Methods for Estimating Crime Rates of Individuals

by John E. Rolph, Jan M. Chaiken, Robert L. Houchens

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Abstract

Describes methods for analyzing offenders' crime commission data and deriving (1) individuals' crime commission rates and (2) rate distributions for groups of offenders with specified characteristics. Uncertain data are treated as censored observations, to obtain nonparametric maximum-likelihood estimates of the distribution of observed crime rates. No standard distributional form was found satisfactory for all crime types, and some types apparently do not occur according to a Poisson process. Shrinkage estimators of individuals' crime commission propensities are obtained by dividing offenders into groups and shrinking data toward a regression estimate of an individual's propensity, based on personal characteristics. A new multivariate distributional form for characterizing the joint distribution of individual crime counts is derived and fit to inmate survey data. Populations that can be surveyed (e.g., prisoners) are unrepresentative of target offender populations of primary interest. Sampling probabilities of surveyed individuals are estimated with stochastic models, allowing estimation of crime rate distributions in target populations.

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