Abstract
It is now widely accepted that the techniques of null hypothesis significance testing (NHST) are routinely misused and misinterpreted by researchers seeking insight from data. There is, however, no consensus on acceptable alternatives, leaving researchers with little choice but to continue using NHST, regardless of its failings. I examine the potential for the Analysis of Credibility (AnCred) to resolve this impasse. Using real-life examples, I assess the ability of AnCred to provide researchers with a simple but robust framework for assessing study findings that goes beyond the standard dichotomy of statistical significance/nonsignificance. By extracting more insight from standard summary statistics while offering more protection against inferential fallacies, AnCred may encourage researchers to move toward the post p < 0.05 era.
| Original language | English |
|---|---|
| Pages (from-to) | 202-212 |
| Number of pages | 11 |
| Journal | American Statistician |
| Volume | 73 |
| Issue number | sup1 |
| Early online date | 20 Mar 2019 |
| DOIs | |
| Publication status | Published - 29 Mar 2019 |
Bibliographical note
© 2019 The Author. Published with license by Taylor & Francis Group, LLC.This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which
permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Keywords
- Analysis of credibility
- Bayesian inference
- Null hypothesis Significance testing
- p-Values