Publication date: Feb 09, 2025
In recent years, the role of the p-value in applied research has been heavily scrutinized. Several new proposals have been put forward from a Bayesian viewpoint, including the analysis of credibility. By using the reverse Bayes theorem, and reasoning in terms of subverting the significance or the non-significance denoted by the p-value, this analysis provides the credibility, in a Bayesian sense, of an experimental result. We discuss a normalized indicator of credibility, namely , a variant of the index (Quatto et al. J. Biopharm. Stat. 32, 308-329, 2022). This can be used to assess the degree of credibility of experimental results and can also be compared with a fixed threshold. The index is extended to the case of one-sided hypotheses. A simulation study is conducted to empirically assess the behavior of the index . Two illustrative examples in the contexts of pharmacotherapy for COVID-19 and heart failure are presented. We then propose adopting the credibility index for meta-analyses, in which it can provide a suitable diagnostic value for modeling fixed and random effects.
Concepts | Keywords |
---|---|
Covid | Analysis of credibility |
Diagnostic | fixed-effect meta-analysis |
Failure | p-value |
Pharmacotherapy | random-effects meta-analysis |
reverse Bayes theorem |
Semantics
Type | Source | Name |
---|---|---|
disease | IDO | role |
disease | MESH | COVID-19 |
disease | MESH | heart failure |