Variance estimation of a survival function for interval-censored survival data.
Interval-censored survival data often occur in medical studies, especially in clinical trials. In this case, many authors have considered estimation of a survival function. There is, however, relatively little discussion on estimating the variance of estimated survival functions. For right-censored data, a special case of interval-censored data, the most commonly used method for variance estimation is to use the Greenwood formula. In this paper we propose a generalization of the Greenwood formula for variance estimation of a survival function based on interval-censored data. Also a simple bootstrap approach is presented. The two methods are evaluated and compared using simulation studies and a real data set. The simulation results suggest that the methods work well.
Sun
J
J
Department of Statistics, University of Missouri-Columbia, 222 Math Sciences Building, Columbia, MO 65211, USA. tsun@stat.missouri.edu
D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000401:mortality / Q000628:therapy; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D016019:Survival Analysis