Patrick Mcelduff asked
> I have a dataset with repeat measures on 150 individuals.
> I want to
> fit a linear regression for each individual (to be used in a
> subsequent analysis). How can I save the slope coefficients for
> each of the 150 regressions?
Ulrich Kohler:
> Use -post- for this task. The following snippet may deal as
> a starting point.
> It assumes that you have an identifier-variable "ID" which
> serially numbers
> the 150 individuals. If you haven't such a variable create
> one with -egen,
> group- (or use an approach with -levels-).
>
> --------------------------------------------------
> post xyz id coef using myfile, replace
> forvalues i = 1/150 {
> regress depvar indepvar if id==`i'
> post xyz ('i') (_b[indepvar])
> }
> postclose xyz
> ----------------------------------------------------
>
> Th code stores the coefficients of indepvar and the
> identifier variable in the Stata-file "myfile.dta".
Roger Newson:
> Use the -parmest- package, downloadable from SSC, which
> creates an output
> data set with 1 observation per parameter and data on
> estimates, confidence
> intervals, P-values and other parameter attributes. My
> Stata Journal
> article (Newson, 2003) summarises some of the things you
> can do with
> -parmest- output data sets, and can be downloaded as a
> pre-publication
> draft from my website (see my signature), using either a
> browser or the Stata -net- command.
>
> References
>
> Newson R. Confidence intervals and p-values for delivery to
> the end user.
> The Stata Journal 2003; 3(3): 245-269.
Some more possibilities:
1. -statsby-. Like -post- and -parmest- this
produces a reduced dataset, or what has been
called a "resultsset".
2. -levels- etc.
e.g.
levels id, local(I)
gen slope = .
qui foreach i of local I {
regress ... if id == `i'
replace slope = -b[indepvar] if id == `i'
}
This produces a variable alongside
the others in your dataset.
Nick
[email protected]
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