Symmetric tests and confidence intervals for survival probabilities and quantiles of censored survival data


Stuart Barber & Christopher Jennison.
We describe existing tests and introduce two new tests concerning the value of a survival function. These tests may be used to construct a confidence interval for the survival probability at a given time or for a quantile of the survival distribution. Simulation studies show that error rates can differ substantially from their nominal values, particularly at survival probabilities close to 0 or 1. We recommend our new 'constrained bootstrap' test for its good overall performance.

Some key words:
Beta distribution, bootstrap sampling, censoring, confidence interval, Greenwood's formula, hypothesis test, Kaplan-Meier estimate, likelihood ratio test, survival data.


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