Efficient Estimation of Clustered Current Status Data
Description
Current status data abounds
in the field of epidemiology and public health, where the only observable data for a subject is
the random inspection time and the event status at inspection. Motivated by such a current status
data from a periodontal study where data are inherently clustered,
we propose a unified methodology to analyze such complex data.