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Re: st: conditional SE of y|X in glm
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: conditional SE of y|X in glm
Date
Tue, 24 Apr 2012 09:57:25 +0100
See -glmcorr- (SSC) for one approach here. That calculates an rmse
which appears similar, if not identical, to what you want. I like to
have such measures accessible for comparing -glm- results with those
of other models in which rmse appears naturally. Perhaps it is a
comfort blanket, but there you go.
Note that putting a constant into a variable is usually overkill as
di sqrt(e(dispers))
does the calculation. Use a scalar or local macro if you want to store
the value.
On Tue, Apr 24, 2012 at 9:31 AM, Marco Ventura <[email protected]> wrote:
> from a GLM estimate I want to retrieve the conditional standard error of y
> given the covariates. If I do
>
> gen sigma=sqrt(e(dispers))
>
> do I always get the right thing independently of any family and link?
> Should I correct it by sqrt(e(dispers)* (_N-1)/_N)?
> And do you think I should instead use the Pearson residuals such as
>
> gen sigma=sqrt(e(dispers_p))
>
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