Date: Tue, 27 Sep 2005 23:24:06 +0200
Reply-To: cristiano <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: cristiano <firstname.lastname@example.org>
Subject: Re: Cluster Analysis - best practices
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Thanks Aric for your suggestion!
2005/9/27, Aric Zion <Aric.Zion@asu.edu>:
> 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.
> -----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
> 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
> 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.
> Robert M. Schacht, Ph.D. <email@example.com>
> Pacific Basin Rehabilitation Research & Training Center
> 1268 Young Street, Suite #204
> Research Center, University of Hawaii
> Honolulu, HI 96814