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Factor analysis is a set of technique to reduce the dimensionality of the data. The goal is to describe the dataset with a smaller number of variables (ie underlying factors).

Factor analysis is mainly used in

• marketing.
• French sociology (Bourdieu and co)
• psychology

It is also known as data mining, multivariate data analysis or exploratory data analysis.

• factomineR

[edit] Principal Component Analysis

• prcomp() in the stats package
• princomp() in the stats package
• PCA deals with continuous variables

[edit] Correspondence Analysis

• corresp in the MASS package
• Michael Greenacre's "ca" package. See the Journal of Statistical Software paper
• Correspondence Analysis and Related Network
• Quick-R's page

Correspondence analysis is a tool for analysing contingency tables.

• Simple and Canonical Correspondence Analysis Using the R Package anacor

[edit] Multiple Correspondence Analysis

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Index

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