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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“We presented RRs and 95% CIs, to avoid misleading signi fi cance threshold interpretations commonly associated with P values [65,66].”
MethodSchader, L. M., Song, W., Kempker, R. R., et al. (2024) · Epidemiology · doi:10.1097/ede.0000000000001782 · Cited by 21
Gestational organophosphate pesticide exposure and childhood cardiovascular outcomes
Stevens, D. R., Blaauwendraad, S. M., Bommarito, P. A., van den Dries, M. A., Trasande, L., Spaan, S., Pronk, A., Tiemeier, H. W., Gaillard, R., Jaddoe, V. W. V., et al. (2024) · Environment International · doi:10.1016/j.envint.2024.109082 · Cited by 22
Aasvik, O., Ulleberg, P., & Hagenzieker, M. (2024) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.10.025 · Cited by 22
Roesch-McNally, G. E. (2018) · Environments · doi:10.3390/environments5040049 · Cited by 21
“The American Statistical Association suggests that researchers should rely-on and interpret p-values with caution [65] therefore the raw p-values (see Tables S1–S5) for each set of covariates in each model are also reported.”
BackgroundAyis, S. A., Rudd, A. G., Ayerbe, L., & Wolfe, C. D. A. (2019) · European Journal of Neurology · doi:10.1111/ene.13899 · Cited by 21
“No formal tests were used to compare estimates across trajectories, with the exception of a few selections, due to the large number of comparisons and the likely inflation of Type I error [14].”
MethodBelazi, W., Ouldboukhitine, S.-E., Chateauneuf, A., et al. (2019) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2019.02.020 · Cited by 21
Willie, T. C., Keene, D. E., Stockman, J. K., Alexander, K. A., Calabrese, S. K., & Kershaw, T. (2019) · AIDS and Behavior · doi:10.1007/s10461-019-02469-w · Cited by 21
Distribution of the C statistic with applications to the sample mean of Poisson data
Bonamente, M. (2019) · Journal of Applied Statistics · doi:10.1080/02664763.2019.1704703 · Cited by 21
Eyre, E. L. J., Clark, C. C. T., Tallis, J. A., Hodson, D., Lowton-Smith, S., Nelson, C., Noon, M. R., & Duncan, M. J. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17103391 · Cited by 23
“Bayesian analysis was incorporated because it allows the combination of domain-specific knowledge, permits direct probability statements to be made about parameters (population level effects), allows zero effects to be determined, provides estimates of uncertainty around parameter values that are more intuitively inte…”
BackgroundSzarek, P., Lilledahl, M. B., Emery, N. C., et al. (2020) · Osteoarthritis and Cartilage Open · doi:10.1016/j.ocarto.2020.100086 · Cited by 21
Cognitive abilities - a new direction in burnout research
Kulikowski, K. (2020) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2020.1841284 · Cited by 27
“Although this indirect effect was marked as “nonsignificant” (p =.086 and 95%CI [−.001 .019]), but as nonsignificant does not mean not important (Wasserstein & Lazar, 2016), we see this effect at least as suggestive that theoretical proposition of the dual effect of cognitive ability on burnout is…”
ResultReliability of additional reported seizure manifestations to identify dissociative seizures
Kerr, W. T., Zhang, X., Janio, E. A., Karimi, A. H., Allas, C. H., Dubey, I., Sreenivasan, S. S., Bauirjan, J., D’Ambrosio, S. R., Banna, M. A., et al. (2020) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2020.107696 · Cited by 21
“Thus, we did not apply a correction for multiple statistical tests [43-45].”
