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st: AW: RE: RE: AW: Creating single values from a nested data file


From   "Martin Weiss" <[email protected]>
To   <[email protected]>
Subject   st: AW: RE: RE: AW: Creating single values from a nested data file
Date   Wed, 16 Dec 2009 16:53:43 +0100

<> 

The missing case with Nick`s proposed solution would then be:


*************
clear*

inp byte(School Student Classize female) 
1	1		.	1
1	2		35	0
1	3		35	1
1	4		35	1
2	1		23	0
2	2		23	1
2	3		23	1
3	1		39	0
3	2		39	1
end

bys School (Classize): keep if _n==1

li, noo sepby(School)
*************

always hoping that there is no school with all missings - in which case
Russel probably wants the missing in his shrunken dataset, anyway...


HTH
Martin


-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Nick Cox
Gesendet: Mittwoch, 16. Dezember 2009 16:47
An: [email protected]
Betreff: st: RE: RE: AW: Creating single values from a nested data file

bysort school : keep if _n == 1 

does what you ask. 

Nick 
[email protected] 

Russel Wildeman

Thank you Martin

The data look like this 

School Student Classize female 
1	1		35	1
1	2		35	0
1	3		35	1
1	4		35	1
2	1		23	0
2	2		23	1
2	3		23	1
3	1		39	0
3	2		39	1


What I would like is for one of the school-level variables (classize) to
have only one observation per school. Hope I am a bit clearer.

Martin Weiss

Could be a case for -reshape- or -collapse-. For further help, you
should
post a meaningful excerpt of your data.

*From:* Russel Wildeman [mailto:[email protected]]

I have education survey data where the data are ordered by school and 
student and more pertinently the variable "school." The data are ordered

by the variable "school" and would give 0 0 0 0 1 1 1 1 etc. I have 
created appropriate school-level variables but the problem is that the 
values of the school-level variables are repeated for the same school, 
whereas I want only one record per school for some of the school-level 
variables. I tried various merging file schemes but none work. Any help 
is highly appreciated

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