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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 07:18:05 -0400 |

Two quick points. Whether an off-the-shelf approach is available depends on the shelf. The literature on analysis of ranking data may have one. I'm sorry that I don't know, but I have not needed to analyze such data. The score is only ordinal outcome, not a real quantification. Beyond that, the ranking imposes a constraint. People are often willing to treat scores as measurements, but one can't finesse the ranking. David Hoaglin On Thu, Apr 19, 2012 at 7:03 AM, Nick Cox <njcoxstata@gmail.com> wrote: > A more general point is that you are not wedded to the scores as given > as long as there is a logic to how you treat or re-present them. For > example, if any skills are graded by 0 by everybody then I am not sure > you can do much with those except list them. As far as the other > skills are concerned, you could look at median and quartiles for > scores as well as mean scores. > > Some years ago in an internal discussion about workload weights for > different kinds of administrative responsibilities we first rejected > the idea of keeping diaries and quantifying time spent because that > would be a pain and reward the inefficient and penalise the efficient. > Then someone who had been reading about Fibonacci numbers said > something like this. Consider the first few Fibonacci numbers 1, 2, 3, > 5, 8, 13, 21. Let's have a system in which being Chair of Dept gets > 21, being in charge of a major area gets 13, and so on down to being > just a committee member gets 1. This was just plucked out of the air > as a piece of pure mathematics, but what was interesting was the quick > consensus was that would produce as good a quantification as any other > scheme, * * 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:*Nick Cox <njcoxstata@gmail.com>

**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>

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