Abstract
Growing interest in recent years in developing broader ranges of intermediate sanctions or alternative-to-incarceration (ATI) programs has prompted a search for more effective ways to measure the impacts of these programs on jail and prison populations. One potentially useful strategy is to develop statistical models that predict the length of incarceration for sentenced offenders and apply these models to program client data to estimate prison bed displacement effects. New York City, which funds and monitors an extensive array of ATI programs, has been sponsoring research to develop and apply such models in an effort to improve the planning and evaluating of these programs. This article presents a series of regression models predicting sentence length using quantitative case and defendant as well as qualitative case strength data, and illustrates how they might be applied to ATI program data to estimate prison displacement effects.
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