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Activity Number:
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168
- Causal Inference
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2018 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract #330423
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Presentation
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Title:
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Nonparametric Mediation Analysis for Investigating the ROle of Microbiome Health
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Author(s):
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Kyle Carter* and Meng Lu and Lingling An
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Companies:
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University of Arizona and University of Arizona and University of Arizona
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Keywords:
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Metagenomics; Mediation Analysis; Integrative Analysis; High Dimensional; Information Theory
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Abstract:
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The human body maintains a close symbiotic relationship with the trillions of microorganisms that live upon and within it. Host gene expression in cooperation with the microbiome has been discovered to play a critical role in disease progression and response. In particular, changes in host gene expression may have a marked impact on the species diversity and abundance. Integration of gene expression and microbiome data can be achieved through mediation modeling. Structural equation modeling has been a popular causal framework, however it maintains strong assumptions about the distribution and association of parameters. We propose a nonparametric approach for selecting significant mediating species for models with high dimensional exposures and mediators. Simulation studies show improved performance compared to traditional mediation methods.
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Authors who are presenting talks have a * after their name.
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