Model-based likelihood ratio confidence intervals for survival functions

Sundarraman Subramanian

Statistics & Probability Letters, 2012, vol. 82, issue 3, 626-635

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.

Keywords: Gaussian process; Lagrange multiplier; Maximum likelihood estimate; Misspecified model; Semiparametric random censorship model (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.spl.2011.11.028

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