icenReg: Regression Models for Interval Censored Data in R

被引：133
|
作者：
Anderson-Bergman, Clifford [1 ]
机构：
[1] Sandia Natl Labs, 7011 East Ave, Livermore, CA 94551 USA
来源：
JOURNAL OF STATISTICAL SOFTWARE | 2017年 / 81卷 / 12期
关键词：
interval censoring; accelerated failure time; proportional hazards; proportional odds; survival analysis; semi-parametric regression; non-parametric; PROPORTIONAL HAZARDS MODEL; NONPARAMETRIC-ESTIMATION; REDUCTION ALGORITHM; SURVIVAL MODELS; COMPUTATION; TESTS; FIT;
D O I：
10.18637/jss.v081.i12
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The non-parametric maximum likelihood estimator and semi-parametric regression models are fundamental estimators for interval censored data, along with standard fully-parametric regression models. The R package icenReg is introduced which contains fast, reliable algorithms for fitting these models. In addition, the package contains functions for imputation of the censored response variables and diagnostics of both regression effects and baseline distribution.
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页码：1 / 23
页数：23
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