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st: Re: Kendall's tau

From   Roger Newson <>
Subject   st: Re: Kendall's tau
Date   Thu, 13 Nov 2003 21:18:46 +0000

At 13:56 13/11/03 -0700, Clint Thompson wrote:
Greetings STATAlisters...
I have a question that isn't necessarily related to the syntax
of a command but rather, the appropriateness of the statistic.
As I understand Kendall's tau (otherwise known as Kendalls rank
correlation coefficient), it is most appropriate for ordered
contingency table data; that is, the two variables need to
assume some sort of sequential ordering.  My query is this:  if
one of my variables is ordered (normal-->moderate-->severe) and
the other is continuous (e.g. proportion of total caloric
intake from saturated fat), can I use Kendall's tau to
ascertain some degree of correlation??  Note that my dataset is
small so I am hesitant to employ a parametric test and I want
to know how much the two variables are correlated, not simply
the existence of an association/distribution equality (K-W
test).  I understand there is an issue of the SJ/STB that
addresses an issue similar to this, however, I do not have
access to the journal.
I think you are referring to my article (Newson, 2002). A pre-publication draft of this paper is available on my website at
which can be accessed either using a browser or using the Stata -net- command. You can also find, on this site, the -somersd- package, manuals for the -somersd- and -cendif- programs, and my UK Stata User Meeting presentation on the subject.

I hope this helps.



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

Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
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

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

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