TY - JOUR
T1 - Semiparametric estimation of marginal hazard function from case-control family studies
AU - Hsu, Li
AU - Chen, Lu
AU - Gorfine, Malka
AU - Malone, Kathleen
PY - 2004/12
Y1 - 2004/12
N2 - Estimating marginal hazard function from the correlated failure time data arising from case-control family studies is complicated by noncohort study design and risk heterogeneity due to unmeasured, shared risk factors among the family members. Accounting for both factors in this article, we propose a two-stage estimation procedure. At the first stage, we estimate the dependence parameter in the distribution for the risk heterogeneity without obtaining the marginal distribution first or simultaneously. Assuming that the dependence parameter is known, at the second stage we estimate the marginal hazard function by iterating between estimation of the risk heterogeneity (frailty) for each family and maximization of the partial likelihood function with an offset to account for the risk heterogeneity. We also propose an iterative procedure to improve the efficiency of the dependence parameter estimate. The simulation study shows that both methods perform well under finite sample sizes. We illustrate the method with a case-control family study of early onset breast cancer.
AB - Estimating marginal hazard function from the correlated failure time data arising from case-control family studies is complicated by noncohort study design and risk heterogeneity due to unmeasured, shared risk factors among the family members. Accounting for both factors in this article, we propose a two-stage estimation procedure. At the first stage, we estimate the dependence parameter in the distribution for the risk heterogeneity without obtaining the marginal distribution first or simultaneously. Assuming that the dependence parameter is known, at the second stage we estimate the marginal hazard function by iterating between estimation of the risk heterogeneity (frailty) for each family and maximization of the partial likelihood function with an offset to account for the risk heterogeneity. We also propose an iterative procedure to improve the efficiency of the dependence parameter estimate. The simulation study shows that both methods perform well under finite sample sizes. We illustrate the method with a case-control family study of early onset breast cancer.
KW - Case-control family data
KW - Correlated failure times
KW - Cross-ratio function
KW - Frailty model
KW - Hazard function
KW - Semiparametric
UR - http://www.scopus.com/inward/record.url?scp=10944227774&partnerID=8YFLogxK
U2 - 10.1111/j.0006-341x.2004.00249.x
DO - 10.1111/j.0006-341x.2004.00249.x
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 15606414
AN - SCOPUS:10944227774
SN - 0006-341X
VL - 60
SP - 936
EP - 944
JO - Biometrics
JF - Biometrics
IS - 4
ER -