Hi,
 
Apologies, this is a stats question rather than an R question. I am trying to obtain reliable confidence limits for a phenotypic measure of QST. I'm calculating this as var(between populations) / (var(between popns)+2*var(within popns)) using nlme. I have tried bootstrapping, using diffferent methods to calculate the confidence intervals, however the type one errors of this approach are much greater than the alpha value of 0.05. My problem is that the number of populations I have is small (only 9) and I believe non-parametric bootstrapping performs poorly when estimating confidence limits for variances when the sample size is small. 
 
I wondered if anyone could suggest a method to correct for this or an approach other than bootstrapping that may yield reliable 95% confidence limits.
 
Many thanks,
Albert

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