Causal Inference: Additive Hazard Model for Mediation Analysis with Measurement Error and Marginal Structural Models

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atmire.migration.oldid5916
dc.contributor.advisorChen, Gemai
dc.contributor.advisorYan, Ying
dc.contributor.authorShen, Lingzhu
dc.contributor.committeememberLu, Xuewen
dc.contributor.committeememberde Leon, Alexander
dc.date.accessioned2017-09-08T15:35:47Z
dc.date.available2017-09-08T15:35:47Z
dc.date.issued2017
dc.date.submitted2017en
dc.description.abstractIn epidemiologic and social science studies, researchers are often interested in understanding the causal effect from an exposure variable to an outcome variable. In this thesis, we develop two different models and methods to conduct causal inference: (1). causal mediation analysis under the additive hazards model with exposure-mediator interaction; (2). marginal structural additive hazards model. The existing literature requires accurate measurements of the mediator and the confounders, which could be infeasible in biomedical studies. Furthermore, the current identification results of causal effects under the additive hazards model do not allow for exposure-mediator interaction. In this thesis, we derive identification results of causal effects under the additive hazards model with exposure-mediator interaction. Furthermore, we propose consistent measurement error correction methods in the absence/presence of exposure-mediator interaction. In the second part of the thesis, we propose a marginal structural additive hazards model. We develop an estimation method for the marginal structural additive hazards model and apply the simulation-extrapolation (SIMEX) method to correct for the bias resulting from measurement error.en_US
dc.identifier.citationShen, L. (2017). Causal Inference: Additive Hazard Model for Mediation Analysis with Measurement Error and Marginal Structural Models (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25229en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/25229
dc.identifier.urihttp://hdl.handle.net/11023/4084
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectStatistics
dc.subject.otherStatistics
dc.titleCausal Inference: Additive Hazard Model for Mediation Analysis with Measurement Error and Marginal Structural Models
dc.typemaster thesis
thesis.degree.disciplineMathematics and Statistics
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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