Statistics for Spatial Data.

25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

The Analysis of Time Series: An Introduction, 4th edn. By C. Chatfield. ISBN 0 412 31820 2. Chapman and Hall, London, 1989. 242 pp. £13.50.

The Analysis of Time Series: An Introduction

Statistics and Data Analysis in Geology

The logistic regression model is frequently used in epidemiologic studies, yielding odds ratio or relative risk interpretations. Inspired by the theory of linear normal models, the logistic regression model has been extended to allow for correlated responses by introducing random effects. However, the model does not inherit the interpretational features of the normal model. In this paper, the authors argue that the existing measures are unsatisfactory (and some of them are even improper) when quantifying results from multilevel logistic regression analyses. The authors suggest a measure of heterogeneity, the median odds ratio, that quantifies cluster heterogeneity and facilitates a direct comparison between covariate effects and the magnitude of heterogeneity in terms of well-known odds ratios. Quantifying cluster-level covariates in a meaningful way is a challenge in multilevel logistic regression. For this purpose, the authors propose an odds ratio measure, the interval odds ratio, that takes these difficulties into account. The authors demonstrate the two measures by investigating heterogeneity between neighborhoods and effects of neighborhood-level covariates in two examples--public physician visits and ischemic heart disease hospitalizations--using 1999 data on 11,312 men aged 45-85 years in Malmo, Sweden.

Appropriate Assessment of Neighborhood Effects on Individual Health: Integrating Random and Fixed Effects in Multilevel Logistic Regression

GIS and Crime Mapping is the definitive text to support readers with the fundamental theory, scientific methodologies, analysis techniques, application design, and management processes for implementing and developing crime mapping. The book includes a comprehensive presentation of GIS, crime mapping and geographic crime analysis solutions for operational, tactical, investigative, and strategic policing and crime reduction purposes. Topics in this book include, • The basics of GIS for mapping crime • Definitions and geographical structures within criminal justice • The principle spatial theories of crime • Spatial statistics for crime analysis • Crime hotspots • Mapping and analysing change over time • Mapping crime with local community data • Information sharing • GIS and crime mapping for operational, tactical, investigative, and strategic policing and crime reduction • Crime map cartography • Implementing GIS and crime mapping • Managing and organising crime mapping and analysis. GIS and Crime Mapping draws from the authors’ international expertise and experiences. The book includes short case studies at relevant sections to help demonstrate the key principles, concepts and applications of crime mapping, and bring an added international richness and depth. GIS and Crime Mapping uniquely combines the topics of theoretical principles, GIS, analysis, map design, and organisational structures of GIS and crime mapping for policing and crime reduction, delivered in a style that is accessible to a broad range of readers. These include intelligence and crime analysts; policing, intelligence, law enforcement and crime reduction practioners; and academics, lecturers, researchers and students in GIS, crime science, crime prevention, community safety, criminal justice or criminology. GIS and Crime Mapping acts as an important and timely book in this growing and exciting field.

