Model-based likelihood ratio confidence intervals for survival functions

Document Type

Article

Publication Date

3-1-2012

Abstract

We introduce an adjusted likelihood ratio procedure for computing pointwise confidence intervals for survival functions from censored data. The test statistic, scaled by a ratio of two variance quantities, is shown to converge to a chi-squared distribution with one degree of freedom. The confidence intervals are seen to be a neighborhood of a semiparametric survival function estimator and are shown to have correct empirical coverage. Numerical studies also indicate that the proposed intervals have smaller estimated mean lengths in comparison to the ones that are produced as a neighborhood of the Kaplan-Meier estimator. We illustrate our method using a lung cancer data set. © 2011 Elsevier B.V.

Identifier

84855288768 (Scopus)

Publication Title

Statistics and Probability Letters

External Full Text Location

https://doi.org/10.1016/j.spl.2011.11.028

ISSN

01677152

First Page

626

Last Page

635

Issue

3

Volume

82

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