Date: Tue, 27 Sep 2005 23:27:09 +0200
Reply-To: cristiano <rivoli2@gmail.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: cristiano <rivoli2@gmail.com>
Subject: Re: Cluster Analysis - best practices
In-Reply-To: <S98544AbVIZXZL/20050926232518Z+14326@avas-mr02.fibertel.com.ar>
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Thanks Hector this literature is for adv-user I think?
2005/9/27, Hector Maletta <hmaletta@fibertel.com.ar>:
> A good introduction is Brian Everitt, Cluster Analysis (Arnold, London and
> Halsted Press, New York).
> At a higher level of sophistication, K.Jajuga, A. Sokolowski and H.-H. Bock,
> editors, Classification, Clustering and Data Analysis (Springer).
> About using SPSS clustering procedures, you better follow Marija Norusis'
> advice.
>
> Hector
>
> > -----Original Message-----
> > From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU]
> > On Behalf Of Aric Zion
> > Sent: Monday, September 26, 2005 8:21 PM
> > To: SPSSX-L@LISTSERV.UGA.EDU
> > Subject: Re: Cluster Analysis - best practices
> >
> > A clear overview is provided by H. Charles Romesburg's
> > "Cluster Analysis for Researchers", (2004) Lulu Press. While
> > this doesn't give guidance on how to specifically run Cluster
> > Analysis in SPSS, it does offer an very clear view of how
> > cluster analysis operates.
> >
> > Aric
> >
> >
> > -----Original Message-----
> > From: SPSSX(r) Discussion on behalf of Bob Schacht
> > Sent: Mon 9/26/2005 1:22 PM
> > To: SPSSX-L@LISTSERV.UGA.EDU
> > Cc:
> > Subject: Re: Cluster Analysis - best practices
> >
> >
> >
> > At 04:32 AM 9/26/2005, cristiano wrote:
> > >Dear listers,
> > > I'm a statistician but I'm looking for some
> > books/resources/example for
> > >using Cluster Analysis with SPSS: i'd like to know
> > the models and methods
> > >behind this analysis.
> > > In your experience, could you suggest to me some stuff?
> > > Thanks in advance
> > > Cristiano
> >
> > Cristiano,
> > As a prelude to your reading, let me comment in
> > general. Cluster analyses
> > fall into two approaches: One is polythetic
> > agglomerative in nature, the
> > other monothetic subdivisive.
> >
> > Polythetic agglomerative methods start with every
> > case as an individual,
> > and proceed to cluster by combining cases that most
> > closely resemble each
> > other. In each step of the analysis, the similarity
> > between remaining cases
> > and clusters is measured, and those most closely
> > resembling each other are
> > combined. This proceeds by steps as far as one wants
> > to go, based on
> > measures of cohesion or similarity.
> >
> > Monothetic subdivisive methods, on the other hand,
> > start with all cases
> > combined into one supergroup. The procedure in this
> > case is how to
> > subdivide the supergroup in to two groups in a way
> > that maximizes the
> > *difference* between the two groups. I'm not clear on
> > how this procedure
> > works, but it may begin with variables with the
> > highest degree of
> > variability, and splitting the cases at the mean.
> > Again, the process
> > proceeds stepwise until some threshold criterion is reached.
> >
> > You may have some a priori reason for preferring one
> > approach over the
> > other. Descriptions of the methods may not identify
> > themselves clearly with
> > these alternatives, so this overview might prove helpful.
> >
> > Bob
> >
> >
> > Robert M. Schacht, Ph.D. <schacht@hawaii.edu>
> > Pacific Basin Rehabilitation Research & Training Center
> > 1268 Young Street, Suite #204
> > Research Center, University of Hawaii
> > Honolulu, HI 96814
> >
> >
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