IntCens: Nonparametric maximum likelihood estimation for a broad class of semiparametric regression models with general interval-censored data (R).

TitleIntCens: Nonparametric maximum likelihood estimation for a broad class of semiparametric regression models with general interval-censored data (R).
Publication TypeSoftware
Year of Publication2016
AuthorsBunn, Paul, Donglin Zeng, and Dan-Yu Lin
Abstract

Interval-censored data arise when the failure time of each study subject is only known to lie in an interval.
IntCens is an R software package that implements nonparametric maximum likelihood estimation (NPMLE)
for a broad class of semiparametric regression models with general interval-censored data. The current release
handles three types of failure time data:
• Univariate. Univariate failure time data described in Zeng, Mao and Lin (2016).
• Multiple Events. Failure times for multiple types of events.
• Clustered. Subjects are clustered, e.g. by family

Original PublicationIntCens: Nonparametric maximum likelihood estimation for a broad class of semiparametric regression models with general interval-censored data (R).
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