A MEASURE OF SEPARABILITY AND RANDOM ZEROS IN STATISTICAL CLASSIFICATION.

The setting for this study is the two-group multinomial classification problem. Based on a measure of the log odds in favor of one particular group, a large sample confidence interval for a measure of separability is derived. The asymptotic result employed assumes that all states have positive observed frequencies. Realizing that this assumption is often violated, we consider a method based upon log-linear representation of state frequencies to first remove any random zeros before attempting to effect a classification. The method is illustrated in a data set dealing with the behavioral consequences following hypoxic trauma. [ABSTRACT FROM AUTHOR]