Large-Scale Simultaneous Hypothesis Testing: The Choice of a Null Hypothesis
Abstract
Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously. This poses new difficulties for the statistician, but also opens new opportunities. In particular, it allows empirical estimation of an appropriate null hypothesis. The empirical null may be considerably more dispersed than the usual theoretical null distribution that would be used for any one case considered separately. An empirical Bayes analysis plan for this situation is developed, using a local version of the false discovery rate to examine the inference issues. Two genomics problems are used as examples to show the importance of correctly choosing the null hypothesis.
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- Authors
- Efron, B.
- Affiliations
- Stanford University (US)
- Corresponding author
- Efron, Bradley
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 2004-03
- Volume
- 99
- Issue
- 465
- Pages
- 96-104
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W1824047490
- Cited by
- 1,005
- References
- 1
- Citations by year
- 2026: 23 · 2025: 23 · 2024: 28 · 2023: 38 · 2022: 41 · 2021: 55 · 2020: 44 · 2019: 49 · 2018: 53 · 2017: 40 · 2016: 42 · 2015: 49 · 2014: 52 · 2013: 49 · 2012: 52
- FWCI
- 17.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- simultaneous hypothesis testing, empirical null distribution, empirical Bayes, local false discovery rate, high-dimensional hypothesis testing, genomics, image processing
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