Chi-square automatic interaction detection: Difference between revisions

Revision as of 15:32, 2 December 2024

Revision as of 17:33, 2 December 2024

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CHAID can be used for prediction (in a similar fashion to [[regression analysis]], this version of CHAID being originally known as XAID) as well as classification, and for detection of interaction between variables.<ref name="morgan1963"/><ref name="messenger1972"/><ref name="morgan1973"/>

In practice, CHAID is often used in the context of [[direct marketing]] to select groups of consumers to predict how their responses to some variables affect other variables, although other early applications were in the fields of medical and psychiatric research.{{fact|date=December 2024}}

Like other decision trees, CHAID's advantages are that its output is highly visual and easy to interpret. Because it uses multiway splits by default, it needs rather large sample sizes to work effectively, since with small sample sizes the respondent groups can quickly become too small for reliable analysis.{{fact|date=December 2024}}

One important advantage of CHAID over alternatives such as multiple regression is that it is non-parametric.{{fact|date=December 2024}}

==See also==