MethodIdentification of a neural basis for cold acclimation in Drosophila larvae
Himmel, N. J., Letcher, J. M., Sakurai, A., Gray, T. R., Benson, M. N., Donaldson, K. J., & Cox, D. N. (2021) · iScience · doi:10.1016/j.isci.2021.102657 · Cited by 20
Lanzano, G., Sgobba, S. A., Caramenti, L., et al. (2021) · Bulletin of the Seismological Society of America · doi:10.1785/0120210044 · Cited by 21
A Review of Bayesian Hypothesis Testing and Its Practical Implementations
Wei, Z., Yang, A., Rocha, L. S., Miranda, M. F., & Nathoo, F. S. (2022) · Entropy · doi:10.3390/e24020161 · Cited by 25
“To prevent the misuse and misinterpretation of p-values, the American Statistical Association (ASA) issued a statement clarifying six principles for the proper use and interpretation of classical significance testing [12]: (i) p-values can indicate how incompatible the data are with a specified statistical model; (ii)…”
BackgroundMethodTesting tests before testing data: an untold tale of compound events and binary dependence
Serinaldi, F., Lombardo, F., & Kilsby, C. G. (2022) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-022-02190-6 · Cited by 23
“…McBride et al. 1993; Meehl 1997; Gill 1999; Johnson 1999; Nicholls 2001; Levine et al. 2008; Clarke 2010; Beninger et al. 2012; Ellison et al. 2014; Nuzzo 2014; Briggs 2016; Greenland et al. 2016; Wasserstein and Lazar 2016; Serinaldi et al. 2018; Wasserstein et al. 2019, and references therein).”
BackgroundInferential Statistics Is an Unfit Tool for Interpreting Data
Sand, A. (2022) · Applied Sciences · doi:10.3390/app12157691 · Cited by 31
Addressing Common Misuses and Pitfalls of P values in Biomedical Research
Wang, M., & Long, Q. (2022) · Cancer Research · doi:10.1158/0008-5472.can-21-2978 · Cited by 23
The Effects of Prenatal Bisphenol a Exposure on Brain Volume of Children and Young MicePreprint
Zheng, J., Reynolds, J. E., Long, M., Ostertag, C., Pollock, T., Hamilton, M., Dunn, J. F., Liu, J., Martin, J. W., Grohs, M. N., et al. (2022) · SSRN Electronic Journal · doi:10.1016/j.envres.2022.114040 · Cited by 24
Modeling climate migration: dead ends and new avenues
Beyer, R. M., Schewe, J., & Abel, G. (2023) · Frontiers in Climate · doi:10.3389/fclim.2023.1212649 · Cited by 28
Believing is seeing – the deceptive influence of bias in quantitative microscopy
Lee, R., Eisenman, L. R., Khuon, S., Aaron, J., & Chew, T. (2024) · Journal of Cell Science · doi:10.1242/jcs.261567 · Cited by 25
“…figure design (Lord et al., 2020) and statistical best practices (Bishop, 2020; Curran-Everett, 2013; Makin and Orban de Xivry, 2019; Nuzzo, 2014; Wasserstein and Lazar, 2016) both strengthens experimental design and helps counteract biases in quantification, although it should be noted that…”
BackgroundXu, S., Marcon, A., Bertelsen, R. J., Benediktsdóttir, B., Brandt, J. G., Frohn, L. M., Geels, C., Gíslason, Þ., Heinrich, J., Holm, M., et al. (2024) · Environmental Research · doi:10.1016/j.envres.2024.119240 · Cited by 20
Null hypothesis significance testing: a short tutorial
Pernet, C. R. (2016) · F1000Research · doi:10.12688/f1000research.6963.3 · Cited by 24
Survival analysis, more than meets the eye
Lucijanić, M., Skelin, M., & Lucijanić, T. (2017) · Biochemia Medica · doi:10.11613/bm.2017.002 · Cited by 21
Data Mining in HIV-AIDS Surveillance System
de Oliveira, A. C. M., Faria, B. M., Gaio, R., et al. (2017) · Journal of Medical Systems · doi:10.1007/s10916-017-0697-4 · Cited by 21
“Moreover, any effect, no matter how tiny, can produce a small p-value if the sample size or measurement precision is high enough [31].”
BackgroundEffects of oxygen-enriched air on cognitive performance during SCUBA-diving – an open-water study
Brebeck, A.-K., Deußen, A., Schmitz‐Peiffer, H., et al. (2017) · Research in Sports Medicine · doi:10.1080/15438627.2017.1314289 · Cited by 21
“This statement is intended to steer research into a “post p 0.05 era” (Wasserstein & Lazar, 2016).”
