Problems in high-dimensional mediation analysis

A mediation model seeks to identify and explain the mechanism of the direct and indirect effects of an exposure variable on an outcome variable, potentially mediated through several intervening variables. Statistical methods for mediation analysis are well-developed when the number of mediator variables is relatively small, but problems arise when the number of potential mediators exceeds the sample size. In this thesis, we address three problems in linear mediation models in the presence of high-dimensional mediators: estimating and inference for the indirect effect, power analysis for testing total effect, and estimation for the proportion of indirect effect.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Statistics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2021

Author dc:creator

• Zhou, Ruixuan

Contributors dc:contributor

• Zhao, Sihai Dave
• Chen, Xiaohui
• Li, Bo
• Qu, Annie

• Mediation Analysis
• High-dimensional Inference

Statement dc:rights

• Copyright 2021 Ruixuan Zhou

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/110660

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/110660