Svend,
Thanks again for your suggestions.
You're right that I could create a set of -drop- statements to remove all
null records (where all reshaped variables are missing) so that -reshape-
would create the unbalanced data set I need. Despite my general aversion
to using SPSS, I took a look at their version of -reshape-, called
-restructure-. There is a handy option to drop all null records, which
easily creates unbalanced data sets. It would be nice if Stata's
-reshape- command had such an option. Given the likelihood of adding new
variables as the data analysis progresses, I will likely use SPSS to
reshape my data.
Mike Frone
****************************************************************
Michael R. Frone, Ph.D.
Senior Research Scientist
Research Institute on Addictions
State University of New York at Buffalo
1021 Main Street
Buffalo, New York 14203
Office: 716-887-2519
Fax: 716-887-2477
E-mail: [email protected]
Internet: http://www.ria.buffalo.edu/profiles/frone.html
****************************************************************
"Svend Juul" <[email protected]>
Sent by: [email protected]
09/12/2006 04:22 AM
Please respond to
[email protected]
To
<[email protected]>
cc
Subject
Re: st: using reshape
Mike Frone wrote:
I obtained data in this form:
respnum_ injnum finalwt2 gender ir1 ir2 ir3_ ir4_1_
354 1 16151.351 male yes 2 no no
354 2 16151.351 male yes 2 yes no
354 3 16151.351 male yes 2 . .
354 4 16151.351 male yes 2 . .
354 5 16151.351 male yes 2 . .
However, because this person only experienced 2 injuries, I wanted the
data in this form:
respnum_ injnum finalwt2 gender ir1 ir2 ir3_ ir4_1_
354 1 16151.351 male yes 2 no no
354 2 16151.351 male yes 2 yes no
How can I keep the number of records for a given respondent equal to the
number of injuries experienced?
----------------------------------------------------
I responded:
Assuming that ir3_ and ir4_1_ are 0/1 numeric variables, no/yes being
the
value labels:
drop if ir3==0 & ir4_1_==0
- but this was nonsense; it should have been:
drop if ir3 >= . & ir4_1_ >= .
-----------------------------------------------------
Mike responded to my nonsense suggestion
Thanks for your response. Unfortunately, as I noted, this was a partial
record for one case. There are many other injury characteristics.
Moreover, a respondent may have from 1 to 5 injury event, so the number
of
records within each value of respnum_ can range from 1 to 5. So a
simple
drop is unlikely to resolve the problem.
-----------------------------------------------------
I guess that you can identify "empty" observations, i.e. observations
not representing an injury, by one or more variables having a missing
value. That is the aim of
drop if ir3 >= . & ir4_1_ >= .
Svend
__________________________________________
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(Institute of Public Health, Department of Epidemiology)
Vennelyst Boulevard 6
DK-8000 Aarhus C, Denmark
Phone: +45 8942 6090
Home: +45 8693 7796
Email: [email protected]
__________________________________________
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