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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Yoav Benjamini, Yosef Hochberg. Journal of the Royal Statistical Society Series B (Statistical Methodology), 1995-01-01
Topic: Risk, prevention and care in population studies
SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
Key findings
- It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate.
- This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
- Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power.
- A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial.
- The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
Why it matters
This paper presents a statistical method for controlling the false discovery rate in multiple testing problems. It is a methodological paper and does not directly address treating, curing, or preventing Alzheimer's disease.
Study details
- Evidence strengthLow
How this study scored 52/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of the Royal Statistical Society Series B (Statistical Methodology)) |
| Journal's citation record | 3 / 4 | Journal of the Royal Statistical Society Series B (Statistical Methodology): journal h-index 309 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 1995 — older than 20 years, still counted |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 7 / 7 | Cited 108,912 times (OpenAlex, 2026-10-10) |
| Citations per year | 5 / 5 | 3,300.4 citations a year over 33 year(s) since 1995 |
| Impact for its field and year | 5 / 6 | Cited 22.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 5 / 6 | Cited by 158 other studies in this library |
| Still being cited | 4 / 4 | Cited 24,174 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Yosef Hochberg: h-index 20 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Tel Aviv University: institution h-index 1,018 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 52 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Benjamini, Y., & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Statistical Methodology). https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Vancouver
Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Statistical Methodology). 1995. doi:10.1111/j.2517-6161.1995.tb02031.x.
BibTeX
@article{benjamini1995-3ac22d99,
author = {Benjamini, Yoav and Hochberg, Yosef},
title = {{Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing}},
journal = {Journal of the Royal Statistical Society Series B (Statistical Methodology)},
year = {1995},
doi = {10.1111/j.2517-6161.1995.tb02031.x},
url = {https://doi.org/10.1111/j.2517-6161.1995.tb02031.x}
}
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158 studies in the alzhub library list this one in their references. Showing the 8 highest-scoring.