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Literature DB >> 11434499

Two cheers for P-values?

Abstract

P-values are a practical success but a critical failure. Scientists the world over use them, but scarcely a statistician can be found to defend them. Bayesians in particular find them ridiculous, but even the modern frequentist has little time for them. In this essay, I consider what, if anything, might be said in their favour.

Entities: Disease

Mesh：

Year: 2001 PMID： 11434499 DOI： 10.1080/135952201753172953

Source DB: PubMed Journal: J Epidemiol Biostat ISSN： 1359-5229

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Cited

10 in total

1. On Causal Inferences for Personalized Medicine: How Hidden Causal Assumptions Led to Erroneous Causal Claims About the D-Value.

Authors: Sander Greenland; Michael P Fay; Erica H Brittain; Joanna H Shih; Dean A Follmann; Erin E Gabriel; James M Robins
Journal: Am Stat Date: 2019-05-20 Impact factor: 8.710

2. For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates.

Authors: Sander Greenland
Journal: Eur J Epidemiol Date: 2017-02-20 Impact factor: 8.082

3. Tests of Statistical Significance Made Sound.

Authors: Brian D Haig
Journal: Educ Psychol Meas Date: 2016-10-05 Impact factor: 2.821

4. Using Evidence from Randomised Controlled Trials in Economic Models: What Information is Relevant and is There a Minimum Amount of Sample Data Required to Make Decisions?

Authors: John W Stevens
Journal: Pharmacoeconomics Date: 2018-10 Impact factor: 4.981

Two cheers for P-values?

1. On Causal Inferences for Personalized Medicine: How Hidden Causal Assumptions Led to Erroneous Causal Claims About the D-Value.

2. For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates.

3. Tests of Statistical Significance Made Sound.

4. Using Evidence from Randomised Controlled Trials in Economic Models: What Information is Relevant and is There a Minimum Amount of Sample Data Required to Make Decisions?

5. Statistical significance and its critics: practicing damaging science, or damaging scientific practice?

6. The Heuristic Value of p in Inductive Statistical Inference.

7. Mastering the scientific peer review process: tips for young authors from a young senior editor.

8. Why most published research findings are false.

9. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.

10. Retract p < 0.005 and propose using JASP, instead.