American Statistical Association
Prentice (1986) introduced the case-cohort design to reduce the cost and necessary manpower in conducting large cohort studies that arise from processing all information, especially those requiring lab analyses and coding of subject-maintained diaries, into measurable covariates. In this design, all variables are measured on everyone in a randomly selected subcohort, but only on those experiencing the event of interest in the remaining non-subcohort. The goal in this presentation is the estimation of the group-specific survival functions when group membership is only partially known, as from case-cohort data. The nonparametric maximum likelihood estimator is derived along with some smoothed variations that require fewer assumptions. Consistency and asymptotic normality are considered. The small-sample behavior is investigated through simulation. A SEER prostate cancer data set is used to exemplify the methods.
|Date:||Wednesday, April 6, 2011|
|Time:||4:00 - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.