I think Lisa refer the section on standardized regression
cofficients of
that book, particularly to the second item on pg. 201 (English
edition).
That item states that one should not use b*s_x/s_y to create
standardized regression coefficients in the presence of interaction
terms. Based on Aiken/West 1991 (28-48) it is recommended that one
should standardize all variables that are part of the interaction in
advance. Hence, instead of coding
. sysuse auto, clear
. gen ia = head*length
. reg mpg head length ia, beta
you should code
. sysuse auto, clear
. egen shead = std(headroom)
. egen slength = std(length)
. egen smpg = std(mpg)
. gen ia2 = shead*slength
. egen sia2 = std(ia2)
. reg smpg shead slength sia2
The estimated coefficients of the constituent effects then show
how much
standard deviations the dependend variable change when the
independent
variable changes by one standard deviation and the other variable
of the
interaction term is at its mean.
Standardized regression coefficients are often used to find out
which of
the independent variables have the "largest" effect. I must admit
that I
often fail to understand why students want to know that. But leaving
that aside, if an effect is not constant over the range of another
variable (i.e. in the presence of an interaction term) the
question of
which independent variable have the largest effect seems pointless.
Many regards
Uli
Am Donnerstag, den 16.04.2009, 14:47 +0200 schrieb Martin Weiss:
<>
Your -gen- statement computes the interaction, but Stata would
treat
this
new variable as a covariate in its own right, w/o any connection to
other
covariates. A similar issue arises with quadratic terms of a
covariate
(http://www.stata.com/statalist/archive/2008-08/msg00307.html).
The book you mentioned has a subsection on the topic on pages
222-226,
and
the English version seems to be a straightforward translation of
it,
AFAIK
(http://www.stata-press.com/books/daus2.html, page 222). I
cannot find
the
stuff on the beta coefficient there, though. They do say that you
should
check for missings with -rowmiss- and that you should subtract
the mean
from
the variables before standardization. The latter is easily
accomplished
via
*****
sysuse auto, clear
*enter your vars to be standardized here
local stdvars "price weight trunk turn"
foreach var of local stdvars{
summ `var', mean
gen std`var'=`var'-r(mean)
}
*****
-egen, std()- would divide by the standard deviation in addition
to my
code...
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von
[email protected]
Gesendet: Donnerstag, 16. April 2009 14:07
An: [email protected]
Betreff: Re: st: AW: beta coefficients for interaction terms
How do I tell stata, that it is an inetraction term?
Here is what I did:
gen appearance_attention=apperance*attention
Is that telling stata, that the new variable is an interaction
term?
I am referring to the book "Datenanalyse mit Stata" by Kohler,
Kreuter
"Note that you can effect the standardization yourself via - egen,
std()-" What standardization do you mean? The z-standardization
or the
"normal" standardization for the beta coefficients, that I need for
the interpretation?
Best Lisa
Zitat von Martin Weiss <[email protected]>:
> <>
>
> Well, did you tell Stata in any way that a specific variable
is an
> "interaction term"? If not, Stata probably treats it as just
another
> covariate in your regression.
>
> BTW, which book are you referring to?
>
> Note that you can effect the standardization yourself via - egen,
> std()-
>
>
> HTH
> Martin
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von
> [email protected]
> Gesendet: Donnerstag, 16. April 2009 12:35
> An: [email protected]
> Betreff: st: beta coefficients for interaction terms
>
> Hi Statalist,
>
> I am working on a regression model with interactions between some
> variables. I read in a book, that I can't use the "normal"
> standardized beta coefficients for the interaction terms. They
said
> that the interpretation of the beta coefficients is not possible
> until
> you z-standardise the interaction variables before you do the
> regression.
>
> Does anyone know, if stata does the z-standardization for the
> interaction variables automatically, so I can use the normal
> standardized beta coefficients (shown in the stata output) for
the
> interpretation?
> I am using the 9.1 version of stata.
>
> I hope someone can help me.
>
> Best Lisa
>
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