Dawit,
I don't understand your question. con==1 refers to one set of observations
in your dataset, and you will have values for the variable conhat (but not
wconhat) for this set of observations.
con==0 refers to a different set of observations in the dataset, and you
will have values for the variable wconhat (but not conhat) for this set of
observations.
What do you mean when you say you want compare the predicted values for two
completely different sets of observations? For any observation, you have a
value for either conhat, or wconhat, but not both.
--Mark
Quoting Dawit Lidia <[email protected]>:
> Dear Nick Cox,
>
> Thanks you for your response. I think I have to refine my question
> as
> follow. Can I do the following test on predicted values without
> adjusting
> the standard errors since observations are not independent within
> group
> (hhno)?
>
> ttest conhat = wconhat unequal
>
> where conhat and wconhat are predicted below.
> areg y1 x1 x2 if con ==1, absorb(hhno) cluster(hhno)
> predict conhat if con ==1, xbd
>
> areg y2 x1 x2 if con ==0, absorb(hhno) cluster(hhno)
> predict wconhat if con ==0, xbd
>
> Hope this will be clear. Many thanks for your help.
> Dawit
>
>
> >From: "Nick Cox" <[email protected]>
> >Reply-To: [email protected]
> >To: <[email protected]>
> >Subject: st: RE: test predicted values
> >Date: Sun, 16 Jan 2005 16:35:28 -0000
> >
> >It would seem more straightforward,
> >and more appropriate, to fit
> >
> >areg y1 x1 x2 con, absorb(hhno) cluster(hhno)
> >
> >which provides your test directly -- unless
> >I am missing some subtlety here.
> >
> >Nick
> >[email protected]
> >
> >Dawit Lidia
> >
> > > I am running the following types of regressions
> > >
> > > areg y1 x1 x2 if con ==1, absorb(hhno) cluster(hhno)
> > > predict conhat if con ==1, xbd
> > >
> > > areg y2 x1 x2 if con ==0, absorb(hhno) cluster(hhno)
> > > predict wconhat if con ==0, xbd
> > >
> > > y1 and y2 are dependent variables and xs are independent
> variables.
> > >
> > >
> > > I want to test if there is mean difference between the two
> > > predicted values
> > > uisng simple 'ttest'.
> > >
> > > My question is, do I need to correct standard errors(se) of
> > > the 'ttest'
> > > since the observed ys are not independent. If the answer is
> > > yes, would you
> > > please suggest me how i can correct it or any other
> > > altenative test that can
> > > adjust se.
> >
> >*
> >* For searches and help try:
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> >* http://www.stata.com/support/statalist/faq
> >* http://www.ats.ucla.edu/stat/stata/
>
> _________________________________________________________________
> MSN Hotmail http://www.hotmail.com Med markedets beste SPAM-filter.
> Gratis!
>
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>
Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3294
email: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
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