What you're doing makes no sense. Given p-values p_i, i=1...n, resulting
from hypothesis tests t_i, i=1...n, the q-value of p_i is the expected
proportion of false positives among all n tests if the significance level
of each test is α=p_i. Thus a q-value is only defined for an observed
p-value.
Jim,
Thanks for the reply. Yes I'm just playing around with the data at the
minute, but regardless of where the p values actually come from, I can't
seem to get a Q value that makes sense.
For example, in one case, I have an actual P value of 0.05. I have a list
of 1,000 randomised p values: ran
Hi Tom,
>From a quick scan of the docs, I think you are looking for qobj$pi0.
The vector qobj$qvalue seems to be the local false discovery rate for
each of your randomizations. Note that the manual implies that the p
values are those of multiple comparisons within a data set, not
randomizations of
On Mon, Apr 18, 2011 at 9:12 AM, Jim Silverton wrote:
> I am using storey's qvalue package but I keep on getting errors. Why is
> this?
>
>> qvalue(p, lambda=0.5)$pi0
> [1] "ERROR: p-values not in valid range."
> Error in qvalue(p, lambda = 0.5)$pi0 :
> $ operator is invalid for atomic vectors
S
I am using storey's qvalue package but I keep on getting errors. Why is
this?
> qvalue(p, lambda=0.5)$pi0
[1] "ERROR: p-values not in valid range."
Error in qvalue(p, lambda = 0.5)$pi0 :
$ operator is invalid for atomic vectors
--
Thanks,
Jim.
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