BackgroundInfluentialAnalysis of structural brain MRI and multi-parameter classification for Alzheimer’s disease
Zhang, Y., & Liu, S. (2017) · Biomedizinische Technik/Biomedical Engineering · doi:10.1515/bmt-2016-0239 · Cited by 21
East Asian wisdom and relativity
Baumann, C., Winzar, H. F., & Fang, T. (2018) · Cross Cultural & Strategic Management · doi:10.1108/ccsm-01-2018-0007 · Cited by 23
“The American Statistical Association has long campaigned against such naïve reliance on p-values, with some success (Wasserstein and Lazar, 2016).”
BackgroundHoriguchi, M., Cronin, A., Takeuchi, M., & Uno, H. (2018) · Statistics in Medicine · doi:10.1002/sim.7661 · Cited by 23
“Unfortunately, even if the P value is quite small, sole P values do not provide enough risk‐benefit information for decision making.(32) We need a robust, interpretable quantitative summary of the treatment effect that corresponds to the prespecified primary test.”
BackgroundRutherford, L., Singleton, A., Derr, L. A., & Merga, M. K. (2018) · Public Library Quarterly · doi:10.1080/01616846.2018.1511214 · Cited by 25
“Given that it is impossible to calculate sampling error for non-probability samples, our approach avoids using p-values (a measure of sampling error) as a guarantee of “statistically significant” findings, in line with the APA’s recent statement about this matter (Wasserstein and Lazar 2016).”
ResultA Patient-Centered Proposal for Bayesian Analysis of Self-Experiments for Health
Schroeder, J., Karkar, R., Fogarty, J. A., Kientz, J. A., Munson, S. A., & Kay, M. (2018) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-018-0033-x · Cited by 21
“In addition to being noisy in small samples, p -values are not in the language of outcomes: as the American Statistical Association (ASA) explains, p -values do not directly translate onto the magnitude of the effect [63].”
BackgroundCorrecting Corrupt Research: Recommendations for the Profession to Stop Misuse of p -Values
Kmetz, J. L. (2019) · The American Statistician · doi:10.1080/00031305.2018.1518271 · Cited by 21
“Additionally, in 2016 the American Statistical Association (ASA) published its Statement on Statistical Significance and P-Values (Wasserstein and Lazar 2016).”
BackgroundLinking Big Data and Prediction Strategies: Tools, Pitfalls, and Lessons Learned
Yang, S., Stansbury, L. G., Rock, P., Scalea, T. M., & Hu, P. (2019) · Critical Care Medicine · doi:10.1097/ccm.0000000000003739 · Cited by 22
Guidelines for Experimental Algorithmics: A Case Study in Network Analysis
Angriman, E., van der Grinten, A., von Looz, M., Meyerhenke, H., Nöllenburg, M., Predari, M., & Tzovas, C. (2019) · Algorithms · doi:10.3390/a12070127 · Cited by 25
Heino, M. T. J., Knittle, K. P., Fried, E. I., Sund, R., Haukkala, A., Borodulin, K., Uutela, A. K., Araújo‐Soares, V., Vasankari, T. J., & Hankonen, N. E. (2019) · Health Psychology and Behavioral Medicine · doi:10.1080/21642850.2019.1646136 · Cited by 21
“…con fi dence intervals are more appropriate to report than p -values, as they provide readily interpretable values on the same scale as the original variable, accommodating inferences of practical relevance (Gardner & Altman, 1986; Nosek et al., 2018; Sterne, 2001; Wasserstein & Lazar, 2016).”
BackgroundYeboah, D., Steinmeister, L., Hier, D. B., Hadi, B., Wunsch, D. C., Olbricht, G. R., & Obafemi-Ajayi, T. (2020) · IEEE Access · doi:10.1109/access.2020.3027453 · Cited by 21
“in that it does not measure the size of an effect and may not always translate to practically significant results [50], as in the case of the sodium and body temperature values.”
