Left truncation;
Interval censoring;
Likelihood estimator;
EFFICIENT ESTIMATION;
REGRESSION;
INFERENCE;
D O I:
10.1016/j.spl.2015.02.015
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
We consider conditional maximum likelihood estimator (cMLE) for the proportional hazards model with left-truncated and interval-censored data. We show that when the covariates are discrete the cMLE is the MLE, and under some regularity conditions the cMLE for the regression parameter is asymptotically normal and efficient. (C) 2015 Elsevier B.V. All rights reserved.
机构:
Hunter Coll, Dept Math & Stat, New York, NY USA
Hunter Coll, Dept Math & Stat, New York, NY 10065 USAHunter Coll, Dept Math & Stat, New York, NY USA
Pan, Chun
Cai, Bo
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机构:
Univ South Carolina, Dept Epidemiol & Biostat, Columbia, SC USAHunter Coll, Dept Math & Stat, New York, NY USA