of course you would have to include a postestimation command
test Adummy = Bdummy
after your regression...
On 4/27/05, Robert Duval <[email protected]> wrote:
> Hi Berk,
>
> Once I faced a similar problem in which I wanted to compare the mean
> of a variable y for two (unpaired) groups, say A and B, without
> imposing the iid assumption.
>
> My solution was to run a regression of y on dummies for A and B
> (noconstant) and allow the "robust cluster" options to take care of
> the non-iid errors.
>
> Since you don't exactly say what your variables A and B are, and
> whether you have individual data (vs. only means and sd's), it is hard
> to know if my suggestion would help...
>
> cheers,
> robert
>
>
> On 4/27/05, Nick Cox <[email protected]> wrote:
> > 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?
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
