Abstract
![CDATA[Correspondence analysis (CA) is popular method for providing a graphical summary of the association between two or more categorical variables. It has gained a reputation for being a quick easily interpreted method of detecting relationships. Despite its popularity, and its acceptance amongst European researchers and those in the UK, the theoretical development of CA in the Australasian region has been relatively slow. Typically CA has been applied exclusively to two-way, or more generally, multi-way contingency tables. However recent, and not so recent, advances make CA a very useful tool for the analysis of other types of data structures. We will look at its application in situations where two categorical variables are nominal data, ordinal data, ranks, continuous and reflect geographical two-dimensional distances. We will also look at some modifications of the classical approach, focusing on identifying an asymetric relationship between the categories using non-symmetrical correspondence analysis (NSCA).]]
| Original language | English |
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| Title of host publication | Proceedings of the 2004 Workshop on Research Methods: Statistics and Finance |
| Publisher | University of Wollongong |
| Number of pages | 12 |
| ISBN (Print) | 1741281075 |
| Publication status | Published - 2004 |
| Event | Workshop on Research Methods: Statistics and Finance - Duration: 1 Jan 2004 → … |
Conference
| Conference | Workshop on Research Methods: Statistics and Finance |
|---|---|
| Period | 1/01/04 → … |
Keywords
- correspondence analysis (statistics)
- contingency tables
- nominal data
- ranked data
- proximity data
- non-symmetrical correspondence analysis