Open AccessicenReg: Regression Models for Interval Censored Data in R
Author(s) -
Clifford Anderson-Bergman
Publication year - 2017
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v081.i12
Subject(s) - estimator , statistics , imputation (statistics) , censored regression model , parametric statistics , regression , regression analysis , r package , mathematics , confidence interval , computer science , missing data
The non-parametric maximum likelihood estimator and semi-parametric regression models are fundamental estimators for interval censored data, along with standard fullyparametric 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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