Correspondence analysis of raw data

Michael Greenacre

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: Correspondence analysis has found extensive use in ecology, archeology, linguistics and the social sciences as a method for visualizing the patterns of association in a table of frequencies or nonnegative ratio-scale data. Inherent to the method is the expression of the data in each row or each column relative to their respective totals, and it is these sets of relative values (called profiles) that are visualized. This ‘relativization’ of the data makes perfect sense when the margins of the table represent samples from sub-populations of inherently different sizes. But in some ecological applications sampling is performed on equal areas or equal volumes so that the absolute levels of the observed occurrences may be of relevance, in which case relativization may not be required. In this paper we define the correspondence analysis of the raw ‘unrelativized’ data and discuss its properties, comparing this new method to regular correspondence analysis and to a related variant of non-symmetric correspondence analysis.

Keywords: Abundance data; biplot; Bray-Curtis dissimilarity; profile; size and shape; visualisation (search for similar items in EconPapers)
JEL-codes: C19 C88 (search for similar items in EconPapers)
Date: 2008-09, Revised 2009-07
New Economics Papers: this item is included in nep-ecm and nep-env
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (137)

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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:1112

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