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Journal of Quantitative Criminology

, Volume 32, Issue 4, pp 723–724 | Cite as

Response to “Crime Places in Context”

  • Alex Reinhart
Comment

The recent paper “Crime Places in Context: An Illustration of the Multilevel Nature of Hot Spot Development” (Deryol et al. 2016), published in Journal of Quantitative Criminology, uses multilevel Poisson regression analysis to evaluate factors which contribute to local crime rates. In particular, the authors test three hypotheses concerning the three-way interaction between nearby carry-out liquor stores, on-premises drinking establishments, and bus routes, to determine whether “it is a combination of risky nodes and paths that are more important than any one single risky facility”. However, the analysis contains statistical flaws which render it unable to test the hypotheses and invalidate the conclusions presented. Most importantly, their interaction term is not an interaction at all.

Table 2 of Deryol et al. ( 2016) shows three hierarchical Poisson regression models fit to the data. Model 2 does not contain an interaction term, fitting the three covariates separately, while Model 3...

Keywords

Linear Hierarchical Model Poisson Regression Analysis Deviance Test Liquor Store Local Crime 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Reference

  1. Deryol R, Wilcox P, Logan M, Wooldredge J (2016) Crime places in context: an illustration of the multilevel nature of hot spot development. J Quant Criminol. doi: 10.1007/s10940-015-9278-1 Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of StatisticsCarnegie Mellon UniversityPittsburghUSA

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