate variability signal and ECG beat image
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Species-Level Resolution of Female Bladder Microbiota from 16S rRNA Amplicon Sequencing
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“fiers and databases (50–52), classifiers and identifiers (53, 54), or individual components of the classification scheme for application in microbiome studies.”
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Unveiling Fast Field Oscillations through Comodulation
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“Statistics We opted to exclude p-value–only based decisions because of recent concerns in the field and as an effort to increase statistical quality (Wasserstein and Lazar, 2016).”
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Mammogram classification using dynamic time warping
Gardezi, S. J. S., Faye, I., Sánchez‐Bornot, J. M., Kamel, N., & Hussain, M. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-016-4328-8 · Cited by 36
“The smaller p-values, the greater the chances to reject the null hypothesis [46].”
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Nicolson, M., Huebner, G. M., Shipworth, D., & Elam, S. (2017) · Nature Energy · doi:10.1038/nenergy.2017.73 · Cited by 35
Analysis of age as a factor in NASA astronaut selection and career landmarks
Kovacs, G., & Shadden, M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0181381 · Cited by 30
Winger, J. G., Rand, K. L., Hanna, N. H., Jalal, S. I., Einhorn, L. H., Birdas, T. J., Ceppa, D. P., Kesler, K. A., Champion, V. L., & Mosher, C. E. (2018) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2018.01.005 · Cited by 36
Quality of Experience for 3-D Immersive Media Streaming
Doumanoglou, A., Griffin, D. P., Serrano, J., et al. (2018) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2018.2823909 · Cited by 36
“We then obtained the p-values [41] for the rest of inputs.”
MethodNead, K. T., Wehner, M. R., & Mitra, N. (2018) · JAMA Oncology · doi:10.1001/jamaoncol.2018.4524 · Cited by 36
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“Based on recommendations from the American Statistical Association, we present the results with 95% CIs and do not present the p-values associated with results (Wasserstein and Lazar 2016).”
MethodInvestor herding behaviour in globally listed shipping stocks
Syriopoulos, T. C., & Bakos, G. (2019) · Maritime Policy & Management · doi:10.1080/03088839.2019.1597288 · Cited by 37
Unemployment and education mismatch in the EU before and after the financial crisis
Pompei, F., & Selezneva, E. (2019) · Journal of Policy Modeling · doi:10.1016/j.jpolmod.2019.09.009 · Cited by 36
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QueryVis: Logic-based Diagrams help Users Understand Complicated SQL Queries Faster
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“05 as a cutoff for “significant” results — can lead to erroneous beliefs and poor decisionmaking [10, 38, 39, 80].”
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“If there is anything misspecified about the model like confounding, suppression, or contamination, then the p-value is uninformative [26].”
BackgroundVinceti, M., Bonaccio, M., Filippini, T., Costanzo, S., Wise, L. A., Castelnuovo, A. F. D., Ruggiero, E., Persichillo, M., Cerletti, C., Donati, M. B., et al. (2021) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2021.02.016 · Cited by 36
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Big data and partial least‐squares prediction
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“We found the ASA’s statement interesting as a reflection of how Statistics relates to the scientific community.”
BackgroundMueller, S. C., Cromheeke, S., Šiugždaitė, R., & Boehler, C. N. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.06.004 · Cited by 39
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Bayesian data analysis for newcomersPreprint
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Predicting field diseases caused by Sclerotinia sclerotiorum : A review
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Xiong, X., Lui, D. T. W., Chung, M. S. H., Au, I. C. H., Lai, F. T. T., Wan, E. Y. F., Chui, C. S. L., Li, X., Cheng, F. W. T., Cheung, C., et al. (2023) · PLoS Medicine · doi:10.1371/journal.pmed.1004274 · Cited by 38
“Following the recommendation of the American Statistical Association [35], we presented 95% of two-sided CIs and interpreted the results based on point estimates with their respective CIs.”
MethodEffects of the Million Hearts Model on Myocardial Infarctions, Strokes, and Medicare Spending
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“We focused on the estimation and precision of our results rather than on hypothesis testing (Wasserstein and Lazar 2016).”
