Confidence Intervals for Current Status Data
نویسندگان
چکیده
The likelihood ratio statistic for testing pointwise hypotheses about the survival time distribution in the current status model can be inverted to yield confidence intervals. One advantage of this procedure is that confidence intervals can be formed without estimating the unknown parameters that figure in the asymptotic distribution of the MLE of the distribution function. We discuss the likelihood ratio based confidence intervals for the distribution function and the quantile function and compare these intervals to several different intervals based on the MLE. The quantiles of the limiting distribution of the MLE are estimated using various methods including parametric fitting, kernel smoothing, and subsampling techniques. Comparisons are carried out both for simulated data and on a data set involving time to immunization against rubella. The comparisons indicate that the likelihood ratio based intervals are preferable from several perspectives.
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تاریخ انتشار 2002