Sangam: A Confluence of Knowledge Streams

Variable Selection in Linear Mixed Model for Longitudinal Data

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dc.contributor Daowen Zhang, Committee Chair
dc.contributor Hao Helen Zhang, Committee Co-Chair
dc.contributor Marie Davidian, Committee Member
dc.contributor Dennis Boos, Committee Member
dc.creator Lan, Lan
dc.date 2010-04-02T18:38:08Z
dc.date 2010-04-02T18:38:08Z
dc.date 2006-08-17
dc.date.accessioned 2023-02-28T17:09:21Z
dc.date.available 2023-02-28T17:09:21Z
dc.identifier etd-05172006-211924
dc.identifier http://www.lib.ncsu.edu/resolver/1840.16/3842
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/265826
dc.description Fan and Li (JASA, 2001) proposed a family of variable selection procedures for certain parametric models via a nonconcave penalized likelihood approach, where significant variable selection and parameter estimation were done simultaneously, and the procedures were shown to have the oracle property. In this presentation, we extend the nonconcave penalized likelihood approach to linear mixed models for longitudinal data. Two new approaches are proposed to select significant covariates and estimate fixed effect parameters and variance components. In particular, we show the new approaches also possess the oracle property when the tuning parameter is chosen appropriately. We assess the performance of the proposed approaches via simulation and apply the procedures to data from the Multicenter AIDS Cohort Study.
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.
dc.subject Oracle property
dc.subject REML
dc.subject SCAD
dc.subject Variance components
dc.title Variable Selection in Linear Mixed Model for Longitudinal Data


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