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Regression Analysis Applied to Local Correctional Systems (From Practical Applications for Criminal Justice Statistics, P 149-167, 1998, M.L. Dantzker and Arthur J. Lurigio, et al., eds. -- See NCJ-175404)

NCJ Number
175411
Author(s)
R Guynes; T McEwen
Date Published
1998
Length
19 pages
Annotation
This study shows how a statistical technique (regression analysis) can be used to help solve or predict information necessary to make policy decisions; in this study, regression analysis was used to supply necessary information about daily jail populations in an effort to determine expansion needs.
Abstract
As part of a project conducted in 1991 for the Montgomery County Council of Government (Maryland), the authors conducted univariate and multivariate regression analysis on several significant influences on the county's criminal justice system: crimes, arrest, average daily jail population, and persons under correctional control. The intent was to model these overall categories against key sociodemographic characteristics over a 2- year period. The variable on average daily jail population was defined as the average number of persons who are in jail on any given day; the variable on persons under correctional control combined persons incarcerated in the county jail with those assigned to several alternative programs. The overall aim of this portion of the study was to determine whether the county jail needed to be expanded, and if so, what size it should be to accommodate the county's needs into the next century. The study showed that regression analysis can play a role in modeling average daily population and in determining jail-sizing needs for the future. Regression analysis also showed that changes in crime and arrests are associated generally with changes in the county's population; further, it showed that regression analysis can identify factors internal to the criminal justice system that are useful in modeling the average daily population of a correctional system. 4 tables and 3 figures

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