A Tale of Two Margins: Exploring the Probabilistic Processes that Generate Prison Visits in the First Two Years of Incarceration
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The study extends previous literature (Cochran in J Crim Justice 40:433–440, 2012, J Res Crime Delinq 51(2):200–229, 2014) by simultaneously examining two margins: the probability of receiving a visit and the number of visits a prisoner receives conditional on receiving any visits; adding a level of nuance to the exploration of prison visits.
A random sample of New York State prisoners admitted between 2000 and 2013 who served at least 24 months and had basic admission, release, and transfer data (N = 22,975) were selected. Visit patterns were derived using group-based trajectory models with a zero-inflated Poisson specification and up to a cubic polynomial on probability and count parameters.
The best fitting model had seven groups that displayed wide variation in the probability of a visit (in both directions). By contrast, the number of visits, conditional on receiving a visit, is relatively constant over time. Subsequent dual trajectory modeling of prison visits with distance from home county demonstrates that the dynamic patterns of probability of visit correspond with dynamic patterns of distance from home county.
We demonstrate that time variation in visitation occurs along the prevalence margin. Researchers interested in studying the longitudinal relationship between visits and outcomes should be attentive to this result. Additionally, characteristics of prisoners assigned to the trajectory groups using Posterior Probabilities of Assignment suggest that pre-prison factors (i.e. criminal record) and in-prison policy decisions (i.e. custody level) are associated with particular patterns of visits over time; highlighting the challenge to understanding the effect of visitation in studies without explicit causal identification strategies.
KeywordsZero-inflated Poisson (ZIP) Group-based trajectory model (GTM) Prison visit
The authors would like to thank the staff at both DCJS and DOCCS for their assistance. All errors remain our own.
These data are provided by the New York State Division of Criminal Justice Services (DCJS) and New York State Department of Corrections and Community Supervision (DOCCS). The opinions, findings, and conclusions expressed in this publication are those of the authors and not those of DCJS or DOCCS. Neither New York State nor DCJS nor DOCCS assume liability for its contents or use thereof.
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