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Handbook of Quantitative Criminology pp 699–724Cite as

Statistical Analysis of Spatial Crime Data

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Abstract

While the geography of crime has been a focal concern in criminology from the very start of the discipline, the development and use of statistical methods specifically designed for spatially referenced data has evolved more recently. This chapter gives an overview of the application of such methods in research on crime and criminal justice, and provides references to the general literature on geospatial statistics, and to instructive and innovative applications in the crime and criminal justice literature.The chapter consists of three sections. The first section introduces the subject matter and delineates it from descriptive spatial statistics and from visualization techniques (“crime mapping.”) It discusses the relevance of spatial analysis, the nature of spatial data, and the issues of sampling and choosing a spatial unit of analysis. The second section deals with the analysis of spatial distributions. We discuss the specification of spatial structure, address spatial autocorrelation, and review a variety of spatially informed regression models and their applications. The third section addresses the analysis of movement, including spatial interaction models, spatial choice models, and the analysis of mobility triads, in the field of crime and criminal justice.

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Notes

  1. 1.

    Some spatial interaction models are also known as gravity models, because their mathematical form resembles Newton’s Law of Gravitation. This law asserts that the gravitational attraction between two bodies is proportional to the product of their masses divided by the squared distance between them, or \(F = g \cdot {M}_{1} \cdot {M}_{2} \cdot {D}^{-2}\), where g is the gravitational constant. As the physics analogy tends to isolate the model from fruitful application and development in social science (Haynes and Fotheringham, 1984), the term spatial interaction model is preferred here.

  2. 2.

    Note that in the aggregate spatial interaction models, we used index i to refer to the origin location. Here, in the disaggregated discrete choice model, i denotes an individual actor.

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  1. Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), Amsterdam, Netherlands

    Wim Bernasco & Henk Elffers

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  1. Wim Bernasco
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  1. College of Criminology, Florida State University, West Call Street 643, Tallahassee, 32306, U.S.A.

    Alex R. Piquero

  2. Inst. Criminology, Hebrew University of Jerusalem, Jerusalem, 91905, Israel

    David Weisburd

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Bernasco, W., Elffers, H. (2010). Statistical Analysis of Spatial Crime Data. In: Piquero, A., Weisburd, D. (eds) Handbook of Quantitative Criminology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-77650-7_33

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