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the claim

The Benjamini and Hochberg approach is used to control the false discovery rate in statistical testing.

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SUPPORTED
the evidence backs this
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9 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that the Benjamini and Hochberg approach is used to control the false discovery rate in statistical testing?

Yes. The Benjamini and Hochberg procedure is a foundational statistical approach widely used to control the false discovery rate in multiple hypothesis testing.

Verdict: SUPPORTED · 9 sources for, 0 against · Last checked

The analysis

The claim is specific, empirical, and contestable in principle, but the retrieved scientific literature overwhelmingly supports the foundational role and ongoing application of the Benjamini and Hochberg approach for controlling the false discovery rate in statistical testing. Multiple foundational and contemporary papers utilize or discuss this procedure without any refuting evidence.

Evidence for · 9
1995
Benjamini and Hochberg (1995) originally proposed the sequential procedure to control the false discovery rate in multiple testing.
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Benjamini, Y. & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. doi.org. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x

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More for · 8
2020
Subsequent mathematical literature confirms the use of the false discovery rate procedure for statistical estimates.
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Palionnaya, S. & Shestakov, O. (2020). Asymptotic Properties of MSE Estimate for the False Discovery Rate Controlling Procedures in Multiple Hypothesis Testing. doi.org. https://doi.org/10.3390/math8111913

2024
Recent methodological literature explicitly references the Benjamini-Hochberg method as a standard tool for false discovery rate control in bioinformatics and statistics.
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Koner, S., Sarkar, N., & Laha, N. (2024). False discovery rate control: Moving beyond the Benjamini–Hochberg method. doi.org. https://doi.org/10.21203/rs.3.rs-3861673/v1

2026
Applied clinical research utilizes the Benjamini-Hochberg correction to control the false discovery rate in multi-group comparisons.
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D, G., A, T., Y, O., M, T., K, O., S, H., Y, M., Y, N., & M, M. (2026). Sexual Dysfunction and Lower Urinary Tract Dysfunction in Adults With Spina Bifida.. doi.org. https://doi.org/10.1111/iju.70635

2026
Environmental and observational studies apply the Benjamini-Hochberg procedure to adjust for multiple comparisons and control the false discovery rate.
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CS, V., RC, S., JF, d. S., IA, Q., ADS, M., DMDCE, C., AD, d. C., & AS, d. C. (2026). Evaluation of nuclear abnormalities in buccal mucosa cells of grazing cattle from pastures routinely treated with 2,4-D: an exploratory field study.. doi.org. https://doi.org/10.1007/s10661-026-15851-8

2026
Statistical methodology literature confirms the Benjamini-Hochberg procedure enables exact control of the false discovery rate.
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Y, L., E, D., & EJ, T. T. (2026). Finding distributions that differ, with false discovery rate control.. doi.org. https://doi.org/10.1093/biomet/asag025

2026
Neuroimaging and clinical studies regularly implement the Benjamini-Hochberg false discovery rate correction for multiple hypotheses.
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YE, S., A, P., S, Y., HE, E., E, B., & MS, S. (2026). Assessment of Cerebral Perfusion Asymmetry in Chronic Migraine Patients Using Intravoxel Incoherent Motion (IVIM)-Derived Pseudodiffusion Coefficient and Perfusion Fraction.. doi.org. https://doi.org/10.1002/nbm.70403

2026
Survey-based research utilizes the Benjamini-Hochberg procedure to control the false discovery rate across multiple exploratory comparisons.
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N, M., ER, B., MT, B., AS, K., R, Y., & JM, D. (2026). Weight-Related Beliefs and Patient-Directed Assumptions Among Preclinical Medical Students: An Item-Level Cross-Sectional Study. doi.org. https://doi.org/10.21203/rs.3.rs-10913760/v1

2026
Methodological guides recommend the Benjamini-Hochberg procedure as a default method for controlling the false discovery rate in distal outcome comparisons.
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DB, C. (2026). Distal outcomes in mixture modeling: A guide for pairwise comparisons, multiplicity control, and effect size reporting.. doi.org. https://doi.org/10.3758/s13428-026-03144-4

What does the evidence say?

The claim is specific, empirical, and contestable in principle, but the retrieved scientific literature overwhelmingly supports the foundational role and ongoing application of the Benjamini and Hochberg approach for controlling the false discovery rate in statistical testing. Multiple foundational and contemporary papers utilize or discuss this procedure without any refuting evidence.

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