Correspondence Analysis

Correspondence Analysis

Correspondence analysis (CA) is a multivariate statistical technique proposed by Hirschfeld and later developed by Jean-Paul Benzécri. It is conceptually similar to principal component analysis, but applies to categorical rather than continuous data. In a similar manner to principal component analysis, it provides a means of displaying or summarising a set of data in two-dimensional graphical form.

All data should be nonnegative and on the same scale for CA to be applicable, and the method treats rows and columns equivalently. It is traditionally applied to contingency tables — CA decomposes the chi-squared statistic associated with this table into orthogonal factors. Because CA is a descriptive technique, it can be applied to tables whether or not the chi-square statistic is appropriate. Several variants of CA are available, including detrended correspondence analysis and canonical correspondence analysis. The extension of correspondence analysis to many categorical variables is called multiple correspondence analysis. An adaptation of correspondence analysis to the problem of discrimination based upon qualitative variables (i.e., the equivalent of discriminant analysis for qualitative data) is called discriminant correspondence analysis or barycentric discriminant analysis.

In the social sciences, correspondence analysis, and particularly its extension multiple correspondence analysis, was made known outside France through French sociologist Pierre Bourdieu's application of it.

Read more about Correspondence Analysis:  Implementations

Other articles related to "correspondence analysis, analysis":

Correspondence Analysis - Implementations
... ca, vegan, ExPosition, and FactoMineR which perform correspondence analysis and multiple correspondence analysis ... A MATLAB program (with a tutorial) for correspondence analysis ...
Seriation (archaeology) - Statistical Methods For Seriation - Correspondence Analysis For Seriation Purposes
... for contextual and frequency problems is based on correspondence analysis ... The sequence of the first axis of a correspondence analysis is considered the best seriation order (Shennan 1997, p ... a mapping of the component scores for the first two axes of the correspondence analysis result will display a parabola if the design styles considered are ...
Principal Component Analysis - Correspondence Analysis
... Correspondence analysis (CA) was developed by Jean-Paul Benzécri and is conceptually similar to PCA, but scales the data (which should be non-negative) so that rows and columns are treated equivalently ... Several variants of CA are available including detrended correspondence analysis and canonical correspondence analysis ... One special extension is multiple correspondence analysis, which may be seen as the counterpart of principal component analysis for categorical data ...
Seriation (archaeology) - Examples - Example 3: Ideal Data, Seriation and Correspondence Analysis
... The correspondence analysis results shown in the figures below were calculated on the basis of 49 contexts with ideal seriation data ... The scatterplot of the first two correspondence analysis axes shows the typical parabola shape ... proposed an adjustment which is called detrended correspondence analysis ...
Biplot - Introduction and History
... R programming language, to generate biplots associated with principal component analysis (PCA), multidimensional scaling (MDS), log-ratio analysis (LRA ... want to consider, for example, principal component analysis (PCA), canonical variates analysis (CVA) or various types of correspondence analysis ...

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