Predicting criminal recidivism: A comparison of neural network models with statistical methods
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Criminal Justice.
Volume (Year): 24 (1996)
Issue (Month): 3 ()
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Web page: http://www.elsevier.com/locate/jcrimjus
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Schmidt, Peter & Witte, Ann Dryden, 1989.
"Predicting criminal recidivism using 'split population' survival time models,"
Journal of Econometrics,
Elsevier, vol. 40(1), pages 141-159, January.
- Peter Schmidt & Ann Dryden Witte, 1987. "Predicting Criminal Recidivism Using "Split Population" Survival Time Models," NBER Working Papers 2445, National Bureau of Economic Research, Inc.
- Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
- Greene, Michael A. & Hoffman, Peter B. & Beck, James L., 1994. "The mean cost rating (MCR) is Somers' D: A methodological note," Journal of Criminal Justice, Elsevier, vol. 22(1), pages 63-69.
- Palocsay, Susan W. & Wang, Ping & Brookshire, Robert G., 2000. "Predicting criminal recidivism using neural networks," Socio-Economic Planning Sciences, Elsevier, vol. 34(4), pages 271-284, December.
- Brendan Cushing-Daniels, 2005. "Even the errors discrimenate: How the split-population model of criminal recidivism makes justice even less colorblind," The Review of Black Political Economy, Springer, vol. 33(1), pages 25-39, September.
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