Re: st: Equivalent to kruskal-wallis in clustered data

[alfonsa leiva <arfons74@yahoo.com>]

Thanks Roger, very usefull

--- On Thu, 11/8/12, Roger B. Newson <r.newson@imperial.ac.uk> wrote:

> From: Roger B. Newson <r.newson@imperial.ac.uk>
> Subject: Re: st: Equivalent to kruskal-wallis in clustered data
> To: statalist@hsphsun2.harvard.edu
> Date: Thursday, November 8, 2012, 1:06 PM
> Sorry, I made a very stupid mistake
> in my last email. The -somersd- 
> command should of course have been:
> 
> xi, noomit: somersd price i.rep78, transf(z) tdist
> cluster(firm)
> 
> so that the Somers' D parameters are estimated clustered by
> -firm-. We 
> then type, as before:
> 
> testparm _I*
> 
> to do the F-test of the hypothesis that all Somers' D
> parameters are 
> zero. The correct P-value is then 0.5973.
> 
> I hope this helps. Sorry for the confusing mistake.
> 
> Best wishes
> 
> Roger
> 
> Roger B Newson BSc MSc DPhil
> 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
> UNITED KINGDOM
> Tel: +44 (0)20 7352 8121 ext 3381
> Fax: +44 (0)20 7351 8322
> Email: r.newson@imperial.ac.uk
> Web page: http://www.imperial.ac.uk/nhli/r.newson/
> Departmental Web page:
> http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/
> 
> Opinions expressed are those of the author, not of the
> institution.
> 
> On 08/11/2012 12:00, Roger B. Newson wrote:
> > Yes, there is a clustered version of the Kruskal-Wallis
> test. It can be
> > done using the -somersd- package (downloadable from
> SSC) with -xi:- and
> > -testparm-.
> >
> > For instance, in the -auto- data, we might test
> independence of price
> > and repair record, assuming that we are sampling car
> firms from a
> > population of car firms, instead of sampling car models
> from a
> > population of car models. We set up the data by
> typing:
> >
> > sysuse auto, clear
> > gene firm=word(make,1)
> > tab firm, m
> >
> > This creates and tabulates  a new variable -firm-,
> indicating the firm
> > that makes each car model. We then do the analysis by
> typing:
> >
> > xi, noomit: somersd price i.rep78, transf(z) tdist
> >
> > which creates variables _Irep78_1 to _Irep78_5,
> indicating membership of
> > each of the 5 repair record groups, and calculates a
> Somers' D of each
> > of these indicators with respect to -price-, with
> confidence limits and
> > a P-value. These Somers' D parameters measure the
> association of each
> > repair record group (compared to all other repair
> record groups) with
> > the car's price in dollars.
> >
> > To do the test, we then type:
> >
> > testparm _I*
> >
> > which tests the hypothesis that all 5 of these Somers'
> D parameters are
> > zero, which implies that no repair group tends to be
> more or less
> > expensive than the rest (the hypothesis usually tested
> using a
> > Kruskall-Wallis test). We see that the P-value is
> 0.5618, so the null
> > hypothesis has not been decisively refuted.
> >
> > I hope this helps. Let me know if you have any further
> queries.
> >
> > Best wishes
> >
> > Roger
> >
> >
> > Roger B Newson BSc MSc DPhil
> > 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
> > UNITED KINGDOM
> > Tel: +44 (0)20 7352 8121 ext 3381
> > Fax: +44 (0)20 7351 8322
> > Email: r.newson@imperial.ac.uk
> > Web page: http://www.imperial.ac.uk/nhli/r.newson/
> > Departmental Web page:
> > http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/
> >
> >
> > Opinions expressed are those of the author, not of the
> institution.
> >
> > On 08/11/2012 10:11, alfonsa leiva wrote:
> >> Dear fellows
> >>
> >>
> >> Basically, GPs were randomized to 3 groups, in the
> bivariate analysis
> >> of effectiveness dependent variable are continuos
> and independet
> >> variable are groups 1,2 or 3 . There is any test
> equivalent to
> >> kruskall-wallis implemented in stata to test the
> study hypothesis
> >> adjusted for the lack of independency of the
> patients(clustered data
> >> by GPs)?
> >>
> >> Thanks in advance
> >>
> >>
> >>
> >> Alfonso Leiva
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