I am using the R package
boot to bootstrap Harrel's C Index with different Cox models. My sample consists of about 700 cases with 90 events.
> boot.ci(boots[], type="bca") BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS Based on 10000 bootstrap replicates CALL : boot.ci(boot.out = boots[], type = "bca") Intervals : Level BCa 95% ( 0.7354, 0.7376 ) Calculations and Intervals on Original Scale Warning : BCa Intervals used Extreme Quantiles Some BCa intervals may be unstable
I understand that this warning is common when the number of replications is too low, but thought that 10000 would suffice. Can I expect to not get this kind of problem when I further raise the number of replications, or is something different wrong that more replications won't fix?