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Re: st: editing


From   Donald Spady <dspady@ualberta.ca>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: editing
Date   Fri, 12 Jul 2013 09:39:10 -0600

Send it back.  Tell them to clean up their product.  I have had the same experience and one can spend hours and hours cleaning and checking and documenting.  Often, you doesn't know what the 'right' entry is, and before you analyze the data you have to have to find out. The only benefit of such a data set is that every student should have one of these as an exercise.  It is a great way to learn about checking for inconsistencies (logical and otherwise), and for learning how a data set can be damaged, so that they will not do so in the future.  

Don  
On 12 Jul , at 07:59, "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> wrote:

> In recent days there's been  a lot on automated editing.  I just got a large (for me) data set with 20,000 observations and 270 variables.  It's in rotten shape - the people who prepared the data made many errors such as giving codes that were impossible - a dichotomous variable had 7 redponse codes, etc.  Many string variables which were clearly the same name had multiple spellings, etc.  
> This to me is a failure of initial editing.  I will go through the data and note errors to some extent, but I am unwilling to take on the role of data editor and cleaner.  Since this is a pro bono task, someone must do more thinking.  I don't see how an automated editing procedure could help with the extremely large number of ways things can get screwed up...
> 
> 
> Peter A. Lachenbruch,
> Professor (retired)
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Donald Spady

--
dspady@ualberta.ca





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