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Correspondence analysis of raw data

Authors: Michael Greenacre;

Correspondence analysis of raw data

Abstract

Correspondence analysis has found extensive use in ecology, archaeology, 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 subpopulations 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, I 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 nonsymmetric correspondence analysis.

Country
Spain
Related Organizations
Keywords

profile, size and shape, Ecology, Population Dynamics, Models, Biological, Abundance data, biplot, Bray-Curtis dissimilarity, profile, size and shape, visualisation, visualisation, Statistics, Econometrics and Quantitative Methods, Data Interpretation, Statistical, abundance data, bray-curtis dissimilarity, Animals, North Sea, Ecosystem, biplot, jel: jel:C88, jel: jel:C19

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    37
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Top 10%
Top 10%
Average
Green
hybrid