Files in this item

FilesDescriptionFormat

application/pdf

application/pdfZHOU-DISSERTATION-2021.pdf (1MB)Restricted to U of Illinois
(no description provided)PDF

Description

Title:Problems in high-dimensional mediation analysis
Author(s):Zhou, Ruixuan
Director of Research:Zhao, Sihai Dave
Doctoral Committee Chair(s):Zhao, Sihai Dave
Doctoral Committee Member(s):Chen, Xiaohui; Li, Bo; Qu, Annie
Department / Program:Statistics
Discipline:Statistics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Mediation Analysis
High-dimensional Inference
Abstract: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.
Issue Date:2021-04-16
Type:Thesis
URI:http://hdl.handle.net/2142/110660
Rights Information:Copyright 2021 Ruixuan Zhou
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05


This item appears in the following Collection(s)

Item Statistics