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Controlling the false discovery rate in behavior genetics research
1Department of Statistics and O.R., The Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel. ybenja@post.tau.ac.il
Behavioural Brain Research
|October 30, 2001
Summary
Multiple comparisons in research can lead to false positives. Controlling the False Discovery Rate (FDR) offers a powerful alternative to traditional methods, reducing errors while increasing the ability to find real differences.
Area of Science:
- Statistics
- Biostatistics
- Neuroscience
Background:
- Multiple statistical tests increase the chance of false positives.
- Traditional methods like Bonferroni correction reduce statistical power.
- Neglecting multiplicity control leads to unreliable findings.
Purpose of the Study:
- Introduce the False Discovery Rate (FDR) as a statistical criterion.
- Demonstrate the limitations of traditional multiplicity control.
- Present FDR control procedures for enhanced statistical power.
Main Methods:
- Explanation of the FDR criterion.
- Development of two novel FDR control procedures.
- Application of FDR procedures to two case studies.
Main Results:
- FDR control effectively manages false discoveries.
- The proposed FDR procedures offer increased statistical power.
- Demonstrated utility in exploratory behavior and strain difference studies.
Conclusions:
- FDR provides a balanced approach to multiple comparisons.
- FDR control enhances the discovery of genuine effects.
- Recommended for researchers dealing with large-scale data analysis.
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