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st: RE: Stata coding
"Nick Cox" <firstname.lastname@example.org>
st: RE: Stata coding
Mon, 13 Apr 2009 13:40:19 +0100
-egen- does not drop, meaning -drop-, observations that do not satisfy
an -if- condition; it merely ignores them.
In this example, I will for illustration take it that -if native == 1-
specifies that people are natives. You should of course substitute your
own correct syntax.
There are various ways to attack your first problem.
Here is one.
bysort country : egen float nativeattitudes = mean(attitudes) if native
bysort country (nativeattitudes) : replace nativeattitudes =
Here is another.
bysort country: egen nativeattitudes = mean(cond(native == 1, attitudes,
The answer to your second problem is yes, if I understand it correctly.
Just put two or more variables in your variable list fed to -by:-.
Rahsaan Maxwell, Ph.D.
Does anyone know if there is a fast way to code new variables in Stata
they equal the mean value of a subpopulation's score on particular other
For example, I am analyzing two main subpopulations: migrants and
Both of which are nested in countries and regions. I want to calculate
variable which captures the mean attitudes of natives in each
and then use that as an independent variable in a model predicting
I have used the code below to calculate mean attitudes of the entire
for country/region but I can't figure out how to make that calculation
only one subgroup yet still have the variable be valid for the whole
population. (If I add an 'if' clause at the end of the code it will
cases that don't apply).
by country, sort : egen float countryattitudes = mean(attitudes)
by region, sort : egen float regionattitudes = mean(attitudes)
I have been calculating subgroup means 'by hand' and then manually
for the countries. Which is slow. But I have almost 300 regions and
variables so I'm wondering if there is a faster way to do this?
And more generally, is it possible to create a new variable with
values per country/region for means across different groups. I.E. I
country1 to have one value for the mean attitude of natives and another
for the mean attitude of migrants. I want to do this in order to graph
migrant/native means across the countries and regions.
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