Premium
Interval censoring: Model characterizations for the validity of the simplified likelihood
Author(s) -
Oller Ramon,
Gomez Guadalupe,
Calle M. Luz
Publication year - 2004
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3315932
Subject(s) - censoring (clinical trials) , mathematics , statistics , maximum likelihood , likelihood function , estimator , nonparametric statistics , equivalence (formal languages) , econometrics , discrete mathematics
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.