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Current controversies: Null hypothesis significance testing
Traditional null hypothesis significance testing (NHST) incorporating the critical level of significance of 0.05 has become the cornerstone of decision‐making in health care, and nowhere less so than in obstetric and gynecological research. However, such
Philip M. Sedgwick +3 more
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Redefine statistical significance [PDF]
"We propose to change the default P-value threshold forstatistical significance for claims of new discoveries from 0.05 to 0.005."
Nyhan, Brendan +78 more
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It is incredibly essential that the current clinicians and researchers remain updated with findings of current biomedical literature for evidence-based medicine.
Hunny Sharma
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A logical analysis of null hypothesis significance testing using popular terminology
Background Null Hypothesis Significance Testing (NHST) has been well criticised over the years yet remains a pillar of statistical inference. Although NHST is well described in terms of statistical models, most textbooks for non-statisticians present the
Richard McNulty
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The tyranny of the P-value: effect size matters
Statistical significance does not necessarily imply clinical significance. A P-value of less than 0.05 does not guarantee that the result will be important. Effect size needs to be calculated in order to appraise clinical relevance.
Leslie Citrome
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Statistical Significance and/or Effect Size? [PDF]
In the paper, we present some dilemmas concerning the use of statistical significance as the only measure for interpreting results and drawing conclusions. We also introduce effect size measures as a complementary measure in interpretation of the results
Tina Štemberger
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How feasible is it to abandon statistical significance? A reflection based on a short survey
Background There is a growing trend in using the “statistically significant” term in the scientific literature. However, harsh criticism of this concept motivated the recommendation to withdraw its use of scientific publications. We aimed to validate the
Fredi Alexander Diaz-Quijano +2 more
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Statistical significance—meaningful or not [PDF]
Statistical tests with large sample sizes can have large power. Power is the ability to detect an effect. Detection is indicated by a result which is statistically significant. A test with large power will detect a very small effect. This very small effect may not be meaningful in the context of the analysis being conducted.
Aitken, Colin, Wilson, Amy, Sleeman, R.
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Errors of Econometric Methodology in the Study of Economics Theories [PDF]
Scientific theories are a way of knowing man. The main difference between this method and other methods is the testability of its claims. Testability helps to correct scientific knowledge of error.
Mojtaba Rostami +3 more
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Talking about Statistical Significance in Numeracy
In recent years, much debate has surrounded the potential for audiences to be mislead by several common practices when reporting statistical significance tests. Two editors of Numeracy share the journals perspectives on these questions.
Nathan Grawe, Gizem Karaali
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