Abstract
Five uses of the Automatic Interaction Detector (AID) program in the analysis of health survey data are illustrated in application to examples of increasing complexity. The “forced trees” technique is discussed as a solution to the problem of substitution effects, and results of the AID technique are compared with those of regression analysis. Alternative research strategies are proposed for joint use of the two methods.
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Selected References
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