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Descripción

In a meta-analysis of articles employing clustering methods, we find that little attention is paid to remaining within-cluster heterogeneity and that average values are relatively high. We suggest addressing this potentially problematic "dark side" of cluster analysis by providing two coefficients as standard information in any cluster analysis findings: a goodness-of-fit measure and a measure which relates explained variation of analysed empirical data to explained variation of simulated random data. The second coefficient is referred to as the Index of Clustering Appropriateness (ICA). Finally, we develop a classification scheme depicting acceptable levels of remaining within-cluster heterogeneity. (authors' abstract)

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ePub-WU OAI Archive (Vienna Univ. of Econ. and B.A.)   ePub-WU OAI Archive (Vienna Univ. of Econ. and B.A.)  

Autor(es)

Franke, Nikolaus -  Reisinger, Heribert -  Hoppe, Daniel - 

Id.: 52867419

Idioma: inglés  - 

Versión: 1.0

Estado: Final

Tipo:  application/pdf - 

Palabras claveremaining within -  cluster heterogeneity / meta -  analysis / goodness -  of -  fit / cluster analysis - 

Tipo de recurso: Article  -  PeerReviewed  - 

Tipo de Interactividad: Expositivo

Nivel de Interactividad: muy bajo

Audiencia: Estudiante  -  Profesor  -  Autor  - 

Estructura: Atomic

Coste: no

Copyright: sí

Formatos:  application/pdf - 

Requerimientos técnicos:  Browser: Any - 

Relación: [References] http://dx.doi.org/10.1362/026725709X429755
[References] http://www.tandf.co.uk/journals/titles/0267257X.asp
[References] http://epub.wu.ac.at/3088/

Fecha de contribución: 18-oct-2016

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