ways. First, while the Burgess method uses subjective judgment to select a cutoff score for a multi-valued predictor with a binary outcome, the Kerby method uses classification and regression tree (CART) analysis. In this way, the selection of the cutoff score is based not on subjective judgment, but on a statistical criterion, such as the point where the chi-square value is a maximum. The second difference is that while the Burgess method is applied to a binary outcome, the Kerby method can apply to a multi-valued outcome, because CART analysis can identify cutoff scores in such cases, using a criterion such as the point where the t-value is a maximum. Because CART analysis is not only binary, but also recursive, the result can be that a predictor variable will be divided again, yielding two cutoff scores. The standard form for each predictor is that a score of one is added when CART analysis creates a partition. One study (Kerby, 2003) selected as predictors the five traits of the Big five personality traits, predicting a multi-valued measure of suicidal ideation. Next, the personality scores were converted into standard form with CART analysis. When the CART analysis yielded one partition, the result was like the Burgess method in that the predictor was coded as either zero or one. But for the measure of neuroticism, the result was two cutoff scores. Because higher neuroticism scores correlated with more suicidal thinking, the two cutoff scores led to the following coding: "low Neuroticism" = 0, "moderate Neuroticism" = 1, "high Neuroticism" = 2 (Kerby, 2003). z-score method Another method can be applied when the predictors are measured on a continuous scale. In such a case, each predictor can be converted into a standard score, or z-score, so that all the predictors have a mean of zero and a standard deviation of one. With this method of unit-weighted regression, the variate is a sum of the z-scores (e.g., Dawes, 1979; Bobko, Roth, & Buster, 2007). Literature review The first empirical study using unit-weighted regression is widely considered to be a 1928 study by sociologist Ernest W. Burgess. He used 21 variables to predict parole success or failure, and the results suggest that unit weights are a useful tool in making decisions about which inmates to parole. Of those inmates with the best scores, 98% did in fact succeed on parole; and of those with the worst