Messerlian, C., & Gaskins, A. J. (2017) · Current Epidemiology Reports · doi:10.1007/s40471-017-0105-0 · Cited by 34
The Heuristic Value of p in Inductive Statistical Inference
Krueger, J. I., & Heck, P. R. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00908 · Cited by 33
“However, the standard p-value is the inverse of this conditional probability, namely the probability of the data (or data more extreme) given the hypothesis, p(D|H) (Wasserstein and Lazar, 2016).”
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Research Dilemmas with Behavioral Big Data
Galit Shmueli, A. (2017) · Big Data · doi:10.1089/big.2016.0043 · Cited by 35
“37 While in some fields there are efforts to move away from using p -value cutoffs as decision points, 38 the practice is very common in both academia and in practice, possibly because proposed alternatives (e.g., ignoring p values altogether, 39 using estimation in place of testing, adopting a…”
Introduction to Bayesian Modeling and Inference for Fisheries Scientists
Doll, J. C., & Jacquemin, S. (2018) · Fisheries · doi:10.1002/fsh.10038 · Cited by 35
Sensor Data Based System-Level Anomaly Prediction for Smart Manufacturing
Wang, J., Liu, C., Zhu, M., Guo, P., & Hu, Y. (2018) · IEEE International Congress on Big Data (BigData Congress) · doi:10.1109/bigdatacongress.2018.00028 · Cited by 37
“It can be modeled as <timestamp, sensorID, deviceID, valueArray, probability>, where the events are either individual records or subsequences depending on the length of valueArray, and probability can be calculated by different approaches including euclidean distance and p-value [18].”
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“research in which it was highlighted that the p-value “does not provide a good measure of evidence regarding a model or hypothesis” (Wasserstein and Lazar, 2016).”
Move out or dig in? Risk awareness and mobility plans in disaster‐affected communities
Haney, T. J. (2018) · Journal of Contingencies and Crisis Management · doi:10.1111/1468-5973.12253 · Cited by 36
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Robot-assisted flexible needle insertion using universal distributional deep reinforcement learning
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Assessing heterogeneity and power in replications of psychological experiments.
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Woodside, A. G. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.05.027 · Cited by 35
“…(NHTS) are detrimental to advancing accurate and useful knowledge (Armstrong, 2010; Hubbard, 2015; McCloskey, 2002; Meehl, 1978; Wasserstein, 2016; Wasserstein & Lazar, 2016; Woodside, 2019; Ziliak & McCloskey, 2008) and NHTS is detrimental to effective decision-making (Hauer, 2004; Ziliak &…”
Water warming increases aggression in a tropical fish
Kua, Z. X., Hamilton, I. M., McLaughlin, A. L., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-76780-1 · Cited by 35
Rowland, F. E., Stow, C., Johnson, L., & Hirsch, R. (2021) · Ecological Indicators · doi:10.1016/j.ecolind.2021.107601 · Cited by 31
How to use likelihood ratios to interpret evidence from randomized trials
Perneger, T. (2021) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2021.04.010 · Cited by 35
Exposure and health risk assessment of indoor volatile organic compounds in a medical university
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Assessing the robustness of results from clinical trials and meta-analyses with the fragility index
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Causality in Econometrics: Choice vs Chance
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“However, in recent years there has been increasing concern that such calculations do not answer the primary questions of interest for decision makers which typically depend on magnitudes of the causal effects and not just their presence (e.g., Wasserstein and Lazar (2016), Imbens (2021)).”
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Beliefs about suicide acceptability in the United States: how do they affect suicide mortality?
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Reasonable patient care under uncertainty
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A Poor Prognosis for the Diagnostic Screening Critique of Statistical TestsPreprint
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The Middle Voice and Connected Constructions in Ibero-Romance
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Prescription Stimulant Use During Pregnancy and Risk of Neurodevelopmental Disorders in Children
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Improving the Quality of the Reporting of Research Results
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Save this Honorable Court: Shaping Public Perceptions of the Supreme Court Off the Bench
Krewson, C. N. (2018) · Political Research Quarterly · doi:10.1177/1065912918801563 · Cited by 35
“Although they are important, a large body of literature suggests p values are an inconclusive means of evaluating results (e.g., see Gill 2018; Wasserstein and Lazar 2016).”
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“All p values are reported as recommended by the American Statistical Association.”
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Attitudes Underlying Reliance on Complementary and Alternative Medicine
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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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