期刊
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
卷 32, 期 3, 页码 315-326出版社
CANADIAN JOURNAL STATISTICS
DOI: 10.2307/3315932
关键词
constant-sum condition; noninformative censoring; nonparametric likelihood inferences
In survival data analysis, the interval censoring problem has generally been treated via likelihood methods. Because this likelihood is complex, it is often assumed that the censoring mechanisms do not affect the mortality process. The authors specify conditions that ensure the validity of such a simplified likelihood. They prove the equivalence between different characterizations of noninformative censoring and define a constant-sum condition analogous to the one derived in the context of right censoring. They also prove that when the noninformative or constant-sum condition holds, the simplified likelihood can be used to obtain the nonparametric maximum likelihood estimator of the death time distribution function.
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