On Consistency of the Self-Consistent Estimator of Survival Functions with Interval-Censored Data

The self-consistent estimator is commonly used for estimating a survival function with interval-censored data. Recent studies on interval censoring have focused on case 2 interval censoring, which does not involve exact observations, and double censoring, which involves only exact, right-censored or...

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Bibliographic Details
Published in:Scandinavian journal of statistics 2000-03, Vol.27 (1), p.35-44
Main Authors: Yu, Qiqing, Li, Linxiong, Wong, George Y. C.
Format: Article
Language:English
Subjects:
case 2 interval-censored data
Censored data
Censorship
Consistent estimators
Distribution functions
Estimators
exact observations
Exact sciences and technology
Linear inference, regression
Mathematical intervals
Mathematics
Maximum likelihood estimation
non-parametric maximum likelihood estimator
Nonparametric inference
Probability and statistics
Relapse
Reliability functions
Sciences and techniques of general use
self-consistent algorithm
Statistical estimation
Statistics
strong consistency
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Summary:The self-consistent estimator is commonly used for estimating a survival function with interval-censored data. Recent studies on interval censoring have focused on case 2 interval censoring, which does not involve exact observations, and double censoring, which involves only exact, right-censored or left-censored observations. In this paper, we consider an interval censoring scheme that involves exact, left-censored, right-censored and strictly interval-censored observations. Under this censoring scheme, we prove that the self-consistent estimator is strongly consistent under certain regularity conditions.
ISSN:0303-6898
1467-9469
DOI:10.1111/1467-9469.00176