|Title||More efficient estimators for case-cohort studies.|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||Kim, S, J Cai, and W Lu|
The case-cohort study design, used to reduce costs in large cohort studies, is a random sample of the entire cohort, named the subcohort, augmented with subjects having the disease of interest but not in the subcohort sample. When several diseases are of interest, several case-cohort studies may be conducted using the same subcohort, with each disease analyzed separately, ignoring the additional exposure measurements collected on subjects with the other diseases. This is not an efficient use of the data, and in this paper, we propose more efficient estimators. We consider both joint and separate analyses for the multiple diseases. We propose an estimating equation approach with a new weight function, and we establish the consistency and asymptotic normality of the resulting estimator. Simulation studies show that the proposed methods using all available information gain efficiency. We apply our proposed method to the data from the Busselton Health Study.
|Original Publication||More efficient estimators for case-cohort studies.|
|PubMed Central ID||PMC3950393|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 CA140632 / CA / NCI NIH HHS / United States
UL1 RR025747 / RR / NCRR NIH HHS / United States
More efficient estimators for case-cohort studies.