The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Some Results on False Discovery Rate in Stepwise multiple testing procedures
Open accessAbstract
The concept of false discovery rate (FDR) has been receiving increasing attention by researchers in multiple hypotheses testing. This paper produces some theoretical results on the FDR in the context of stepwise multiple testing procedures with dependent test statistics. It was recently shown by Benjamini and Yekutieli that the Benjamini–Hochberg step-up procedure controls the FDR when the test statistics are positively dependent in a certain sense. This paper strengthens their work by showing that the critical values of that procedure can be used in a much more general stepwise procedure under similar positive dependency. It is also shown that the FDR-controlling Benjamini–Liu step-down procedure originally developed for independent test statistics works even when the test statistics are positively dependent in some sense. An explicit expression for the FDR of a generalized stepwise procedure and an upper bound to the FDR of a step-down procedure are obtained in terms of probability distributions of ordered components of dependent random variables before establishing the main results.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
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
An improved Bonferroni procedure for multiple tests of significance
SIMES, R. J. (1986) · Biometrika · doi:10.1093/biomet/73.3.751 · Cited by 2,396
Karlin, S., & Rinott, Y. (1980) · Journal of Multivariate Analysis · doi:10.1016/0047-259x(80)90065-2 · Cited by 616
Adapting to unknown sparsity by controlling the false discovery rate
Abramovich, F., Benjamini, Y., Donoho, D. L., & Johnstone, I. M. (2006) · The Annals of Statistics · doi:10.1214/009053606000000074 · Cited by 455
The Simes Method for Multiple Hypothesis Testing with Positively Dependent Test Statistics
Sarkar, S. K., & Chang, C.-K. (1997) · Journal of the American Statistical Association · doi:10.1080/01621459.1997.10473682 · Cited by 336
Self-citationBenjamini, Y., & Liu, W. (1999) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(99)00040-3 · Cited by 242
Sarkar, S. K. (1998) · The Annals of Statistics · doi:10.1214/aos/1028144846 · Cited by 242
Self-citationWilliams, V. S. L., Jones, L. V., & Tukey, J. W. (1999) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986024001042 · Cited by 187
Williams, V. S. L., Jones, L. V., & Tukey, J. W. (1999) · Journal of Educational and Behavioral Statistics · doi:10.2307/1165261 · Cited by 186
Cited by
Adaptive linear step-up procedures that control the false discovery rate
Benjamini, Y., Krieger, A. M., & Yekutieli, D. (2006) · Biometrika · doi:10.1093/biomet/93.3.491 · Cited by 3,228
The positive false discovery rate: a Bayesian interpretation and the q-value
Storey, J. D. (2003) · The Annals of Statistics · doi:10.1214/aos/1074290335 · Cited by 2,204
… and the Cross-Section of Expected Returns
Harvey, C. R., Liu, Y., & Zhu, H. (2016) · Review of Financial Studies · doi:10.1093/rfs/hhv059 · Cited by 2,119
Escaping the Bonferroni iron claw in ecological studies
García, L. V. (2004) · Oikos · doi:10.1111/j.0030-1299.2004.13046.x · Cited by 560
Adapting to unknown sparsity by controlling the false discovery rate
Abramovich, F., Benjamini, Y., Donoho, D. L., & Johnstone, I. M. (2006) · The Annals of Statistics · doi:10.1214/009053606000000074 · Cited by 455
Metadata
- Authors
- Sarkar, S. K.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2002-02-01
- Volume
- 30
- Issue
- 1
- Pages
- 239-257
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W1635341812
- Cited by
- 268
- References
- 17
- FWCI
- 7.92
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Some Results on False Discovery Rate in Stepwise multiple testing procedures. https://app.cochat.ai/papers/10.1214/aos/1015362192
- The paper
- Sarkar, S. K. (2002). Some Results on False Discovery Rate in Stepwise multiple testing procedures. The Annals of Statistics. https://doi.org/10.1214/aos/1015362192
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
