Date: Tue, 27 Sep 2005 12:20:33 -1000
Reply-To: Bob Schacht <firstname.lastname@example.org>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Bob Schacht <email@example.com>
Subject: Re: Cluster Analysis - best practices
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At 11:19 AM 9/27/2005, cristiano wrote:
> do you know some paper where I can study the two approches?
The Polythetic agglomerative approach is what most programs use, in my
understanding. The Monothetic Subdivisive approach was pioneered(?) by
archeologist Robert Whallon, one of my teachers in grad school, who
published this method as follows:
Whallon, R.J., Jr.
1971 Type: A computer program for monothetic subdivisive classification.
University of Michigan Museum of Anthropology Technical Reports, 1. Ann Arbor.
1972 A new approach to pottery typology. American Antiquity 37:13-33
Whallon, R.J. & J.A. Brown, Eds.
1982 Essays on Archaeological Typology. Center for American Archaeology
Press, Evanston, Illinois.
I do not know if Whallon's methods have been reviewed in the statistical
literature. Unfortunately, my notes on his methods are in storage where I
can't get at them at the moment.
>2005/9/26, Bob Schacht <firstname.lastname@example.org>:
> > 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. <email@example.com>
> > Pacific Basin Rehabilitation Research & Training Center
> > 1268 Young Street, Suite #204
> > Research Center, University of Hawaii
> > Honolulu, HI 96814