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

Suzan Gazioglu, Jiawei Wei, Elizabeth M. Jennings, Raymond J. Carroll

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.
Original languageEnglish (US)
Pages (from-to)250-260
Number of pages11
JournalStatistics in Biosciences
Volume5
Issue number2
DOIs
StatePublished - May 25 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-CI-016-04
Acknowledgements: 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).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

Fingerprint Dive into the research topics of 'A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data'. Together they form a unique fingerprint.

Cite this