Multi-stage Multiple Testing in the Era of Big Data and Cloud Computing
Abstract/Contents
- Abstract
- This article was inspired by lectures on multiple testing during the Big Data Conference in 2017 at CMSA, which the first author attended. Subsequent work led to a new approach to multi-stage multiple testing with applications to precision medicine and information technology in the Big Data and Multi-Cloud Era. An overview of this new approach and the key underlying ideas are provided.
Description
| Type of resource | text |
|---|---|
| Date created | November 4, 2021 |
| Date modified | November 5, 2021; December 5, 2022 |
| Publication date | November 5, 2021 |
Creators/Contributors
| Author | Lai, T.L. |
|---|---|
| Author | Liu, C. |
Subjects
| Subject | adaptive subgroup selection |
|---|---|
| Subject | group sequential designs |
| Subject | false discovery rate |
| Subject | familywise error rate |
| Genre | Text |
| Genre | Technical report |
Bibliographic information
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- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 4.0 International license (CC BY-NC-ND).
Preferred citation
- Preferred citation
- Lai, T. and Liu, C. (2021). Multi-stage Multiple Testing in the Era of Big Data and Cloud Computing. Department of Statistics Technical Report, Stanford University. Available from the Stanford Digital Repository at https://purl.stanford.edu/fv935sw6027
Collection
Statistics Department Technical Reports
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