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From |
David Hoaglin <dchoaglin@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: which statistical analysis to use |

Date |
Wed, 18 Apr 2012 15:33:22 -0400 |

Deborah, By an interesting coincidence, the issue of Computational Statistics & Data Analysis that arrived today contains a paper on ranking data: Lee PH, Yu PLH. Mixtures of weighted distance-based models for ranking data with applications in political studies. Computational Statistics & Data Analysis 2012; 56:2486-2500. That paper is probably not directly relevant to the analysis that you are trying to do, but its list of references may be helpful in making contact with that literature. In particular, I noticed two books: Marden JI. Analyzing and Modeling Rank Data. Chapman and Hall, 1995. Fligner MA, Verducci JS (eds.). Probability Models and Statistical Analyses for Ranking Data. Springer-Verlag, 1993. I hope this information is useful. David Hoaglin On Tue, Apr 17, 2012 at 7:59 AM, Deborah Beckers <deborahbeckers@hotmail.com> wrote: > 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? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: which statistical analysis to use***From:*Deborah Beckers <deborahbeckers@hotmail.com>

**References**:**st: which statistical analysis to use***From:*Deborah Beckers <deborahbeckers@hotmail.com>

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