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NCJ Number: 78709 Add to Shopping cart Find in a Library
Title: Confirmatory and Exploratory Analysis of the Spatio and Temporal Properties of Crime Data - Final Report - Executive Summary
Author(s): R G Golledge; L J Hubert
Corporate Author: University of California, Santa Barbara
United States of America
Date Published: 1981
Page Count: 222
Sponsoring Agency: National Institute of Justice (NIJ)
Washington, DC 20531
National Institute of Justice/
Rockville, MD 20849
University of California, Santa Barbara
Santa Barbara, CA 93106
US Dept of Justice NIJ Pub
Washington, DC 20531
Grant Number: 79-NI-AX-0057
Sale Source: National Institute of Justice/
NCJRS paper reproduction
Box 6000, Dept F
Rockville, MD 20849
United States of America
Document: PDF
Type: Statistics
Language: English
Country: United States of America
Annotation: This executive summary discusses the methodology and findings of research designed to develop procedures for analyzing selected spatial and temporal characteristics of crime data.
Abstract: One of the major problems investigated was implications of aggregation in data tables for evaluating criminal justice statistics. Another problem analyzed was assessing homogeneity in cross-classified proximity data. Given an arbitrary proximity matrix that is cross-classified according to two dimensions, a nonparametric strategy generalizing Friedman's analysis-of-variance method is suggested for testing the saliences of the dimensions. The implications of unidimensional seriation for evaluating criminal justice data are also considered. The problem of validating a given unidimensional scale (ordering of a set of objects along a single dimension) is discussed in terms of a few simple properties of the data used to obtain the scale. In the examination of proximity matrix reorganization and hierarchical clustering, connections between hierarchical clustering and the seriation of objects along a continuum that depends on the patterning of entries in a proximity matrix are discussed. Several generalizations of the usual spatial autocorrelation indices are developed, based on the notion of matrix comparisons. Also introduced is an inference model for the percentage voting agreement measure which considered the composition of the parent group in evaluating the cohesion of a subgroup. Some comments on non-Euclidian mental maps are included, and possible future research is discussed.
Index Term(s): Crime Statistics; Evaluation; Nonbehavioral correlates of crime; Statistical analysis
Note: This document has microfiche versions of NCJ 78709-78713.
To cite this abstract, use the following link:
http://www.ncjrs.gov/App/publications/abstract.aspx?ID=78709

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