NHST

Library / Papers (10)

1. Abandon Statistical Significance (2019) by Blakeley B. McShane et al.
2. Absence of Evidence is Not Evidence of Absence (1995) by D. G Altman et al. 1
3. Confusion Over Measures of Evidence (p's) Versus Errors (alpha's) In Classical Statistical Testing (2003) by Raymond Hubbard et al. 1
4. Erroneous Analyses of Interactions in neuroscience (2011) by Sander Nieuwenhuis et al. 1
5. On the Problem of the Most Efficient Tests of Statistical Hypotheses (1933) by Jerzy Neyman et al. 1
6. P values, Hypothesis tests, and likelihood (1993) by Steven N Goodman 2
7. Some Difficulties of Interpretation Encountered in the Application of the Chi-Square Test (1938) by Joseph Berkson 3 1
8. Statistical Significance and Effect Size reporting (1998) by Thompson B
9. Testing the Approximate Validity of Statistical Hypotheses (1954) by J. L. Hodges et al. 2 2
10. The Failure of Null Hypothesis Significance Testing When Studying Incremental Changes, and What to Do about It (2017) by Andrew Gelman

Library / Web (1)

1. Surely God Loves 51 km/h Nearly as Much as 49 km/h? by Daniel Lakens

Library / Quotes (6)

1. "Absence of Evidence is Not Evidence of Absence" (1995) by D. G Altman et al.
2. "Incorrect Statistical Procedures in Neuroscience" (2011) by Sander Nieuwenhuis et al.
3. "Neyman-Pearson vs. Fisher" (1993) by Steven N Goodman et al.
4. "Neyman–pearson vs. Fisher" (2003) by Raymond Hubbard et al.
5. "NHST" (1933) by Jerzy Neyman et al.
6. "Scientific Method" (1993) by Steven N Goodman et al.