Cluster analysis

E. J. Bynen

ISBN 10: 9401167842 / ISBN 13: 9789401167840

Editore: Springer, Springer Feb 2012, 2012

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This item is printed on demand - Print on Demand Titel. Neuware -During the last years the number of applications of cluster analysis in the social sciences has increased very rapidly. One of the reasons for this is the growing awareness that the assumption of homogeneity implicit in the application of such techniques as factor analysis and scaling is often violated by social science data; another is the increased interest in typolo gies and the construction of types. Dr. Bijnen has done an extremely useful job by putting together and evaluating attempts to arrive at better and more elegant techniques of cluster analysis from such diverse fields as the social sciences, biology and medicine. His presentation is very clear and concise, reflecting his intention not to write a 'cookery-book' but a text for scholars who need a reliable guide to pilot them through an extensive and widely scattered literature. Ph. C. Stouthard v Preface This book contains a survey of a number of techniques of clustering analysis. The merits and demerits of the procedures described are also discussed so that the research worker can make an informed choice be tween them. These techniques have been published in a very great number of journals which are not all easily accessible to the sociologist. This difficulty is com pounded because developments in the different disciplines have occurred almost entirely independently from each other; reference is made only sporadically in a piece of literature to the literature of other disciplines.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.

Codice articolo 9789401167840

Dati bibliografici

• Titolo: Cluster analysis
• Editore: Springer, Springer Feb 2012
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 9401167842
• ISBN 13: 9789401167840
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 229 L x 152 A x 8 P (millimetri) 229 millimetri di larghezza per 152 millimetri di altezza per 8 millimetri di profondità
• Peso: 198 grammi

Descrizione articolo

Riassunto

During the last years the number of applications of cluster analysis in the social sciences has increased very rapidly. One of the reasons for this is the growing awareness that the assumption of homogeneity implicit in the application of such techniques as factor analysis and scaling is often violated by social science data; another is the increased interest in typolo­ gies and the construction of types. Dr. Bijnen has done an extremely useful job by putting together and evaluating attempts to arrive at better and more elegant techniques of cluster analysis from such diverse fields as the social sciences, biology and medicine. His presentation is very clear and concise, reflecting his intention not to write a 'cookery-book' but a text for scholars who need a reliable guide to pilot them through an extensive and widely scattered literature. Ph. C. Stouthard v Preface This book contains a survey of a number of techniques of clustering analysis. The merits and demerits of the procedures described are also discussed so that the research worker can make an informed choice be­ tween them. These techniques have been published in a very great number of journals which are not all easily accessible to the sociologist. This difficulty is com­ pounded because developments in the different disciplines have occurred almost entirely independently from each other; reference is made only sporadically in a piece of literature to the literature of other disciplines.

Contenuti

1. Coefficients for Dehning The Degree of Similarity Between Objects.- 1.1. Introduction.- 1.2. The slope method of Du Mas.- 1.3. Cattell’s rc coefficient of pattern similarity.- 1.4. The D-coefficient.- 1.5. Cohen’s rc coefficient.- 1.6. Zubin’s index and its variants.- 1.6.1. Zubin’s index.- 1.6.2. The similarity index of Jaccard.- 1.6.3. The index of Rogers and Tanimoto.- 1.6.4. The G-index of Holley and Guilford.- 1.7. Hyvarinen’s coefficient.- 1.8. Smirnov’s coefficient.- 1.9. Goodall’s probabilistic similarity index.- 1.10. The distance measure of Williams, a.o..- 1.11. Conclusion.- 2. Methods Developed for Forming Clusters of Variables or Objects.- 2.1. Introduction.- 2.2. The matrix diagonal method.- 2.3. Methods for re-ordering a socio-matrix.- 2.3.1. Method of Beum and Brundage.- 2.3.2. Method of Coleman and MacRae.- 2.3.3. Method of Weiss.- 2.3.4. Method of Spilerman.- 2.4. Ramifying linkage analysis.- 2.5. The Gengerelli method.- 2.6. The approximate delimitation method.- 2.7. The B-coefficient of Holzinger and Harman.- 2.8. Iterative factor analysis.- 2.8.1. Wherry and Gaylord.- 2.8.2. Bass.- 2.8.3. Boon van Ostade.- 2.8.4. Conclusion.- 2.9. Sneath’s single linkage method.- 2.10. Serensen’s complete linkage method.- 2.11. Wishart’s method.- 2.12. The method of Michener and Sokal.- 2.13. Bridges’ method.- 2.14. The King method.- 2.15. Tryon’s cluster analysis.- 2.16. Conclusion.- Methods of Forming Clusters for Objects.- 3.1. Introduction.- 3.2. Thomdike’s method.- 3.3. The method of Sawrey, Keller and Conger.- 3.4. Ward’s method.- 3.5. Johnson’s hierarchical clustering scheme.- 3.6. Hierarchical representation of similarity matrices by trees.- 3.7. Cluster analysis according to Constantinescu.- 3.8. The method of Rogers and Tanimoto.- 3.9. Hyvarinen’s method.- 3.10. Bonner’s methods.- 3.10.1. On the basis of dichotomous variables.- 3.10.2. On the basis of variables on interval level.- 3.11. Boolean cluster search method.- 3.12. Gengerelli’s method.- 3.13. Mattson and Dammann’s method.- 3.14. The methods of Edwards, a.o..- 3.15. Conclusion.- 4. Methods for The Construction of Types Following Mcquitty.- 4.1. Introduction.- 4.2. Agreement analysis.- 4.3. Elementary linkage analysis.- 4.4. Elementary factor analysis.- 4.5. Hierarchical linkage analysis.- 4.6. Hierarchical syndrome analysis.- 4.7. Multiple rank order typal analysis.- 4.8. Classification by reciprocal pairs.- 4.9. Intercolumnar correlational analysis.- 4.10. Nominee-selectee analysis.- 4.11. Multiple agreement analysis.- 4.12. Criticism.- 5. Some Applications.- 5.1. Introduction.- 5.2. Thorndike’s method.- 5.3. The method of Sawrey, Keller and Conger.- 5.4. Ward’s method.- 5.5. McQuitty’s syndrome analysis.- 5.5.1. On election results.- 5.5.2. On latent class analysis data.- 5.6. Factor analysis.- 5.6.1. On the basis of correlation coefficients.- 5.6.2. On the basis of product sums.- 5.7. Comparison of the applications.- Conclusion.