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

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Thu, 19 Apr 2012 08:04:55 -0400 |

Nick, If a substantial number of the 27 skills were scored as 0 by all companies, one could (as you suggested earlier) set those skills aside. That might simplify the analysis. (The analysis would be conditional, because a skill with an observed score of 0 could have a positive probability of receiving a positive score, but the impact seems small when all 300+ companies gave it a 0.) An look at which sets of skills received nonzero rankings should be the first step. The constraint is that an individual company can (assuming it can't give tied scores) assign only one 1, only one 2, etc. To analyze the data as measurements, we would need a question that allowed a company to assign any score it wished to a particular skill. One might, for example, ask, "On a scale of 0 to 100, how important is this skill to your company?" Research may have shown that such a question tends not to produce good, reproducible data; and it is probably more effort for the company than the actual ranking, leading to higher rates of nonresponse, etc. The data collection has to face many practical problems. David On Thu, Apr 19, 2012 at 7:27 AM, Nick Cox <njcoxstata@gmail.com> wrote: > I think I agree to all. The ranking literature I have seen by the > authors you quoted earlier contains some really cute methods for the > case in which all the ranks are distinct (no ties). Then the ranks are > permutations of the integers 1 up and group theory and goodness knows > what lead to some very smart analyses. Here we are at the opposite > end, in which tieing is massive. I wouldn't expect much from that > direction. > > As you say, there are constraints here, so there can only be so many > 1s, so many 2s and so forth. That constrains the companies, but it > doesn't constrain the skills except indirectly, as I understand it. * * 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/

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

**Re: st: which statistical analysis to use***From:*David Hoaglin <dchoaglin@gmail.com>

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

**Re: st: which statistical analysis to use***From:*Nick Cox <njcoxstata@gmail.com>

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

**Re: st: which statistical analysis to use***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: which statistical analysis to use***From:*David Hoaglin <dchoaglin@gmail.com>

**Re: st: which statistical analysis to use***From:*Nick Cox <njcoxstata@gmail.com>

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