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Re: st: summary statistics


From   Donald Spady <dspady@ualberta.ca>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: summary statistics
Date   Tue, 2 Oct 2012 13:59:21 -0600

Lars
  Thanks for your comment. I was unaware of the preserve // restore option.  I tend not to use collapse and that is probably the reason.
  
Don
On 2012-10-02, at 5:39 AM, Lars Folkestad <lfolkestad@health.sdu.dk> wrote:

> Using preserv // restore prior and after the collapse code would preserve your data and not destroy it - As you say. 
> 
> I must ad i have not tried tabm or tab_chi but i definatly will.
> 
> Mvh
> Lars Folkestad
> 
> 
> Den 01/10/2012 kl. 19.05 skrev "Donald Spady" <dspady@ualberta.ca>:
> 
>> Thanks to both of you for your comments and alternative approaches.  I liked the original in that it does not destroy the data, as collapse would do, however, it is nice to know there are several possible ways of getting what I want.  Nick is also correct in that I am not overly fluent in Stata; I have used it for several years, and am comfortable in general, but only with the basics and what I use on a regular basis.
>> 
>> Don
>> 
>> On 2012-10-01, at 10:33 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>> 
>>> Actually, I pointed to _two_ user-written commands that do this.
>>> 
>>> In general, I agree with Clyde. The trade-off between doing it
>>> yourself from first principles and finding a suitable user-written
>>> command (or even an official one) is delicate, and always with a user.
>>> However, the success of Clyde's approach depends partly on his being
>>> an experienced user who is fluent in, and feels comfortable with, much
>>> of Stata.
>>> 
>>> With a structure this simple, a two-line solution is also competitive.
>>> 
>>> stack HSS*, into(HSS) clear
>>> tab _stack HSS
>>> 
>>> -- although that loses some detail on variable names and labels, and
>>> so does not qualify as a good solution by itself.
>>> 
>>> However, the full trade-off needs to take account of various awkward facts:
>>> 
>>> 1. You might want to do this repeatedly.
>>> 
>>> 2. You might (almost certainly will) want to go back to your original
>>> data structure.
>>> 
>>> 3. You might want to carry weights through the -reshape- too.
>>> 
>>> As said, I am in agreement, just spelling out some issues.
>>> 
>>> Nick
>>> 
>>> On Mon, Oct 1, 2012 at 5:14 PM, Clyde B Schechter
>>> <clyde.schechter@einstein.yu.edu> wrote:
>>>> Don Spady was looking for a command that would take variables HSS1-HSS18, each with a discrete 1 to 5 response set and create a table like:
>>>> 
>>>>              Col 1    Col2     Col 3    Col 4   Col5
>>>> HSS1        n1            n2            n3             n4           n5
>>>> HSS2        n1            n2            n3             n4           n5
>>>> HSS3
>>>> 
>>>> And Nick Cox pointed him to a user-written command that does this.
>>>> 
>>>> I would just add that this can also be easily done using a few built-in Stata commands:
>>>> 
>>>> (I assume there is another variable, called id, which identifies the observations.  If not, it can be generated first)
>>>> 
>>>> reshape long HSS, i(id) j(varnum)
>>>> collapse (count) Col = id, by(varnum HSS)
>>>> reshape wide Col, i(varnum) j(HSS)
>>>> gen variable= "HSS"+string(varnum)
>>>> list variable Col*, noobs clean
>>>> 
>>>> 
>>>> I suppose it is a matter of taste which way to do these things.  In general, if it is something I do repeatedly, I find the convenience of a single command (which I might write an ado file for myself) worthwhile.  But if it's a one-off, it's generally faster to write a few lines of code and also not later be bothered with trying to remember what some unfamiliar command name means.
>>> 
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>> 
>> Donald Spady
>> 
>> --
>> dspady@ualberta.ca
>> 
>> 
>> 
>> 
>> 
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> 

Donald Spady

--
dspady@ualberta.ca





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