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Incorporating Correlations to Improve Multiple Testing Procedures Controlling False Discoveries
He, Li
He, Li
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Thesis/Dissertation
Date
2011
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Statistics
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http://dx.doi.org/10.34944/dspace/1389
Abstract
Multiple testing is playing an important role in analyzing data from modern scientific investigations. Some fundamentally important theoretical and methodological issues related to multiple testing still remain to be fully investigated. Often the correlation structure among test statistics involved in multiple testing is known a priori or it can be estimated from the data, yet this structure is not often properly taken into consideration while developing multiple testing procedures, even though not doing so might result in a less powerful method than one would like to have or lead to irrelevant or misleading conclusions. This dissertation focuses on research related to improving some of the commonly used multiple testing procedures by incorporating correlations into them. We propose several new results in this dissertation and present some ideas to carry out further research.
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