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|a 363.325/12
|2 23
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|a UAMI
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|a Perry, Walt L.
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|a Predicting suicide attacks :
|b integrating spatial, temporal, and social features of terrorist attack targets /
|c Walter L. Perry, Claude Berrebi, Ryan Andrew Brown, John Hollywood, Amber Jaycocks, Parisa Roshan,.
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|a Santa Monica, CA :
|b RAND,
|c [2013]
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|a 1 online resource
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|a text
|2 rdacontent
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|a computer
|2 rdamedia
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|a online resource
|2 rdacarrier
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|a Includes bibliographical references.
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|a Description based on print version record and CIP data provided by publisher.
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|a Cover; Title Page; Copyright; Preface; Contents; Figures; Tables; Summary; Acknowledgments; Abbreviations; CHAPTER ONE: Introduction and Overview; Background; About This Report; CHAPTER TWO: Quantitative Data and Methods; Quantitative Data; Socioeconomic Characteristics; Demographic Characteristics; Electoral Data; Proximity to Terrorist Safe Houses; Sociocultural Precipitants; Principal Component Analysis and Logistic Regression; Logistic Regression; Dimension Reduction; Classification and Regression Trees; Sociocultural Precipitants Analysis; Results of Quantitative Data Analysis
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|a Principal Components Analysis Logistic Regression Models; Classification and Regression Trees; Sociocultural Precipitants; Summing Up; CHAPTER THREE: Qualitative Analysis; Methodology; Hypotheses Driving the Use of the Methodology; Assumptions in Using the Methodology; Restrictions; Timing; Results of Qualitative Data Analysis; Identification of Codes; Distribution of Codes; Retargeting of Previously Attacked Locations; Dispersion of Attacks over Time; Assessment of Transportation Targets; Comparison of Codes to a Subject-Matter Expert Hypothesis; CHAPTER FOUR: Conclusions and Recommendations
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|a Conclusions from Quantitative Data Analysis Conclusions from Qualitative Data Analysis; Recommendations for Further Research; Regression Analyses and Classification; Sociocultural Precipitants; Transferability; Appendixes; A. Sociocultural Precipitant Database; B. Logistic Regression Output; About the Authors; Bibliography
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|a As part of an exploration of ways to predict what determines the targets of suicide attacks, RAND conducted a proof-of-principle analysis of whether adding sociocultural, political, economic, and demographic factors would enhance the predictive ability of a methodology that focused on geospatial features. This test case focused on terrorist bombing incidents in Israel, but the findings indicate that the methodology merits further exploration.
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|a JSTOR
|b Books at JSTOR Open Access
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590 |
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|a JSTOR
|b Books at JSTOR All Purchased
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650 |
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|a Suicide bombings
|z Israel.
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650 |
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|a Terrorism
|z Israel.
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650 |
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|a Terrorists
|x Suicidal behavior
|z Israel.
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650 |
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6 |
|a Attentats-suicides
|z Israël.
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650 |
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6 |
|a Terrorisme
|z Israël.
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650 |
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6 |
|a Terroristes
|x Comportement suicidaire
|z Israël.
|
650 |
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7 |
|a Suicide bombings
|2 fast
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650 |
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7 |
|a Terrorism
|2 fast
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650 |
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7 |
|a Terrorists
|x Suicidal behavior
|2 fast
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651 |
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|a Israel
|2 fast
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0 |
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|i Print version:
|a Perry, Walt L.
|t Predicting suicide attacks
|d Santa Monica, CA : RAND, [2013]
|z 9780833078001
|w (DLC) 2013005100
|
856 |
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|u https://jstor.uam.elogim.com/stable/10.7249/j.ctt2jc9d2
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