Title	On heteroscedastic covariate measurement error in Cox regression
Creator	Huang, Yijian
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2016-08-16T09:29
Description	Many survival studies have error-contaminated covariates, which may lack a gold standard of measurement. Furthermore, the error distribution can depend on the true covariates but the dependence structure is typically diﬃcult to quantify; heteroscedasticity is a common manifestation. In this talk, we suggest an additive measurement error model in this circumstance, and develop a functional modeling method for Cox regression when an instrumental variable is available. The estimated regression coeﬃcients are consistent and asymptotically normal. Preliminary numerical studies, including simulations, will be provided.
Extent	40 minutes
Subject	Mathematics; Statistics; Probability theory and stochastic processes
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Emory University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2017-02-14
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0342785
URI	http://hdl.handle.net/2429/60589
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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