GIS and Crime Mapping

This paper is timely, given that policing is currently going through a period of significant change in both operational tactics and organisational structures. New ideas in crime reduction and changes to short- and long-term policing strategies are underway. Intelligence-led policing represents a recent approach and is one of the more prevalent of the current "shifts in crime control philosophy and policing practice" (Maguire 2000). Surprisingly, given the wide distribution of the term "intelligence-led policing", considerable confusion remains in regard to its actual meaning to both front-line officers and police management. This paper provides an introduction to intelligence-led policing and discusses some of the related limitations and opportunities. Adam Graycar Director Since the 1990s, "intelligence-led policing" (also known as intelligence-driven policing") has entered the lexicon of modern policing, especially in the UK and more recently Australia. Yet even with the ability of new ideas and innovation to spread throughout the policing world at the click of a mouse, there is still a lack of clarity among many in law enforcement as to what intelligence-led policing is, what it aims to achieve, and how it is supposed to operate. This can be seen in recent inspection reports of Her Majesty's Inspectorate of Constabulary (HMIC) in the UK (HMIC 2001, 2002), and in the lack of clarity regarding intelligence-led policing in the United States. A recent summit in March 2002 of over 120 criminal intelligence experts from across the US, funded by the US government and organised by the International Association of Chiefs of Police, may become a turning point in policing within the US. The participants called for a National Intelligence Plan, with one of the core recommendations being to "promote intelligence-led policing through a common understanding of criminal intelligence and its usefulness" (IACP 2002, p. v). The aspirations of the summit are considerable, but what is unclear from the summit report is a sound understanding of the aims of intelligence-led policing and its relationship to crime reduction. As intelligence-led policing is now a term in common usage within Australian law enforcement (a search of web pages and media releases found the term "intelligence-led" in all Australian police sites and the web site of the new Australian Crime Commission), it is timely to consider the origins of intelligence-led policing, the crime reduction levers it aims to pull, and the limitations and possibilities for this type of operational practice. Origins of Intelligence-led Policing Intelligence-led policing entered the police lexicon at some time around the early 1990s. As Gill (1998) has noted, the origins of intelligence-led policing are a little indistinct, but the earliest references to it originate in the UK where a seemingly inexorable rise in crime during the late 1980s and early 1990s coincided with increasing calls for police to be more effective and to be more cost-efficient. The driving forces for this move to a new strategy were both external and internal to policing. External drivers included an inability of the traditional, reactive model of policing to cope with the rapid changes in globalisation which have increased opportunities for transnational organised crime and removed physical and technological barriers across the policing domain. In the new "risk society" (Ericson & Haggerty 1997) the police were seen as the source of risk management data for a range of external institutions. With such an influence beyond the boundaries of law enforcement, it was never going to be long before the "new public management" drive to increase efficiency in public agencies reached the police. At the same time there was an internal recognition that changes were taking place in the dynamic relationship between the private security industry and the public police. …

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Intelligence-Led Policing

Originating with the Newark, NJ, foot patrol experiment, research has found police foot patrols improve community perception of the police and reduce fear of crime, but they are generally unable to reduce the incidence of crime. Previous tests of foot patrol have, however, suffered from statistical and measurement issues and have not fully explored the potential dynamics of deterrence within microspatial settings. In this article, we report on the efforts of more than 200 foot patrol officers during the summer of 2009 in Philadelphia. Geographic information systems (GIS) analysis was the basis for a randomized controlled trial of police effectiveness across 60 violent crime hotspots. The results identified a significant reduction in the level of treatment area violent crime after 12 weeks. A linear regression model with separate slopes fitted for treatment and control groups clarified the relationship even more. Even after accounting for natural regression to the mean, target areas in the top 40 percent on pretreatment violent crime counts had significantly less violent crime during the operational period. Target areas outperformed the control sites by 23 percent, resulting in a total net effect (once displacement was considered) of 53 violent crimes prevented. The results suggest that targeted foot patrols in violent crime hotspots can significantly reduce violent crime levels as long as a threshold level of violence exists initially. The findings contribute to a growing body of evidence on the contribution of hotspots and place-based policing to the reduction of crime, and especially violent crime, which is a significant public health threat in the United States. We suggest that intensive foot patrol efforts in violent hotspots may achieve deterrence at a microspatial level, primarily by increasing the certainty of disruption, apprehension, and arrest. The theoretical and practical implications for violence reduction are discussed.

http://ttaniguchi.net/wp-content/uploads/2014/08/Ratcliffe-et-al-2012-The-Philadelphia-Foot-Patrol-Experiment.pdf

The philadelphia foot patrol experiment: a randomized controlled trial of police patrol effectiveness in violent crime hotspots*

Using epidemiological techniques for testing disease contagion, it has recently been found that in the wake of a residential burglary, the risk to nearby homes is tem- porarily elevated. This paper demonstrates the ubiquity of this phenomenon by analyzing space-time patterns of burglary in 10 areas, located in five different countries. While the precise patterns vary, for all areas, houses within 200 m of a burgled home were at an elevated risk of burglary for a period of at least two weeks. For three of the five countries, differences in these patterns may partly be explained by simple differences in target density. The findings inform theories of crime concentration and offender targeting strategies, and have implications for crime forecasting and crime reduction more generally.

/pdf/space-time-patterns-of-risk-a-cross-national-assessment-of-4eogatkrzx.pdf

Jerry H. Ratcliffe

Papers

GIS and Crime Mapping

Intelligence-Led Policing

The philadelphia foot patrol experiment: a randomized controlled trial of police patrol effectiveness in violent crime hotspots*

Space-time patterns of risk: A cross national assessment of residential burglary victimization

GIS and Crime Mapping: Chainey/GIS and Crime Mapping