This problem is discussed, among other places,
in Rupert Miller's book "Beyond ANOVA". As
you say, the issue is getting a more accurate P-value.
I think you can do that if you also have a serial
correlation, i.e. the dependence arises because
these values are from a time series. I am not aware
that the procedure is canned as a Stata program, but
it should yield to calculator-style manipulations.
Nick
[email protected]
Berk Sensoy
> Thanks for your answer, but I don't think it will work because ttest
> assumes that variables in each sample are iid.
> Essentially, because observations of each variable are correlated, I
> have fewer effective observations than actual observations, so ttests
> understate the standard error of the mean.
>
> Anyone know how to test mean(A)=mean(B) when cov(ai,aj) != 0 and
> cov(bi,bj) != 0?
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