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NCJ Number: NCJ 164098     Find in a Library
Title: Risk Classification of Probationers: Development of a Statistical Model Based on Management Information System Data
Author(s): P K Lattimore ; R L Linster
Date Published: 1996
Page Count: 98
Sponsoring Agency: National Institute of Justice
US Department of Justice
Office of Justice Programs
United States of America

US Dept of Justice NIJ Pub
United States of America
Sale Source: National Institute of Justice/NCJRS
Box 6000
Rockville, MD 20849
United States of America

NCJRS Photocopy Services
Box 6000
Rockville, MD 20849-6000
United States of America
Document: PDF 
Type: Report (Technical)
Language: English
Country: United States of America
Annotation: This report describes the establishment of methods and models for using management information system data of the Florida Department of Corrections to classify individuals by their likelihood of "failing" during probation.
Abstract: The classification is based on statistical estimation of the likelihood of individual failure (revocation and absconding) during the probation supervision period. These estimations are then used to classify individuals as high-, medium-, or low-risk for probation supervision purposes. The analysis uses case history records on offenders admitted to Florida probation between January 1, 1991, and December 31, 1994. While the data are specific to Florida's probationers and policies, the methods appear to be applicable to addressing practical issues associated with risk management in other jurisdictions and program settings. The report includes background information on Florida's probation system, hypothetical examples to illustrate important practical implications of translating individual failure probabilities into a three-level risk classification system, a technical description of mathematical methods by which individual failure probabilities are calculated, and information on work planned by researchers at the Florida Department of Corrections to convert the technical results into a fully automated probationer risk classification system. Appendixes contain additional information on logistic regression models and software for estimating multinomial logit models, along with model coefficients and goodness of fit graphs. Footnotes, tables, and figures
Main Term(s): Criminology
Index Term(s): Computer aided operations ; Mathematical models ; Probationers ; Statistical analysis ; Management Information Systems ; Correctional information systems ; Statistics ; Offender classification ; Probation condition violations ; Probation outcome prediction ; Courts ; Florida
Note: NIJ Working Paper 96-01
   
  To cite this abstract, use the following link:
https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=164098

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