Citation
Zeng, Donglin; Lin, Dan-Yu; Avery, Christy L.; North, Kari E.; & Bray, Molly S. (2006). Efficient Semiparametric Estimation of Haplotype-Disease Associations in Case-Cohort and Nested Case-Control Studies. Biostatistics, 7(3), 486-502.Abstract
Estimating the effects of haplotypes on the age of onset of a disease is an important step toward the discovery of genes that influence complex human diseases. A haplotype is a specific sequence of nucleotides on the same chromosome of an individual and can only be measured indirectly through the genotype. We consider cohort studies which collect genotype data on a subset of cohort members through case-cohort or nested case-control sampling. We formulate the effects of haplotypes and possibly time-varying environmental variables on the age of onset through a broad class of semiparametric regression models. We construct appropriate nonparametric likelihoods, which involve both finite- and infinite-dimensional parameters. The corresponding nonparametric maximum likelihood estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Consistent variance-covariance estimators are provided, and efficient and reliable numerical algorithms are developed. Simulation studies demonstrate that the asymptotic approximations are accurate in practical settings and that case-cohort and nested case-control designs are highly cost-effective. An application to a major cardiovascular study is provided.URL
http://dx.doi.org/10.1093/biostatistics/kxj021Reference Type
Journal ArticleYear Published
2006Journal Title
BiostatisticsAuthor(s)
Zeng, DonglinLin, Dan-Yu
Avery, Christy L.
North, Kari E.
Bray, Molly S.