The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Microarrays, Empirical Bayes and the Two-Groups Model
Open accessAbstract
The classic frequentist theory of hypothesis testing developed by Neyman, Pearson and Fisher has a claim to being the twentieth century’s most influential piece of applied mathematics. Something new is happening in the twenty-first century: high-throughput devices, such as microarrays, routinely require simultaneous hypothesis tests for thousands of individual cases, not at all what the classical theory had in mind. In these situations empirical Bayes information begins to force itself upon frequentists and Bayesians alike. The two-groups model is a simple Bayesian construction that facilitates empirical Bayes analysis. This article concerns the interplay of Bayesian and frequentist ideas in the two-groups setting, with particular attention focused on Benjamini and Hochberg’s False Discovery Rate method. Topics include the choice and meaning of the null hypothesis in large-scale testing situations, power considerations, the limitations of permutation methods, significance testing for groups of cases (such as pathways in microarray studies), correlation effects, multiple confidence intervals and Bayesian competitors to the two-groups model.
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Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
False Discovery Rate–Adjusted Multiple Confidence Intervals for Selected Parameters
Benjamini, Y., & Yekutieli, D. (2005) · Journal of the American Statistical Association · doi:10.1198/016214504000001907 · Cited by 671
Generalizations of the familywise error rate
Lehmann, E. L., & Romano, J. P. (2005) · The Annals of Statistics · doi:10.1214/009053605000000084 · Cited by 320 · cited 2×
“In practice the permutation null usually approximates the theoretical null closely, as a long history of research on the permutation t-test demonstrated; see Section 5.9 of Lehmann and Romano (2005).”
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Metadata
- Authors
- Efron, B.
- Venue
- Statistical Science
- Publisher
- Institute of Mathematical Statistics
- Published
- 2008-02-01
- Volume
- 23
- Issue
- 1
- Pages
- 1-22
- ISSN
- 0883-4237 (ISSN-L)
- OpenAlex
- W2104976021
- Cited by
- 252
- References
- 5
- FWCI
- 5.83
- Type
- journal article
- Language
- en
- Open access
- bronze
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