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Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale

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  • Quick, Matthew
  • Li, Guangquan
  • Brunton-Smith, Ian

Abstract

To examine if, and how, spatial crime patterns are explained by one or more underlying crime-general patterns.

Suggested Citation

  • Quick, Matthew & Li, Guangquan & Brunton-Smith, Ian, 2018. "Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 22-32.
    • Handle: RePEc:eee:jcjust:v:58:y:2018:i:c:p:22-32
    DOI: 10.1016/j.jcrimjus.2018.06.003
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    References listed on IDEAS

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    1. Haining, Robert & Law, Jane & Griffith, Daniel, 2009. "Modelling small area counts in the presence of overdispersion and spatial autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2923-2937, June.
    2. Leonhard Knorr‐Held & Nicola G. Best, 2001. "A shared component model for detecting joint and selective clustering of two diseases," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 73-85.
    3. A. Hirschfield & K.J. Bowers, 1997. "The Effect of Social Cohesion on Levels of Recorded Crime in Disadvantaged Areas," Urban Studies, Urban Studies Journal Limited, vol. 34(8), pages 1275-1295, July.
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    5. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    6. Andresen, Martin A., 2011. "Estimating the probability of local crime clusters: The impact of immediate spatial neighbors," Journal of Criminal Justice, Elsevier, vol. 39(5), pages 394-404.
    7. Chamberlain, Alyssa W. & Hipp, John R., 2015. "It's all relative: Concentrated disadvantage within and across neighborhoods and communities, and the consequences for neighborhood crime," Journal of Criminal Justice, Elsevier, vol. 43(6), pages 431-443.
    8. Malleson, Nick & Andresen, Martin A., 2016. "Exploring the impact of ambient population measures on London crime hotspots," Journal of Criminal Justice, Elsevier, vol. 46(C), pages 52-63.
    9. Chiu, W. Henry & Madden, Paul, 1998. "Burglary and income inequality," Journal of Public Economics, Elsevier, vol. 69(1), pages 123-141, July.
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    Cited by:

    1. Seppo Virtanen & Mark Girolami, 2021. "Spatio‐temporal mixed membership models for criminal activity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1220-1244, October.
    2. Miriam Marco & Enrique Gracia & Antonio López-Quílez & Marisol Lila, 2021. "The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach," IJERPH, MDPI, vol. 18(10), pages 1-14, May.
    3. Cernat, Alexandru & Buil-Gil, David & brunton-smith, ian & Pina-Sánchez, Jose & Murrià-Sangenís, Marta, 2021. "Estimating crime in place: Moving beyond residence location," SocArXiv gx9a7, Center for Open Science.
    4. Matthew Quick, 2019. "Multiscale spatiotemporal patterns of crime: a Bayesian cross-classified multilevel modelling approach," Journal of Geographical Systems, Springer, vol. 21(3), pages 339-365, September.
    5. Arun Sondhi & Alessandro Leidi & Emily Gilbert, 2021. "A Small Area Estimation Method for Investigating the Relationship between Public Perception of Drug Problems with Neighborhood Prognostics: Trends in London between 2012 and 2019," IJERPH, MDPI, vol. 18(17), pages 1-12, August.

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