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Activity Number:
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475
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Type:
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Contributed
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Date/Time:
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Thursday, August 7, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #300791 |
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Title:
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Predicting Access Rates to Substance Abuse Programs in Correctional Facilities Using Regression Trees
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Author(s):
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Panagiota Kitsantas*+ and Faye Taxman and Matthew Perdoni and Deanna Breslin
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Companies:
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George Mason University and George Mason University and George Mason University and George Mason University
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Address:
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4400 University Drive, Fairfax, VA, 22030,
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Keywords:
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regression trees ; substance abuse ; correctional facilities ; access rates
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Abstract:
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The purpose of this study was to investigate the relative importance of structural, administrative, and program level variables in predicting access rates to substance abuse treatment services for drug-involved offenders. The data, which were collected through a nationally representative survey of correctional and treatment administrators as part of the Criminal Justice Drug Abuse Treatment Studies, included 295 substance abuse treatment programs that were classified into three modalities of treatment services: high, medium and low intensity. Regression trees were built for each of these modalities to determine which variables were important in predicting access. This is the first phase of understanding capacity of correctional agencies to appropriate treatment services for offenders.
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