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Examining the (IR) Relevance of Aggregation Bias for Multilevel Studies of Neighborhoods and Crime with an Example Comparing Census Tracts to Official Neighborhoods in Cincinnati

NCJ Number
Criminology Volume: 40 Issue: 3 Dated: August 2002 Pages: 681-709
Date Published
August 2002
39 pages

This article compares models predicting re-arrest for domestic violence in Cincinnati.


Potential differences in results from bi-level models predicting re-arrest for domestic violence in Cincinnati is presented in this article. Arguing that aggregate units representing “neighborhoods” have been inconsistent predictors in multilevel studies of neighborhood influences on crime, this author proposes that different measures of neighborhood boundaries may affect multilevel findings if aggregate-level effects are studied only at specific macro levels. In order to compare possible differences in multilevel findings by type of aggregate, the author compares results from two separate bi-level analyses of the affects of re-arrest for domestic violence. Focusing on individuals, census tracts, and officially defined city neighborhoods in Cincinnati, aggregate measures were analyzed through hierarchical nonlinear modeling. Results indicate that both census tract and city neighborhood macro units generated the same findings at the individual and aggregate levels of analysis. After discussing how the results of this study compared with and supported previous macro and multilevel studies, the author concludes that the results presented here are encouraging for future research on official neighborhoods aggregates. Tables, references, appendices

Date Published: August 1, 2002