BackgroundAlföldi, Z., Borysławski, K., Ihász, F., Soós, I., & Podstawski, R. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.747781 · Cited by 21
Mai, G., & Wang, W. Y. (2023) · Human Brain Mapping · doi:10.1002/hbm.26503 · Cited by 19
“…definition, that is, the probability of the bootstrap results when they are more extreme than the actual test statistic given the null distribution (Wasserstein & Lazar, 2016): where Pr refers to probability, T is the bootstrap result (given the null distribution) and t is the actual test…”
BackgroundPacheco, C. R., Culkin, V., Putkaradze, A., & Zeng, N. (2025) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-025-01705-y · Cited by 29
Effect sizes for experimental research
Hedges, L. V. (2025) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12389 · Cited by 20
Humans and stuff: Interweaving social and physical science in energy policy research
Galvin, R. (2017) · Energy Research & Social Science · doi:10.1016/j.erss.2017.01.012 · Cited by 20
“The American Statistics Association also complains that very few engage with the ubiquitous problem of what level of ‘significance’ is significant for whom, even if the numbers are right (Wasserstein and Lazar, 2016).”
BackgroundExperimental investigation of the effects of acute exercise on memory interference
Wingate, S., Crawford, L. K., Frith, E., & Loprinzi, P. D. (2018) · Health Promotion Perspectives · doi:10.15171/hpp.2018.28 · Cited by 20
Das, N., Sil, A., & Betkerur, J. B. (2019) · Indian Dermatology Online Journal · doi:10.4103/idoj.idoj_368_19 · Cited by 20
“The concern was of that extent that some journal banned the use of P‐value (null hypothesis significance testing).[3]”
BackgroundSironi, M., Ploubidis, G. B., & Grundy, E. M. D. (2020) · Demography · doi:10.1007/s13524-020-00855-x · Cited by 20
Matthews, R. (2020) · Journal of the Royal Society of Medicine · doi:10.1177/0141076820921050 · Cited by 20
Harbour seals responded differently to pulses of out-migrating coho and Chinook smolts
Allegue, H., Thomas, A., Liu, Y., & Trites, A. W. (2020) · Marine Ecology Progress Series · doi:10.3354/meps13389 · Cited by 20
Åvitsland, A., Leibinger, É., Resaland, G. K., Solberg, R. B., Kolle, E., & Dyrstad, S. M. (2020) · Mental health and physical activity · doi:10.1016/j.mhpa.2020.100348 · Cited by 26
“In an effort to adhere to the American Statistical Association’s statement on statistical significance and p-values (Wasserstein & Lazar, 2016), and more recent recommendations in a special issue of the journal The American Statistician (Wasserstein, Schirm, & Lazar, 2019); we do not dichotomously…”
Fogg, C., Bridges, J., Meredith, P., Spice, C., Field, L., Culliford, D. J., & Griffiths, P. (2020) · Age and Ageing · doi:10.1093/ageing/afaa133 · Cited by 20
Statistical analysis of some correlations between compression index and Atterberg limits
Spagnoli, G., & Shimobe, S. (2020) · Environmental Earth Sciences · doi:10.1007/s12665-020-09272-0 · Cited by 20
Spotted owls and forest fire: Comment
Jones, G. M., Gutiérrez, R. J., Block, W. M., Carlson, P. C., Comfort, E. J., Cushman, S. A., Davis, R. J., Eyes, S. A., Franklin, A. B., Ganey, J. L., et al. (2020) · Ecosphere · doi:10.1002/ecs2.3312 · Cited by 19
“Lee (2018) makes this claim because mean effects were not “statistically significant” at the a = 0.05 level, even though this is increasingly recognized as an arbitrary threshold on which to base inference (Wasserstein and Lazar 2016, Dushoff et al. 2018, Amrhein et al. 2019).”
