<>
" so it is not telling you anything for which you need to estimate the
regression to find out."
So the point estimate is equal to ouput of other commands, bout how about
the CI?
*************
sysuse auto, clear
egen shead = std(headroom)
egen slength = std(length)
gen ia2 = shead*slength
egen sia2 = std(ia2)
/*compare */
reg mpg shead slength sia2
mean mpg
*************
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Kit Baum
Gesendet: Sonntag, 21. Juni 2009 15:59
An: [email protected]
Betreff: st: re: beta coefficients for interaction terms
<>
Lisa said
but it is important for my paper to show the value of the intercept,
and I get different values if I use either the standardized or the not
standardized dependent variable. If I have the null hypothesis that is
is equal to zero, do I have to use the standardized or not
standardized dependent variable? And coming back to my original
question: Why do I have to standardize the dependent variable?
and in fact if you do standardize both dep and indep vars as suggested
by an earlier post, the constant term is by definition zero. The
regression surface passes through the multivariate point of means, and
that is now (0,0,0,0,0).
When you do run the regression of *un*standardized dep var on
standardized regressors as you would now like to do, the constant term
is by construction the *un*conditional mean of the dep var:
. reg mpg shead slength sia2
Source | SS df MS Number of obs
= 74
-------------+------------------------------ F( 3, 70)
= 41.45
Model | 1563.44248 3 521.147494 Prob > F
= 0.0000
Residual | 880.016979 70 12.5716711 R-squared
= 0.6398
-------------+------------------------------ Adj R-squared
= 0.6244
Total | 2443.45946 73 33.4720474 Root MSE
= 3.5457
----------------------------------------------------------------------------
--
mpg | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------
+----------------------------------------------------------------
shead | -.1288064 .4934882 -0.26 0.795
-1.113038 .8554248
slength | -4.598606 .4846015 -9.49 0.000 -5.565113
-3.632098
sia2 | .4815198 .4260752 1.13 0.262 -.
3682604 1.3313
_cons | 21.2973 .4121741 51.67 0.000 20.47524
22.11935
----------------------------------------------------------------------------
--
.
end of do-file
. su mpg
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
mpg | 74 21.2973 5.785503 12 41
so it is not telling you anything for which you need to estimate the
regression to find out.
Kit Baum | Boston College Economics & DIW Berlin |
http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming
| http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata |
http://www.stata-press.com/books/imeus.html
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