Predicting suicide attacks : : integrating spatial, temporal, and social features of terrorist attack targets /

Predicting suicide attacks : : integrating spatial, temporal, and social features of terrorist attack targets / / Walter L. Perry [and seven others].

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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 fea...

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Bibliographic Details
Superior document:Rand Corporation monograph series
:
Naval Research Laboratory (U.S.)
Perry, Walt L.,
VerfasserIn:
Perry, Walt L.
TeilnehmendeR:
Perry, Walt L.,
Naval Research Laboratory (U.S.)
RAND Homeland Security and Defense Center.
Place / Publishing House:Santa Monica, CA : : RAND Corporation,, 2013.
Year of Publication:2013
Language:English
Series:Rand Corporation monograph series.
Physical Description:1 online resource (xxv, 85 pages) :; illustrations (some color)
Notes:Description based upon print version of record.
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Table of Contents:
  • 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
  • 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
  • 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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