BackgroundInfluentialLawford, B. J., Bennell, K. L., Campbell, P. K., Kasza, J., & Hinman, R. S. (2020) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/23386 · Cited by 22
“However, in accordance with recommendations from the American Statistical Association [53], we did not interpret our results on the basis of statistical significance alone, instead considering the clinical significance of the findings.”
ResultTucker, M. A., Idrissi, A., & Almeida, D. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.586464 · Cited by 20
“, 2016; Gigerenzer, 2004; Haller and Krauss, 2002), promote unhelpful dichotomous thinking about the results (Cumming, 2014; Wasserstein and Lazar, 2016) and do not easily support cumulative weighing of the evidence (for instance, it is unclear what conclusions follow from replications that fail to reach p < 0.”
BackgroundThe Cross-National Relationship Between Women’s Autonomy and Long-Term Homicide Trends
Santos, M. R., Jacobson, D. E., & Georgiev, G. G. (2021) · International Criminology · doi:10.1007/s43576-021-00025-y · Cited by 20
Penzenstadler, B., Torkar, R., & Montes, C. M. (2022) · Empirical Software Engineering · doi:10.1007/s10664-022-10148-z · Cited by 27
“…interviews.7 7We decided to not work with hypotheses for the statistical part because the American Association for Statistics recommends to not use dichotomous hypothesis testing because very seldom when we study complex systems we can derive to such an easy T/F answer (Wasserstein and Lazar 2016).”
BackgroundBabaei, S., Amirabadi, R., Taghikhany, T., et al. (2021) · Ocean Engineering · doi:10.1016/j.oceaneng.2021.110116 · Cited by 20
The Fragility of Statistically Significant Results in Gynaecologic Surgery: A Systematic Review
Pascoal, E., Liu, M., Lin, L., et al. (2021) · Journal of Obstetrics and Gynaecology Canada · doi:10.1016/j.jogc.2021.11.016 · Cited by 20
Modeling functional difference between gyri and sulci within intrinsic connectivity networks
Wang, Q., Zhao, S., He, Z., Zhang, S., Jiang, X., Zhang, T., Liu, T., Liu, C., & Han, J. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac111 · Cited by 20
Serum lead levels and its association with overweight and obesity
Hernández‐Mendoza, H., Ríos-Lugo, M. J., Álvarez-Loredo, H. E., Romero-Guzmán, E. T., Gaytán-Hernández, D., Martínez-Navarro, I., Juárez-Flores, B. I., & Chang-Rueda, C. (2022) · Journal of Trace Elements in Medicine and Biology · doi:10.1016/j.jtemb.2022.126984 · Cited by 20
Kulkarni, R. U., Wang, C. L., & Bertozzi, C. R. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010061 · Cited by 22
“While p -values are useful, they are best paired with a measure of effect size [35,36].”
BackgroundAffatato, O., Miguet, M., Schiöth, H. B., & Mwinyi, J. (2021) · The Journal of Headache and Pain · doi:10.1186/s10194-021-01356-x · Cited by 21
Larson, C., Rivera-Figueroa, K., Thomas, H., FEIN, D. A., Stevens, M. C. G., & Eigsti, I. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103043 · Cited by 20
Reed, C. C., Berhe, A. A., Moreland, K. C., Wilcox, J., & Sullivan, B. W. (2022) · Ecological Applications · doi:10.1002/eap.2677 · Cited by 21
Wijs, L. A., Doherty, D. A., Keelan, J. A., et al. (2022) · Human Reproduction · doi:10.1093/humrep/deac122 · Cited by 20
“No adjustment for multiple testing was applied in accordance with the recommendations of the American Statistical Association (Lew, 2016; Wasserstein and Lazar, 2016).”
MethodXu, A. L., Ortiz-Babilonia, C. D., Gupta, A., Rogers, D. L., Aiyer, A. A., & Vulcano, E. (2022) · Foot & Ankle Orthopaedics · doi:10.1177/24730114221119758 · Cited by 21
Travis-Lumer, Y., Goldberg, Y., & Levine, S. Z. (2022) · Emerging Themes in Epidemiology · doi:10.1186/s12982-022-00118-7 · Cited by 20
Schuberth, F., Rosseel, Y., Rönkkö, M., Trinchera, L., Kline, R. B., & Henseler, J. (2022) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2022.2134140 · Cited by 19
“Researchers should additionally pay attention to the magnitude of the estimates (Wasserstein et al., 2019; Wasserstein & Lazar, 2016).”
