<>
Mandy,
try the code below to see how the solutions drift apart depending on the
percentage of missings that you introduce into the dataset. ( I know my
method is crude but illustrates the issue quite well). Set the thing to zero
to see that w/o missings the solutions coincide.
**********
clear*
set mem 400m
* enter the percentage of missings here
loc mis 0.01
u http://www.stata-press.com/data/imeus/traffic, clear
foreach var of varlist fatal beertax spircons unrate perincK {
replace `var'=. if runiform()<`mis'
}
qui ds, not(type string)
foreach var of varlist `r(varlist)'{
egen std`var'=std(`var')
}
xi: reg fatal beertax spircons unrate perincK i.state, beta
xtreg stdfatal stdbeertax stdspircons stdunrate stdperincK, fe
**********
HTH
Martin
_______________________
----- Original Message -----
From: "Mandy fu" <[email protected]>
To: <[email protected]>
Sent: Tuesday, March 03, 2009 8:22 PM
Subject: Re: st: AW: can I get standardized coefficients by standardize
variables first?
Dear Mr. Weiss,
Thanks for your reply! You are right---it should be -foreach-- rather
than --local--.
What I meant and actually used is using --foreach--to standardize all
the variables. I don't know why I wrote into -local--. Thanks!
I think I kind of find why the results given by the two methods are
different. It maybe is due to missing values. That is, for some groups
, there are missing values for some years and for some indepent
variables.
------------------------------
group year y var1 var2 var 3 var4
1 1981 1 1 missing 0 1
1 1982
1 1983
2 1981
2 1982
3 1981
3 1982
3 1983
------------------------------------
For the first observation, it's included in the way "standardizing
varaibles first" because y , var1,var3-4 included this observation.
But it's excluded from the way "using beta option directly".
So, can I underdtand that it is an alternative way to get beta
coefficents by standardized variables first and then use the regular
commands? This is the question I'm interested in.
Thanks a lot!
Mandy
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