A Multidimensional Contingency Table Analysis of Parole Outcome

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Abstract
A major trend in the development of prediction in criminal justice has been toward increased statistical sophistication of methods. This study examines the utility of a new statistical method—log-linear analysis—as a means of predicting parole success relative to the Burgess method in both a construction and cross-validation sample. In addition, a replication study of the derived log- linear model was performed. The results suggest that the more sophisticated technique does not improve the ability to predict parole success beyond that achieved by the simpler method. Further, the hierarchical model emerging from the construction sample did not replicate in the validation sample. These results, when read in light of other studies, indicate that improvement in statistical technique may not be the best means of improving predictive effi ciency. The results also indicate that replication of hierarchical model fitting cannot be assumed, but rather must be studied empirically. The implications of these results are discussed for prediction research and theory testing.