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Activity Number:
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139
- Challenges and Advances in Statistical Inference for Problems with Nonregularity in the Era of Big Data
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Type:
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Invited
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Date/Time:
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Monday, July 31, 2017 : 10:30 AM to 12:20 PM
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Sponsor:
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WNAR
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Abstract #322220
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View Presentation
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Title:
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Marginal Screening in Case-Control Studies
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Author(s):
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Min Qian* and Ian McKeague
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Companies:
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Columbia University and Columbia University
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Keywords:
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Family-wise error rate ;
Genome-wide association studies ;
Multiple testing ;
Non-regular asymptotics
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Abstract:
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Screening high dimensional predictors from case-control studies poses a challenging multiple testing problem. The standard approach to this problem is to apply a Bonferroni correction to tests of association based on odds ratios, but that can result in a highly conservative test, especially when the tables are far from being independent. We propose a new and potentially more powerful approach that takes into account dependence between predictors along with addressing the inherent issue of post-selection inference.
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Authors who are presenting talks have a * after their name.
