TY - JOUR
T1 - Missing genetic information in case-control family data with general semi-parametric shared frailty model
AU - Graber-Naidich, Anna
AU - Gorfine, Malka
AU - Malone, Kathleen E.
AU - Hsu, Li
N1 - Funding Information: Acknowledgements This research is supported in part by a grant from the United States-Israel Binational Science Foundation and grants from the National Institutes of Health (R01 CA98858 and R01 AG14358). The authors thank all of the CARE Study Investigators and Staff for their leadership in designing and conducting the CARE Study which is supported by the National Institute of Child health and Human Development, with additional support from the National Cancer Institute, through contracts with Emory University (N01 HD3-3168), Fred Hutchinson Cancer Research Center (N01 HD2-3166), Karmanos Cancer Institute at Wayne State University (N01 HD 3-3174), University of Pennsylvania (N01 HD3-3176), University of Southern California (N01 HD 3-3175), and through an intro-agency agreement with the Centers for Disease Control and Prevention (Y01 HD7022).
PY - 2011/4
Y1 - 2011/4
N2 - Case-control family data are now widely used to examine the role of gene-environment interactions in the etiology of complex diseases. In these types of studies, exposure levels are obtained retrospectively and, frequently, information on most risk factors of interest is available on the probands but not on their relatives. In this work we consider correlated failure time data arising from population-based case-control family studies with missing genotypes of relatives. We present a new method for estimating the age-dependent marginalized hazard function. The proposed technique has two major advantages: (1) it is based on the pseudo full likelihood function rather than a pseudo composite likelihood function, which usually suffers from substantial efficiency loss; (2) the cumulative baseline hazard function is estimated using a two-stage estimator instead of an iterative process. We assess the performance of the proposed methodology with simulation studies, and illustrate its utility on a real data example.
AB - Case-control family data are now widely used to examine the role of gene-environment interactions in the etiology of complex diseases. In these types of studies, exposure levels are obtained retrospectively and, frequently, information on most risk factors of interest is available on the probands but not on their relatives. In this work we consider correlated failure time data arising from population-based case-control family studies with missing genotypes of relatives. We present a new method for estimating the age-dependent marginalized hazard function. The proposed technique has two major advantages: (1) it is based on the pseudo full likelihood function rather than a pseudo composite likelihood function, which usually suffers from substantial efficiency loss; (2) the cumulative baseline hazard function is estimated using a two-stage estimator instead of an iterative process. We assess the performance of the proposed methodology with simulation studies, and illustrate its utility on a real data example.
KW - Case-control family study
KW - Frailty model
KW - Missing genotypes
KW - Multivariate survival analysis
UR - http://www.scopus.com/inward/record.url?scp=79951949839&partnerID=8YFLogxK
U2 - 10.1007/s10985-010-9178-5
DO - 10.1007/s10985-010-9178-5
M3 - مقالة
C2 - 21153764
SN - 1380-7870
VL - 17
SP - 175
EP - 194
JO - Lifetime Data Analysis
JF - Lifetime Data Analysis
IS - 2
ER -