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'''CHAID''' is a type of [[decision tree]] technique, based upon adjusted significance testing. The technique was developed in [[South Africa]] and was published in 1980 by Gordon V. Kass. It can be used for prediction (like [[regression analysis]], originally known as XAID) or for detection of interaction between variables. CHAID stands for '''CH'''i-squared '''A'''utomatic '''I'''nteraction '''D'''etector, based upon a formal extension of the US AID (Automatic Interaction Detector) and THAID (THeta Automatic Interaction Detector) procedures of the 1960's and 70's.
In practice, CHAID is often used in the context of [[direct marketing]] to select groups of consumers and predict how their responses to some variables affect other variables, although early applications were in the field of medical and psychiatric research.
Like other decision trees, its 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 as with small sample sizes the respondent groups can quickly become too small for reliable analysis.
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* D.M. Hawkins & G.V. Kass. Automatic Interaction Detection. In D.M. Hawkins (ed) Topics in Applied Multivariate Analysis. Cambridge University Press, Cambridge, 1982, pp. 269-302.
* T.M. Hooton, R.W. Haley, D.K. Culver, J.W. White, W.B. Morgan & R.J. Carroll. The Joint Associations of Multiple Risk Factors with the Occurrence of Nosocomial Infections. American Journal of Medicine, Vol. 70, (1981), pp. 960-970.
* S. Brink
* D.P. McKenzie, P.D. McGorry, C.S. Wallace, L.H. Low, D.L. Copolov & B.S. Singh. Constructing a Minimal Diagnostic Decision Tree. Methods of Information in Medicine, Vol. 32 (1993), pp. 161-166.
==External links==
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