On a Stepwise Procedure for Two Population Bayes Decision Rules Using Discrete Variables
John M. Lachin · Biometrics · 1973
The primary difficulty in the application of Bayes decision rules based on discrete data has been the problem of deriving satisfactory estimates of the likelihoods. A measure of the potential effectiveness of a t dimensional sample space is developed, a linear function of which is asymptotically distributed as chi-square. A stepwise procedure for item selection is then presented in order to derive more stable estimates of the likelihoods through a reduction of the dimensionality of the sample space. The procedure is then illustrated with application to the problem of screening for schizophrenia.