R Users,
We have updated the bpcp R package. It gives pointwise confidence intervals
for a survival distribution from right censored data. It is not based on
asymptotic approximations, so it may be used with any sample size, and with any
censoring distribution, as long as the censoring is non-informative.
Extensive simulations show that the bpcp confidence intervals appear to
guarantee coverage. When there is no censoring the method reduces to the exact
binomial intervals for the proportion of survivors at each time point.
Here are some important improvements:
1. The bpcp function now includes a midp option. This provides an
confidence interval that is closer to the nominal level "on average" over the
values of the parameter. It reduces to the mid-p confidence interval for a
binomial parameter when there is no censoring. Just like other mid-p
confidence intevals, for some values of the parameter it can be conservative,
and for some values it can be slightly anti-conservative. With extensive
censoring it can be very conservative, because (as with the original version)
no assumptions are made about the censoring distribution.
2. There is a new convention for the original bpcp exactly at the failure
times. This new convention ensures that the bpcp confidence intervals enclose
the Kaplan-Meier estimator.
3. There is a new option to enforce monotonicity. This is rarely needed,
but is used by default. All new simulations were done using this enforced
monotonicity.
4. An error was fixed in the method that only occurred when non-default
Delta values were used.
References:
Fay, MP, Brittain, EH (2016). Finite Sample Pointwise Confidence Intervals for
a Survival Distribution with Right-Censored Data. (to appear in Statistics in
Medicine, outlines midp modification, and provides many more simulations).
Fay, MP, Brittain, EH, and Proschan, MA (2013). Pointwise confidence intervals
for a survival distribution with small samples or heavy censoring.
Biostatistics. 14(4): 723-736.
Thanks,
Let me know if you have comments or want a preprint of the 2016 paper.
Mike
**************************************
Michael P. Fay, PhD
Mathematical Statistician
Biostatistics Research Branch/DCR/NIAID
5601 Fishers Lane, Room 4B53
Rockville, MD 20852
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