JSM 2005 - Toronto

Abstract #303754

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 495
Type: Contributed
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Social Statistics Section
Abstract - #303754
Title: Clustering Linkage Methods: Humor to a Statistician
Author(s): Wade Watkins*+ and Bruce Barrett
Companies: University of Alabama and University of Alabama
Address: 1225 David Drive, Pelham, AL, 35124, United States
Keywords: Cluster Analysis ; Dendrogram
Abstract:

Investigating the associations between objects is necessary for much applied research. A statistical methodology called cluster analysis measures the strength of association between objects and assigns the objects to groups based on similarity. For reasons of computational efficiency, current cluster analysis methodologies employ some form of a hierarchical algorithm requiring linkage methods. The statistical literature suggests many possible linkage methods to use; but they lead to a diverse set of solutions, leading the analyst to inquire which is best. However, creating linkage rules without a global objective has provided only a slightly different clustering answer with no purpose for obtaining that answer. Therefore, we demonstrate that no more linkage methods need to be defined until global objectives are established.

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