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Causal mediation analysis with a partially missing mediator: exploring the effect of portable air purifier use during pregnancy on infant birth weight

Thesis type
(Thesis) M.Sc.
Date created
2021-08-26
Authors/Contributors
Author: Kang, Xi
Abstract
Mediation analysis examines the exposure-outcome association that acts through an intermediate variable. However, mediation analysis becomes challenging when data have missing values. Although methods exist to deal with missing data and mediation analysis independently, few studies have examined how to combine the approaches, specifically, how to pool the mediation analysis results across a series of imputed datasets and compute confidence intervals for target parameters. We propose a new technique that combines multiple imputation with maximum likelihood estimation. Using computer simulations, we compare the performance of our proposed approach with a traditional bootstrap approach. Our method performs well and is more computationally efficient than other resampling methods. We apply the new method to randomized trial data on the role of cadmium exposure in mediating the effects of an environmental health intervention on birth weight.
Document
Identifier
etd21608
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: McCandless, Lawrence
Language
English
Member of collection
Download file Size
input_data\22260\etd21608.pdf 1.26 MB

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