Patrick:
Welcome to the list. I would do this as follows: If you know
the lowest and highest number your id variable can take than
it is pretty simple to create a new file that will contain
all integers between these numbers. Than you can merge that
file with your dataset, which will create the new cases and
the _merge variable that is created by -merge- will tell you
which cases are added. See the example below.
HTH,
Maarten
*------------- begin example -----------
clear
set obs 30
gen mpg = _n + 11 /*I want to fill in all missing integers of mpg*/
list in 1/10
sort mpg
tempfile numbers /*this way the file `numbers' will only be available*/
save `numbers' /*during this do session, see: -help tempfile-*/
sysuse auto, clear
sort mpg
list mpg foreign in 1/10
merge mpg using `numbers'
tab _merge /*a case is added if _merge == 2, see: -help merge-*/
sort mpg
gen var1skippedvalue = _merge==2 /*this uses a logical expression
var1skipped value equals 1 if it is added and zero if it is not*/
list mpg foreign var1skippedvalue in 1/10
*----------- end example ---------------
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
-----Original Message-----
From: [email protected] [mailto:[email protected]]On Behalf Of Patrick Woodburn
Sent: woensdag 8 november 2006 10:44
To: [email protected]
Subject: st: Generating blank observations
Dear Statalist,
This is my first post to the list, and I hope it is clear enough. I
just have one question for now:
If I have an id variable called "var1" with a selection of unique values
in a given range of integers (eg the values 1, 3, 5, 6, 7, and 9), and I
want to create new observations which contain each missing value in that
range and are blank for all other variables (eg new observations
containing 2, 4, 8 and 10) and a new variable to flag that they have
been artificially generated, what do I do? Currently, all I can think
of is the rather roundabout way of doing it below, but I can't help but
think that surely there must be a more efficient method.
Best regards,
Patrick
*Code begins (dataset already open)
preserve
keep var1
drop if var1==.
bysort var1: assert _n==1
gen flag=0
gen id=1
reshape wide flag, i(id) j(var1)
forvalues i=1/10 {
cap gen flag`i'=1
}
reshape long flag, i(id) j(var1)
drop id
keep if flag==1
save var1skippedvalues
restore
append using var1skippedvalues
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