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Positive regression dependence on subsets for multivariate χ² random variables

Abstract Number:

2082 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

David Swanson (1)

Institutions:

(1) University of Texas MD Anderson Cancer Center, N/A

First Author:

David Swanson  
University of Texas MD Anderson Cancer Center

Presenting Author:

David Swanson  
University of Texas MD Anderson Cancer Center

Abstract Text:

We show a dependence condition, positive regression dependence on subsets, for multivariate X² random variables of a generalized Wishart type. This class of random variables occurs asymptotically on collections of test statistics arising from analysis of variance models. The dependence condition holds when the test statistics are generated under an arbitrary combination of null and alternative hypotheses, where the subset on which positive regression dependence holds is those test statistics realized under the null hypothesis. The condition is therefore sufficient for application of several multiple testing adjustment procedures including false discovery rate adjustment, and useful for high-dimensional settings when differences between multiple strata is of inferential interest.

Keywords:

multiple testing|positive regression dependence|false discovery rate|positive regression dependence on subsets| |

Sponsors:

IMS

Tracks:

Statistical Theory

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