Well, the root mean square is best not
described as an "average". It is evidently
a kind of average, but a more precise description
is easy enough.
After a model you can use -predict- to get at residuals
and then run -summarize- (and anything else
needed) to get whatever summary measures you want.
Essentially the same issue for -glm- is
addressed by -glmcorr- on SSC.
Apart from doing it by hand, most of the code
in -glmcorr- might be used for your problem.
However, a much bigger question is this: Why did the
writers of -svy: reg- not provide this? Perhaps
they were queasy about what summary measure(s)
are justifiable in a -svy:- context. I don't
know, but that's what you need to worry about.
Nick
[email protected]
Richard Forshee
> Steven, this measure is also called the root mean squared
> error (which is
> reported in the -reg- command but not in the -svy: reg-
> command), and it
> measures the average deviation of a predicted value from the
> actual observed
> value in the sample.
Steven Samuels
> I don't have access to this journal. My question: standard error of
> WHAT estimate?
Richard Forshee
> > A recent article in my field encourages reporting both the R-
> > squared and the
> > Standard Error of the Estimate (or Root MSE). (James S. Krueger
> > and Michael
> > S. Lewis-Beck. Goodness-of-Fit: R-Squared, SEE and 'Best
> > Practice'. The
> > Political Methodologist, vol. 15, no. 1, pp 2-4. 2007)
> >
> > When I run a svy: reg command, I do not see the SEE (or Root MSE)
> > reported.
> > I checked ereturn list, and I did not see anything that
> appeared to
> > be the
> > SEE. Is there a way calculate the SEE when running a svy: reg
> > command?
> > Maybe it could be derived using the predict , stdp postestimation
> > command?
> > Or is there a reason that SEE is not appropriate in the context of
> > a svy:
> > reg command?
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