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Variance estimation of a survival function for interval‐censored survival data
Author(s) -
Sun Jianguo
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.719
Subject(s) - statistics , survival function , variance (accounting) , generalization , survival analysis , estimation , confidence interval , interval (graph theory) , data set , interval estimation , function (biology) , mathematics , econometrics , computer science , mathematical analysis , accounting , management , combinatorics , evolutionary biology , economics , business , biology
Abstract 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. Copyright © 2001 John Wiley & Sons, Ltd.