LEADER 04101nam 2200613Ia 450 001 9910993983503321 005 20250414171158.0 010 $z9780833078001 010 $a9780833078032$b(electronic bk.) 010 $a0833078038 035 $a(MiAaPQ)EBC1365207 035 $a(Au-PeEL)EBL1365207 035 $a(CaPaEBR)ebr10678771 035 $a(OCoLC)857365413 035 $a(CKB)17642205200041 035 $a(oapen)doab115035 035 $a(EXLCZ)9917642205200041 100 $a20130305d2013 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPredicting suicide attacks $eintegrating spatial, temporal, and social features of terrorist attack targets /$fWalter L. Perry ... [et al.] 205 $a1st ed. 210 $aSanta Monica, Calif $cRAND$d[2013] 210 1$aSanta Monica, CA :$cRAND Corporation,$d2013. 215 $a1 online resource (95 pages) 225 1 $aRand Corporation monograph series 300 $aDescription based upon print version of record. 311 08$aPrint version: Perry, Walter L. Predicting Suicide Attacks Santa Monica : RAND Corporation, The,c2013 9780833078001 311 08$a0833078003 320 $aIncludes bibliographical references (p. 83-85). 327 $aCover -- 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. 330 $aAs part of an exploration of ways to predict what determines the targets of suicide attacks, RAND conducted a proof-of-principle analysis of whether adding sociocultural, political, economic, and demographic factors would enhance the predictive ability of a methodology that focused on geospatial features. This test case focused on terrorist bombing incidents in Israel, but the findings indicate that the methodology merits further exploration. 410 0$aRand Corporation monograph series. 606 $aSuicide bombings$zIsrael 606 $aTerrorism$zIsrael 606 $aTerrorists$xSuicidal behavior$zIsrael 615 0$aSuicide bombings 615 0$aTerrorism 615 0$aTerrorists$xSuicidal behavior 676 $a363.325/12 700 $aPerry$b Walt L$0904735 702 $aPerry$b Walt L. 712 02$aNaval Research Laboratory (U.S.) 712 02$aRAND Homeland Security and Defense Center. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910993983503321 996 $aPredicting suicide attacks$92023213 997 $aUNINA