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st: RE: which statistical analysis to use


From   "Ganamotse, Gaofetoge N" <gngana@essex.ac.uk>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: which statistical analysis to use
Date   Wed, 18 Apr 2012 09:56:52 +0000

Dear Deborah,

I have has a similar problem with my data. You have not presented your sample data so I don't know if, like me you have a problem of multiple responses. If that's the I found this article helpful for restructuring my data.

http://www.stata-journal.com/sjpdf.html?articlenum=pr0008

Also you can read around Rao-Scott chi-square adjustments to understand the problem with multiple response sets. I then used chi-square from svyset which gives an adjusted chi-square (F-statistic). I don't know if that is correct though, so I stand to be corrected

Thanks

Gaofetoge Ntshadi Ganamotse

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Deborah Beckers
Sent: 17 April 2012 12:59
To: statalist@hsphsun2.harvard.edu
Subject: st: which statistical analysis to use

Hello everybody, 


I'm having a problem with statistical analysis for my thesis. I am using stata 11 for windows.
My data consists of a survey filled in by 360 companies, and the question I want to use is a question where they get a list of 27 employee skills, and they have to choose the 7 most important skills, by giving them a score from 1 to 7. The other skills (which they find less important) are not given any score (they are zero in my data). The data for that question thus looks somewhat as follows (example for 3 companies, one row per company:


My question is: what kind of statistical analysis should I do, and how, to find out whether certain skills are ranked as more (or less) important than others by the companies, and if this difference is significant?
I tried to do this with a chi-square test for goodness of fit, but i got the error: too many variables specified. 


Can somebody please help me?
Thank you! 		 	   		  
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