Abstract
This paper introduces a general procedure using hierarchical stochastic models for characterizing criminal careers within a population of heterogeneous offenders. Individuals engage in criminal careers which are treated as stochastic processes governed by fixed parameters (e.g., a rate parameter), and these parameters come from specified distributions. The parameters of these distributions at the upper level of the hierarchy must then be specified. The models are estimated using data on all persons arrested at least once in the six-county Detroit Standard Metropolitan Statistical Area during the 4 years 1974–1977 for a criterion offense (an index crime other than larceny) and arrested at least once for robbery through April 1979. The collected data set is not a random sample of all such offenders in the population. There is a bias toward selecting those with a higher arrest frequency. In order to make more general inferences, statistical adjustment was needed to overcome the arrest-frequency sampling bias. We construct a series of models for the arrest career and fit the models with the data set of arrests. After correcting biases in the data, we estimate the model parameters using empirical Bayes methods and then examine the resulting models.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahn, C. W. (1986).Hierarchical Stochastic Modelling of Arrest Careers, Unpublished Ph.D. thesis, Department of Statistics, Carnegie-Mellon University, Pittsburgh, Pa.
Avi-Itzhak, B., and Shinnar, R. (1973). Quantitative models in crime control.J. Crim. Just. 1: 185–217.
Barnett, A., Blumstein, A., and Farrington, A. (1987). Probabilistic models of youthful criminal careers.Criminology 25: 83–107.
Barnett, A., Blumstein, A., and Farrington, A. (1989). A prospective test of a criminal career model.Criminology 27: 373–388.
Blumstein, A., and Cohen, J. (1981).Analysis of Criminal Careers from an Incapacitation Perspective, School of Urban and Public Affairs, Carnegie-Mellon University, Pittsburgh, Pa.
Blumstein, A., Cohen, J., and Hsieh, P. (1982).The Duration of Adult Criminal Careers, School of Urban and Public Affairs, Carnegie-Mellon University, Pittsburgh, Pa.
Blumstein, A., Cohen, J., Roth, J., and Visher, C. (eds.) (1986).Criminal Careers and “Career Criminals”, National Research Council, National Academy of Sciences, Washington, D.C.
Chaiken, J., and Chaiken, M. (1982). Varieties of Criminal Behavior. Draft report to the National Institute of Justice, Rand Corporation, Santa Monica, Calif.
Lehoczky, J. P. (1986). Random parameter stochastic process models of criminal careers. In Blumstein, A., Cohen, J., Roth, J., and Visher, C. A. (eds.),Criminal Careers and “Career Criminals”, National Academy of Sciences Press, Washington, D.C., pp. 379–403.
Lehoczky, J. P., and Schervish, M. (1986). Estimation of Incarceration and Criminal Careers Using Hierarchical Models. Final Report Bureau of Justice Statistics Contract, 85-BJ-CX-0004.
Morris, C. N. (1983). Parametric empirical Bayes inference: Theory and applications.J. Am. Stat. Assoc. 78: 47–65.
Rhodes, W. (1989). The criminal career: Estimates of the duration and frequency of crime commission.J. Quant. Criminal. 5: 3–32.
Schmidt, P., and Witte, A. D. (1988).Predicting Recidivism Using Survival Models, Springer-Verlag, New York.
Vardi, Y. (1988). Statistical models for intercepted data.J. Am. Stat. Assoc. 83: 183–197.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Ahn, C.W., Blumstein, A. & Schervish, M. Estimation of arrest careers using hierarchical stochastic models. J Quant Criminol 6, 131–152 (1990). https://doi.org/10.1007/BF01065848
Issue Date:
DOI: https://doi.org/10.1007/BF01065848