|Title||Analysis of multiple survival events in generalized case-cohort designs.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Kim, Soyoung, Donglin Zeng, and Jianwen Cai|
|Date Published||2018 Dec|
|Keywords||Atherosclerosis, Biometry, Case-Control Studies, Cohort Studies, Computer Simulation, Humans, Outcome Assessment, Health Care, Research Design, Survival Analysis|
Generalized case-cohort design has been proposed to assess the effects of exposures on survival outcomes when measuring exposures is expensive and events are not rare in the cohort. In such design, expensive exposure information is collected from both a (stratified) randomly selected subcohort and a subset of individuals with events. In this article, we consider extension of such design to study multiple types of survival events by selecting a proportion of cases for each type of event. We propose a general weighting scheme to analyze data. Furthermore, we examine the optimal choice of weights and show that this optimal weighting yields much improved efficiency gain both asymptotically and in simulation studies. Finally, we apply our proposed methods to data from the Atherosclerosis Risk in Communities study.
|Original Publication||Analysis of multiple survival events in generalized case-cohort designs.|
|PubMed Central ID||PMC6328348|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 ES021900 / ES / NIEHS NIH HHS / United States
R01 GM047845 / GM / NIGMS NIH HHS / United States
Analysis of multiple survival events in generalized case-cohort designs.