On 17 Oct 2003 at 14:04, Enda Kelly wrote:

When you simulate the p-value, you are doing a binomiual simulation. 
Your estimated p-value is x/n with variance
p(1-p)/n <= 0.25/n
If you want three-place precision in p-values, for instance, you 
simply solve
sqrt(0.25/n) <= 0.001

Since you are only interested in high precision for small -p-values, 
it should be sufficient to solve
sqrt(0.05*0.95/n) <= 0.001

Kjetil Halvorsen


> Hi. Thanks to all those who contributed to the discussion on my original
> query attached below. Most of you requested more information, so I'll
> try and flesh out the problem here. The actual computation I'm
> attempting is a genetic linkage disequilibrium (LD) test, with the null
> hypothesis that no LD exists between two genetic sites (loci) i.e. the
> alleles (genes) at one locus appear randomly with respect to the second
> locus. An EM algorithm is used to get the likelihood of the observed
> data (L1). The likelihood under the assumption of no LD is also
> calculated (L0), and from this a statistic S=2*ln(L1/L0) is calculated. 
> For data with low genetic diversity and large sample sizes, S has a
> chi-square distribution, and the P-value is thereby obtained. For more
> complex cases the alleles at one locus were permuted 1000 times (or
> more), and for each permutation S was calculated and the P-value for the
> test was the proportion of replicates that produced values of S equal or
> greater than the original S. In both cases I bootstrapped the original
> data 1000 times to get the CIs.
> This was done for a number of pairs of loci. To illustrate what I meant
> by "narrow" and "enormous", here are some examples with the p-value, the
> median of the bootstrap values and the upper and lower limits of 95% CI:
> 
> Locus pair    P-value         Median          Lower           Upper
> 1             0.002414        0.002422        0.000055        0.037401
> 2             0.971621        0.512296        0.181935        0.850761
> 3             0.000000        0.000000        0.000000        0.000000
> 4             0.018936        0.016100        0.001082        0.193285
> 5             0.832001        0.505662        0.173286        0.857703
> 
> Judging by the comments on the relationship between p-values and
> confidence intervals, I have a suspicion that going through the
> computationally expensive process of bootstrapping is not actually
> teaching me anything new, but I would like to get some sort of estimate
> of error associated with the computed p-values. Some mention has been
> made of the variance being proportional to p(1-p) - is the constant of
> proportionality easy to compute? Presumably the number of permutations
> is a factor.
> Regards,
> Enda
> 
> > Hi. I have a query regarding whether it is logical to place a
> > confidence interval about a P-value. The computation involved uses a
> > permutation method to produce a P-value for a hypothesis test. In an
> > effort to check the reliability of this P-value I have been
> > bootstrapping the raw data to produce a confidence interval about this
> > P-value. Curiously, for significant P-values the CI is in general
> > quite narrow, whereas for non-significant values, I get enormous CIs.
> > This leads me to the suspicion that there is something flawed about
> > the process. Am I correct in my suspicions?
> 
> 
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