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Conditional equivalence testing: An alternative remedy for publication bias
Harlan Campbell1, Paul Gustafson1
1Department of Statistics, University of British Columbia, Vancouver, Canada.
Plos One
|April 14, 2018
Summary
We propose conditional equivalence testing (CET), a novel two-stage method addressing reproducibility and null result publication bias. This approach enhances scientific rigor and publication diversity.
Area of Science:
- Statistics
- Scientific Publishing
- Research Methodology
Background:
- Concerns regarding reproducibility in scientific research are increasing.
- Limited publication of null results contributes to publication bias.
- Standard null hypothesis significance testing (NHST) may not fully capture the nuances of scientific findings.
Purpose of the Study:
- To introduce and detail a novel publication policy incorporating conditional equivalence testing (CET).
- To explore the potential of CET in addressing reproducibility and the under-publication of null results.
- To provide a framework for scientific journals to reduce publication bias.
Main Methods:
- Implementation of a two-stage testing scheme: standard NHST followed conditionally by equivalence testing.
- Comparison of CET with existing Bayesian testing schemes.
- Development of guidelines for journal adoption of CET.
Main Results:
- Conditional equivalence testing (CET) offers a structured approach to evaluating research findings.
- CET demonstrates potential similarities with Bayesian methodologies.
- A clear pathway for journal implementation to mitigate publication bias is outlined.
Conclusions:
- CET provides a robust framework for enhancing scientific rigor and addressing publication bias.
- The adoption of CET by journals can lead to a more balanced and reproducible scientific literature.
- Further investigation into CET's practical application and impact is warranted.
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