Scaling Sociomatrices by Optimizing an Explicit Function: Correspondence Analysis of Binary Single Response Sociomatrices

Elliot Noma, D. Randall Smith

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Most methods for detecting structure in sociometric data involve either continuous spatial representations (e.g. MDS) or discrete hierarchical clustering analysis (e.g. CONCOR). By producing either spatial or clustering representations, these methods can highlight only some of the theoretically interesting group structures. Correspondence analysis, in contrast, can provide either spatial or clustering representations by assigning spatial coordinates to minimize the distance between individuals linked by a sociometric relationship. These scales may then be used to identify individuals' locations in a multidimensional representation of a group's structure or to reorder the rows and columns of a sociomatrix. Unlike many other methods of sociometric analysis, the numerical methods of correspondence analysis also are well understood and the optimization of the goodness-of-fit measure allows an evaluation of a particular model of group structure.

Original languageEnglish (US)
Pages (from-to)179-197
Number of pages19
JournalMultivariate Behavioral Research
Volume20
Issue number2
DOIs
StatePublished - Apr 1985

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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