BackgroundThe Challenge of Quantification: An Interdisciplinary Reading
Fiore, M. D., Kuc-Czarnecka, M. E., Piano, S. L., Puy, A., & Saltelli, A. (2022) · Minerva · doi:10.1007/s11024-022-09481-w · Cited by 21
“Statistical institutes urgently issue guidelines (Wasserstein and Lazar 2016), while a significant number of statistical professionals launch a petition to abolish the concept of significance altogether (Amrhein, Greenland, and McShane 2019; Gelman 2019).”
BackgroundDemarquette, A., Perrault, T., Alapetite, T., Bouizegarene, M., Bronnert, R., Fouré, G., Masson, C., Nicolas, V., Lasocki, S., & Léger, M. (2023) · British Journal of Anaesthesia · doi:10.1016/j.bja.2023.01.001 · Cited by 25
Rot‐Jaune‐Verde: On linguistic bias of referees in Swiss soccer*
Faltings, R., Krumer, A., & Lechner, M. (2023) · Kyklos · doi:10.1111/kykl.12332 · Cited by 20
Skidmore, J., Oleson, J., Yuan, Y., et al. (2023) · Ear and Hearing · doi:10.1097/aud.0000000000001389 · Cited by 20
“It should be pointed out that the significance of the results was not evaluated exclusively based on p -values but also based on its impact on clinical outcomes following the recommended best practice in the field of biostatistics (Wasserstein & Lazar 2016).”
BackgroundResponses of multimetric indices to disturbance are affected by index construction features
Ruaro, R., Gubiani, É. A., Padial, A. A., Karr, J. R., Hughes, R. M., & Mormul, R. P. (2024) · Environmental Reviews · doi:10.1139/er-2023-0098 · Cited by 20
Quin, N., Tikotzky, L., Astbury, L., Spina, M.-A., Fisher, J., Stafford, L., Wiley, J. F., & Bei, B. (2024) · SLEEP · doi:10.1093/sleep/zsae106 · Cited by 23
“Following the American Statistician Association’s recommendation not to base scientific conclusions only on whether a p -value passes a specific threshold [66], we present ESs and 95% confidence intervals along with p -values for group differences at each time point.”
MethodAceituno, D., Fawsitt, C., Power, G. M., Law, E. H., Vaghela, S., & Thom, H. H. Z. (2024) · Journal of the European Academy of Dermatology and Venereology · doi:10.1111/jdv.20372 · Cited by 20
“39 We found no evidence of a difference between ritlecitinib 50 mg and baricitinib 4 mg on SALT ≤10 and SALT ≤20, across all the models.”
‘Big data’ and policy learning
Dunleavy, P. (2017) · Bristol University Press eBooks · doi:10.2307/j.ctt1t89d4k.15 · Cited by 20
Odintsova, V. Y., Tyakht, A., & Alexeev, D. G. (2017) · Current Issues in Molecular Biology · doi:10.21775/cimb.024.017 · Cited by 20
“Therefore, one should be wary when basing the conclusions of a metagenomic study on P-value analysis alone (Baker, 2016; Wasserstein and Lazar, 2016).”
BackgroundWood, B. L., Mocko, M., Everson, M., et al. (2018) · CHANCE · doi:10.1080/09332480.2018.1467642 · Cited by 20
Do frequent exposures to threats and violence at work affect later workforce participation?
Biering, K., Andersen, L. P., Høgh, A., et al. (2018) · International Archives of Occupational and Environmental Health · doi:10.1007/s00420-018-1295-6 · Cited by 20
“According to recommendations by the American Statistical Association, we do not base the interpretation of the findings on statistical significance, but rather on the size and the direction of the estimates (Wasserstein and Lazar 2016).”
Method
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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