Graduate Thesis Or Dissertation
 

Asymptotic Uncertainty of False Discovery Proportion

Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3j333935d

Descriptions

Attribute NameValues
Creator
Abstract
  • Multiple hypothesis testing has been a popular topic in statistical research. Although vast works have been done, controlling the false discoveries remains a challenging task when the corresponding test statistics are dependent. Various methods have been proposed to estimate the false discovery proportion (FDP) under arbitrary dependence among the test statistics. One of the main ideas is to reduce arbitrary dependence to weak dependence and then to establish theoretically the strong consistency of the FDP and false discovery rate (FDR) under weak dependence. As a consequence, FDPs share the same asymptotic limit in the framework of weak dependence. We observe that the asymptotic variance of the FDP, however, may rely heavily on the dependence structure of the corresponding test statistics even when they are only weakly dependent; and it is of great practical value to quantify this variability, as it can serve as an indicator of the quality of the FDP estimate from the given data. As far as we are aware, the research on this respect is still limited in the literature. In this dissertation, we first derive the asymptotic expansion of FDP under mild regularity conditions for weakly dependent 𝑧-tests and then examine how the asymptotic variance of FDP varies under different dependence structures both theoretically and numerically. We also extend our theoretical results to the weakly dependent 𝑡-tests when the marginal variances of the test statistics need to be estimated. For both 𝑧-tests and 𝑡-tests, we propose practical methods to estimate the asymptotic variance of FDP and show their applicability to both synthetic and real multiple hypothesis testing problems. With the observations in this dissertation, we recommend that in a multiple testing performed by an FDP procedure, we may report both the mean and the variance estimates of FDP to enrich the study outcome.
License
Resource Type
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Rights Statement
Publisher
Peer Reviewed
Language
Embargo reason
  • Pending Publication
Embargo date range
  • 2022-03-26 to 2024-04-27

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details MeiMeng2022.pdf 2022-03-26 Public Download