Results 11 to 20 of about 113,606 (254)
The state of the art of hypothesis testing in the social sciences
Social Sciences and Humanities Open, 2022 Over many decades, one seemingly fatal critique after another has been launched against the use of social sciences' dominant practice of null-hypothesis significance testing, also known as NHST.
Arjen van Witteloostuijn +1 more
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The reporting of p values, confidence intervals and statistical significance in Preventive Veterinary Medicine (1997–2017) [PDF]
PeerJ, 2021 Background Despite much discussion in the epidemiologic literature surrounding the use of null hypothesis significance testing (NHST) for inferences, the reporting practices of veterinary researchers have not been examined.
Locksley L. McV. Messam +5 more
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Public Health and Toxicology, 2021 Null hypothesis significance testing (NHST) text was once widely popular and almost systematically used for the identification of causal relations and for risk assessment in toxicology and medicine.
Silvio Roberto Vinceti +1 more
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Farewell to Bright-Line: A Guide to Reporting Quantitative Results Without the S-Word
Frontiers in Psychology, 2020 Recent calls to end the practice of categorizing findings based on statistical significance have focused on what not to do. Practitioners who subscribe to the conceptual basis behind these calls may be unaccustomed to presenting results in the nuanced ...
Kevin M. Cummins +3 more
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Manipulating the Alpha Level Cannot Cure Significance Testing
Frontiers in Psychology, 2018 We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science.
David Trafimow +67 more
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Indian Dermatology Online Journal, 2019 Biomedical research relies on proving (or disproving) a research hypothesis, and P value becomes a cornerstone of “null hypothesis significance testing.” P value is the maximum probability of getting the observed outcome by chance. For a statistical test
Amrita Sil +2 more
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Upsala Journal of Medical Sciences, 2022 Background: The aim was to investigate inferences of statistically significant test results among persons with more or less statistical education and research experience.
Per Lytsy, Mikael Hartman, Ronnie Pingel
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A Review of Bayesian Hypothesis Testing and Its Practical Implementations
Entropy, 2022 We discuss hypothesis testing and compare different theories in light of observed or experimental data as fundamental endeavors in the sciences. Issues associated with the p-value approach and null hypothesis significance testing are reviewed, and the ...
Zhengxiao Wei +4 more
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Bleeding, Thrombosis and Vascular Biology, 2022 Scientific literature is overflowing of significance testing and p-values.
Augusto Di Castelnuovo +1 more
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Frontiers in Neuroinformatics, 2021 Classical null hypothesis significance testing is limited to the rejection of the point-null hypothesis; it does not allow the interpretation of non-significant results. This leads to a bias against the null hypothesis.
Ruslan Masharipov +6 more
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