Given interest in doing this, a minute detail
may be worth noting.
Fooling -adjust- by supplying a -by()- variable
which is constant (and, strictly, non-missing
for the observations of interest) is the trick
here which perhaps many have worked out for
themselves.
It doesn't really matter what the value of the -by()-
variable is, subject to those constraints. However,
gen all = " "
has the best cosmetic effect on the tabular
output of -adjust-. To spell this out,
-adjust- is happy that the -by()- argument
is a string variable, but not happy that
it is missing. Setting it to a space
produces a clean table as below.
. adjust we tu tr, by(all) gen(predict)
--------------------------------------------------------------------------------------------------
Dependent variable: mpg Command: regress
Created variable: predict
Covariates set to mean: weight = 3019.4595, turn = 39.648647, trunk = 13.756757
--------------------------------------------------------------------------------------------------
----------------------
all | xb
----------+-----------
| 21.2973
----------------------
Key: xb = Linear Prediction
This really is minute -- especially as in these circumstances
the -generate-d variable is what you want, not the table --
but some people might care, especially if they do this a lot.
Nick
[email protected]
John Reynolds
> Nick wrote:
> -------------------------------------
> You can use -adjust-: you just need to talk your way past the
> requirement
> for a -by()- option (unless that is part of what you want).
> Here is a silly example:
> . sysuse auto
> . regress mpg weight headroom turn trunk length displacement
> . gen all = 1
> . adjust headroom turn trunk length displacement, by(all) gen(predict)
> . scatter predict weight
> -------------------------------------
>
> Thanks for posting the command and example, I frequently have
> a need to plot
> predicted values as well. I took your mpg example and
> extended it to other
> scenarios that arise in my work, i.e., nonlinear and conditional
> associations. Also, I made the chart a line graph rather
> than a scatter
> plot as a personal preference.
>
> * 1. Linear effect of weight on mpg.
> sysuse auto
> gen all = 1
> regress mpg weight headroom turn trunk length displacement
> adjust headroom turn trunk length displacement, by(all) gen(predict)
> line predict weight, sort ytitle(Predicted MPG)
>
> * 2. Curvilinear effect of weight, modeled w/ a parabola
> gen weightsq=weight*weight
> regress mpg weight weightsq headroom turn trunk length displacement
> adjust headroom turn trunk length displacement, by(all) gen(predict2)
> line predict2 weight, sort ytitle(Predicted MPG)
>
> * 3. Effect of weight conditional on foreign vs. domestic mfr
> gen fweight=foreign*weight
> regress mpg weight foreign fweight headroom turn trunk length
> displacement
> adjust headroom turn trunk length displacement, by(all) gen(predict3)
> twoway (line predict3 weight if foreign==0, sort clpat(solid)) (line
> predict3 weight if foreign==1, sort clpat(dash)),
> ytitle(Predicted MPG)
> legend(order(1 "Domestic" 2 "Foreign"))
>
*
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