[2][3] CHAID is based on a formal extension of AID (Automatic Interaction Detection)[4] and THAID (THeta Automatic Interaction Detection)[5][6] procedures of the 1960s and 1970s, which in turn were extensions of earlier research, including that performed by Belson in the UK in the 1950s.
[2] A history of earlier supervised tree methods can be found in Ritschard, including a detailed description of the original CHAID algorithm and the exhaustive CHAID extension by Biggs, De Ville, and Suen.
[citation needed] 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.
[citation needed] One important advantage of CHAID over alternatives such as multiple regression is that it is non-parametric.