A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data

Handle URI:
http://hdl.handle.net/10754/597353
Title:
A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data
Authors:
Gazioglu, Suzan; Wei, Jiawei; Jennings, Elizabeth M.; Carroll, Raymond J.
Abstract:
Primary analysis of case-control studies focuses on the relationship between disease (D) and a set of covariates of interest (Y, X). A secondary application of the case-control study, often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated due to the case-control sampling, and to avoid the biased sampling that arises from the design, it is typical to use the control data only. In this paper, we develop penalized regression spline methodology that uses all the data, and improves precision of estimation compared to using only the controls. A simulation study and an empirical example are used to illustrate the methodology.
Citation:
Gazioglu S, Wei J, Jennings EM, Carroll RJ (2013) A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data. Stat Biosci 5: 250–260. Available: http://dx.doi.org/10.1007/s12561-013-9094-9.
Publisher:
Springer Science + Business Media
Journal:
Statistics in Biosciences
KAUST Grant Number:
KUS-CI-016-04
Issue Date:
25-May-2013
DOI:
10.1007/s12561-013-9094-9
PubMed ID:
24707323
PubMed Central ID:
PMC3975606
Type:
Article
ISSN:
1867-1764; 1867-1772
Sponsors:
Jennings, Wei and Carroll’s research were supported by a grant from the National Cancer Institute (R37-CA057030). This publication is based in part on work supported by Award Number KUS-CI-016-04, made by King Abdullah University of Science and Technology (KAUST).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorGazioglu, Suzanen
dc.contributor.authorWei, Jiaweien
dc.contributor.authorJennings, Elizabeth M.en
dc.contributor.authorCarroll, Raymond J.en
dc.date.accessioned2016-02-25T12:31:22Zen
dc.date.available2016-02-25T12:31:22Zen
dc.date.issued2013-05-25en
dc.identifier.citationGazioglu S, Wei J, Jennings EM, Carroll RJ (2013) A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data. Stat Biosci 5: 250–260. Available: http://dx.doi.org/10.1007/s12561-013-9094-9.en
dc.identifier.issn1867-1764en
dc.identifier.issn1867-1772en
dc.identifier.pmid24707323en
dc.identifier.doi10.1007/s12561-013-9094-9en
dc.identifier.urihttp://hdl.handle.net/10754/597353en
dc.description.abstractPrimary analysis of case-control studies focuses on the relationship between disease (D) and a set of covariates of interest (Y, X). A secondary application of the case-control study, often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated due to the case-control sampling, and to avoid the biased sampling that arises from the design, it is typical to use the control data only. In this paper, we develop penalized regression spline methodology that uses all the data, and improves precision of estimation compared to using only the controls. A simulation study and an empirical example are used to illustrate the methodology.en
dc.description.sponsorshipJennings, Wei and Carroll’s research were supported by a grant from the National Cancer Institute (R37-CA057030). This publication is based in part on work supported by Award Number KUS-CI-016-04, made by King Abdullah University of Science and Technology (KAUST).en
dc.publisherSpringer Science + Business Mediaen
dc.subjectNonparametric Regressionen
dc.subjectB-splinesen
dc.subjectBiased Samplesen
dc.subjectHomoscedastic Regressionen
dc.subjectSecondary Dataen
dc.subjectSecondary Phenotypesen
dc.subjectTwo-stage Samplesen
dc.subjectRegression Splinesen
dc.titleA Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Dataen
dc.typeArticleen
dc.identifier.journalStatistics in Biosciencesen
dc.identifier.pmcidPMC3975606en
dc.contributor.institutionDepartment of Mathematical Sciences, Montana Tech of the University of Montana, Butte MT 59701.en
dc.contributor.institutionBeijing Novartis Pharma Co. Ltd., Integrated Information Sciences (IIS), Building 3 Floor 3, No. 3728 Jinke Road, Pudong New District, Shanghai, 201203, China.en
dc.contributor.institutionDepartment of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843-3143.en
kaust.grant.numberKUS-CI-016-04en

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