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Likelihood Ratio-Based Confidence Intervals in Survival Analysis
S. A. Murphy
Journal of the American Statistical Association
Vol. 90, No. 432 (Dec., 1995), pp. 1399-1405
Stable URL: http://www.jstor.org/stable/2291531
Page Count: 7
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Confidence intervals for the survival function and the cumulative hazard function are considered. These confidence intervals are based on an inversion of the likelihood ratio statistic. To do this, two extensions of the likelihood, each of which yields meaningful likelihood ratio hypothesis tests and subsequent confidence intervals, are considered. The choice of the best extension is difficult. In the failure time setting, the binomial extension is best in constructing confidence intervals concerning the survival function and the Poisson extension is best in constructing confidence intervals concerning the cumulative hazard. Simulations indicate that these two methods perform as well as or better than competitors based on the asymptotic normality of the estimator.
Journal of the American Statistical Association © 1995 American Statistical Association