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23 J. Quantitative Criminology 1 (2007)

handle is hein.journals/jquantc23 and id is 1 raw text is: J Quant Criminol (2007) 23:1-22 DOI 10.1007/s10940-006-9016-9 Using Booking Data to Model Drug User Arrest Rates: A Preliminary to Estimating the Prevalence of Chronic Drug Use William Rhodes - Ryan Kling - Patrick Johnston Published online: 26 October 2006 O Springer Science+Business Media, LLC 2006 Abstract Public policy is often concerned with the size and characteristics of special populations that are difficult to reach in household surveys. Chronic drug users, who often live outside conventional households, provide the illustration motivating this paper. An alternative to household surveys is to question chronic drug users where they congregate-jails, treatment programs, and shelters, for example. Using such opportunistic data for prevalence estimation raises difficult problems for statistical inference: Study subjects who arrive at the collection points cannot be deemed a random sample of the general population. However, if we could estimate the rates at which chronic drug users arrive at the collection points, then we could use those estimates to weight the sample to represent the population. This paper presents a modified Poisson mixture model used to estimate the stochastic process that accounts for how chronic drug users get arrested. It uses that model to estimate arrest rates for 38 counties using up to sixteen quarters of data from the Arrestee Drug Abuse Monitoring survey. Keywords Chronic drug use Hard-to-reach populations Arrest rates Endogenous stratification Poisson mixture models Model-based estimation W. Rhodes (H) Domestic Health Division, Abt Associates Inc., 55 Wheeler Street, Cambridge, MA 02138-1168, USA e-mail: BillRhodes@abtassoc.com R. Kling Domestic Health Division, Abt Associates Inc., Cambridge, MA, USA P. Johnston Clinical Research Program, Children's Hospital, Boston, MA, USA 4_ Springer