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st: Re: Fisher's exact test in r x c contingency tables


From   Roger Newson <roger.newson@kcl.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Re: Fisher's exact test in r x c contingency tables
Date   Thu, 02 Jun 2005 18:58:38 +0100

At 17:16 02/06/2005, Mike Lacy wrote (amongst other useful stuff):

>What is your opinion? At the moment I rather think about applying
>tests that were designed for ordinal / ordinal relationships in r x c
>contingency tables (say, Goodman and Kruskal's gamma) than
>embarking on a potentially hazardous procedure.

If your variables are nominal, gamma would not make sense. However, if your variables are actually ordered but your data are sparse, you might want to bootstrap the Gamma value:

bootstrap r(gamma), reps(1000) : tabulate rep78 pricecat, gamma
Alternatives to Kruskal's gamma include Somers' D and Kendall's tau-a, which can be estimated with confidence intervals using the -somersd- package (downloadable from SSC). More about the case for confidence intervals for Somers' D and Kendall's tau-a can be found in Newson (2002), of which you can download a preprint from my website (see my signature below).

Hope this helps.

Roger


References

Newson R. 2002. Parameters behind "nonparametric" statistics: Kendall's tau, Somers' D and median differences. The Stata Journal 2(1): 45-64.


--
Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
Division of Asthma, Allergy and Lung Biology
King's College London

5th Floor, Capital House
42 Weston Street
London SE1 3QD
United Kingdom

Tel: 020 7848 6648 International +44 20 7848 6648
Fax: 020 7848 6620 International +44 20 7848 6620
or 020 7848 6605 International +44 20 7848 6605
Email: roger.newson@kcl.ac.uk
Website: http://phs.kcl.ac.uk/rogernewson/

Opinions expressed are those of the author, not the institution.

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