A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology

Bibliographic Details
Main Author:	Kim, Youngho
Language:	English
Published:	The Ohio State University / OhioLINK 2007
Subjects:	Geography hierarchical Bayesian data analysis surveillance space-time surveillance crime.
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=osu1186607028

id	ndltd-OhioLink-oai-etd.ohiolink.edu-osu1186607028
record_format	oai_dc
spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-osu11866070282021-08-03T05:52:35Z A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology Kim, Youngho Geography hierarchical Bayesian data analysis surveillance space-time surveillance crime. This dissertation analyzes crime in both ecological and surveillance perspectives. In ecological perspective, many studies ignore spatial effects in the models, leading to inefficient and biased results. This dissertation, by applying Bayesian hierarchical analysis, accounts for spatial effect in the model and presents correct socio-demographic factors related to residential crime occurrences. In surveillance perspective, literature to date has limitations in presenting exact locations of crime hotspots and implementing continuous analysis over time. Use of population information is the main reason of the limitations in the literature. Because the population information is based on census administrative area unit and is only updated in decennial bases, corresponding hotspots involve approximations in both population size and their locations. However, this study handles the problem by applying a newly devised surveillance method, which uses only crime accounts over time without the use of population information. The goal of this dissertation is providing significant demographic factors of crime and crime hotspots in near real time base, which will contribute to crime control. This goal is achieved by 1) handling spatial autocorrelation and heterogeneity in the analysis, 2) visualizing spatial effects on a map, 3) enabling continuous surveillance over time, 4) providing precise crime hotspot locations, and 5) presenting local changes in clusters over time. The models presented in this dissertation is applied to residential crimes occurred in Columbus, Ohio for the year 2000. Empirical results present significant demographic factors of residential crimes and locations of crime hotspots over time in near real-time framework. 2007-08-23 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1186607028 http://rave.ohiolink.edu/etdc/view?acc_num=osu1186607028 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection	NDLTD
language	English
sources	NDLTD
topic	Geography hierarchical Bayesian data analysis surveillance space-time surveillance crime.
spellingShingle	Geography hierarchical Bayesian data analysis surveillance space-time surveillance crime. Kim, Youngho A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology
author	Kim, Youngho
author_facet	Kim, Youngho
author_sort	Kim, Youngho
title	A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology
title_short	A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology
title_full	A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology
title_fullStr	A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology
title_full_unstemmed	A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology
title_sort	surveillance modeling and ecological analysis of urban residential crimes in columbus, ohio, using bayesian hierarchical data analysis and new space-time surveillance methodology
publisher	The Ohio State University / OhioLINK
publishDate	2007
url	http://rave.ohiolink.edu/etdc/view?acc_num=osu1186607028
work_keys_str_mv	AT kimyoungho asurveillancemodelingandecologicalanalysisofurbanresidentialcrimesincolumbusohiousingbayesianhierarchicaldataanalysisandnewspacetimesurveillancemethodology AT kimyoungho surveillancemodelingandecologicalanalysisofurbanresidentialcrimesincolumbusohiousingbayesianhierarchicaldataanalysisandnewspacetimesurveillancemethodology
_version_	1719426954735648768

A surveillance modeling and ecological analysis of urban residential crimes in Columbus, Ohio, using Bayesian Hierarchical data analysis and new space-time surveillance methodology

Similar Items