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http://dx.doi.org/10.5351/KJAS.2012.25.5.707

Analyzing Clustered and Interval-Censored Data based on the Semiparametric Frailty Model  

Kim, Jin-Heum (Department of Applied Statistics, University of Suwon)
Kim, Youn-Nam (Clinical Trials Center Severance Hospital, Yonsei University Health System)
Publication Information
The Korean Journal of Applied Statistics / v.25, no.5, 2012 , pp. 707-718 More about this Journal
Abstract
We propose a semi-parametric model to analyze clustered and interval-censored data; in addition, we plugged-in a gamma frailty to the model to measure the association of members within the same cluster. We propose an estimation procedure based on EM algorithm. Simulation results showed that our estimation procedure may result in unbiased estimates. The standard error is smaller than expected and provides conservative results to estimate the coverage rate; however, this trend gradually disappeared as the number of members in the same cluster increased. In addition, our proposed method was illustrated with data taken from diabetic retinopathy studies to evaluate the effectiveness of laser photocoagulation in delaying or preventing the onset of blindness in individuals with diabetic retinopathy.
Keywords
Cox proportional hazards model; diabetic retinopathy studies; EM algorithm; frailty; interval censoring;
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