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st: RE: Re: Non parametric repeated measures


From   "Newson, Roger B" <r.newson@imperial.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Re: Non parametric repeated measures
Date   Wed, 23 Aug 2006 13:35:30 +0100

A Stata 9 package that might help you here is -somersd-, downloadable
from SSC, which calculates confidence intervals for a wide family of
rank statistics, based on generalizations of Kendall's tau-a, Somers' D
and median differences, ratios and slopes. -somersd- has a -cluster()-
option for clustered data, which allows the possibility of repeated
measures data.

I hope this helps.

Best wishes

Roger


Roger Newson
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London 
Royal Brompton campus 
Room 33, Emmanuel Kaye Building 
1B Manresa Road
London SW3 6LR
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: r.newson@imperial.ac.uk 
www.imperial.ac.uk/nhli/r.newson/

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

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Paul Fenner
Sent: 23 August 2006 12:52
To: statalist@hsphsun2.harvard.edu
Subject: st: Re: Non parametric repeated measures

I have been asked to analyse the following experiment The outcome score
is a 
bacterial concentration scored 0 to 5. The data consists of an initial 
score, the score after treatment A and then the score after treatment B.

This is measured on 32 subjects. The whole experiment is then repeated
on a 
new set of 25 subjects but this time the sequence is initial, treatment
B, 
treatment A. The null hypothesis is that the removal of bacteria is 
independent of the treatment sequence.
I have searched the archive but I cannot find a non-parametric repeated 
measures anova. As an alternative I can show, using the the ranksum
test, 
that there there is no significant difference between the three measures
for 
the two experiments but I am not happy with this as it is ignoring the 
correlated nature of the data in each experiment.
I would be grateful for any advice on handling this data in Stata 9.2.
Thanks.
Paul

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