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Re: st: Regression with only higher level DV and IVs
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: Regression with only higher level DV and IVs
Date
Sat, 5 Jan 2013 12:23:33 +0000
You might get away with using -egen- to summarize by school and then
-egen-'s -tag()- function to select precisely one observation for each
school.
Here is a silly example to show technique:
. sysuse auto
(1978 Automobile Data)
. egen wt_mean = mean(weight), by(rep78)
. egen mpg_mean = mean(mpg), by(rep78)
. egen tag = tag(rep78)
. regress mpg_mean wt_mean if tag
Source | SS df MS Number of obs = 5
-------------+------------------------------ F( 1, 3) = 102.35
Model | 43.0722735 1 43.0722735 Prob > F = 0.0021
Residual | 1.26244615 3 .420815385 R-squared = 0.9715
-------------+------------------------------ Adj R-squared = 0.9620
Total | 44.3347197 4 11.0836799 Root MSE = .6487
------------------------------------------------------------------------------
mpg_mean | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
wt_mean | -.0078468 .0007756 -10.12 0.002 -.0103151 -.0053785
_cons | 45.1725 2.336426 19.33 0.000 37.73695 52.60805
------------------------------------------------------------------------------
But getting an appropriate structure need not be as painful as you
imply: see -collapse-, -contract-.
Nick
On Sat, Jan 5, 2013 at 11:59 AM, Stephen Cranney <[email protected]> wrote:
> I have a dataset with my observations being individual students who
> are then nested within schools. I am trying to do a regression of
> school-level dependent variables on school-level indicators. Is there
> a quick and easy way to do this without resorting to painful data
> shaping or tricking the multilevel modelling commands into doing it?
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