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A Comparison of Ideologically-Motivated Homicides from the New Extremist Crime Database and Homicides from the Supplementary Homicide Reports Using Multiple Imputation by Chained Equations to Handle Missing Values

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Abstract

This study took advantage of the new open-source Extremist Crime Database (ECDB) to overcome obstacles to studying domestic far-right terrorism from a criminological perspective. In the past, exclusive definitions and inclusion criteria have limited available data on violent crimes committed by domestic far-right terrorists, and official data on violent crimes fail to capture offenders’ links to domestic far-right terrorism and ideological motivation (e.g., anti-government, anti-abortion, anti-religion). Therefore, little is known about the nature of far-right terrorist violence and how such violence is similar to and different from routine or more common forms of violence. Focusing on homicides, this study addressed why and how open-source terrorism data and official crime data can be comparatively analyzed. In doing so, we also demonstrate the utility of synthesizing terrorism and official crime data sources. Data on 108 far-right terrorist homicides were taken from the ECDB. Data on 540 common homicides (five comparison homicides for each far-right terrorist homicide) were randomly sampled from the 2000 Supplementary Homicide Reports. Using multiple imputation by chained equations and logistic regression, we imputed missing values and estimated models to compare the two homicide types on 12 different victim, offender, and event characteristics. Relative to common homicides, we found that far-right terrorist homicides were significantly more likely to have white offenders, multiple victims, multiple offenders, and to occur between strangers, and they were significantly less likely to have white victims, to be carried out with a firearm, and to occur in cities with more than 100,000 residents.

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Notes

  1. This research was supported by the United States Department of Homeland Security through the National Consortium for the Study of Terrorism and Responses to Terrorism (START), grant number N00140510629. Any opinions, findings, and conclusions or recommendations in this document are those of the authors and do not necessarily reflect views of the US Department of Homeland Security.

  2. Although not a focus of the current study, the ECDB Project is collecting open-source data for other domestic extremist crimes including bombings and arsons committed by animal and environmental extremists, as well as homicides, attempted homicides, and bombing plots by homegrown jihadists.

  3. The RAND-MIPT Terrorism Incident Database Project has been subsumed by the RAND Database of Worldwide Terrorism Incidents (http://www.rand.org/nsrd/projects/terrorism-incidents/).

  4. Though having multiple research assistants involved in data coding process is advantageous in regards to efficiency, there may be legitimate concerns over the inter-rater reliability. There were a number of ways in which this study ensured successful inter-rater reliability among open-source data coders for the ECDB project. First, all went through extensive training on the coding process for each variable. Each new coder entered into a probationary status in which he or she coded a number of duplicate cases as seasoned coders for the purposes of comparison. In this way, any inconsistencies were addressed early in the coding process. Second, each codebook includes a variable to capture specific coders’ names. Therefore, this study was able to explore over time the data for abnormalities across data coders. Third, open-source coding occurred in stages, which increased the chances that all available information from open sources was captured. After open-source data collectors compiled search reports on each case, data collectors conducted target searches based on information uncovered during the initial search. This presented the continued opportunity for coders to recheck their past work, as well as the work of fellow open-source coders.

    Often filling in values for variables included in the current study required little interpretation by coders because the variables captured the basic facts of each fatal crime. Nonetheless, it remains important to constantly track the level of coding reliability over time. The ECDB presents a good opportunity to comparatively examine the quality of coding for the 108 ideologically motivated far-right extremist homicides. Data for these homicides were originally coded in early 2008 primarily by three research assistants. However, in 2010 all of the homicide variables included in this study were reviewed and, if necessary, recoded by a new coder. In this way, a new coder was able to update the homicide cases based on newly available information and catch any coding errors by the original coder. The coding of variables was compared across coders and the rate of coder agreement was calculated across the initial and secondary coding stages for each variable, including suspect age (93%), suspect race (100%), suspect gender (100%), weapon (100%), number of suspects (97%), number of deaths (98%), region (state) (99%), and population (city size) (93%). In effect, inter-rater reliability across coders was not deemed a threat to the quality of far-right extremist homicide data.

  5. The total number of far-right ideological (and non-ideological) homicides used in the current study differ slightly from those used by Chermak et al. (this issue) because in our analysis, for the purposes of comparison with SHR data, we selected only the first victim and offender dyad in those homicides involving multiple victims. In addition, late in the process of our analysis it was discovered that four far-right terrorist homicide events had inadvertently failed to be transferred from the ECDB to our list of homicides. Though we did not add a further five common comparison homicides from the 2000 SHR for each of these new homicides, we did add the four new ideological homicides to our database and reestimated the model. The addition of these cases had no tangible effect on the size of the odds ratios and no impact on the inferences drawn from the results shown in Table 4.

  6. While the number of homicides in the SHR would allow us to provide a much larger comparison group than we have selected, any incremental benefits in statistical power gained from adding additional controls diminishes rapidly beyond about three cases per control (Breslow 1982), and going beyond five controls per case provides no useful increase in precision.

  7. The Census West includes Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

  8. Several of the 28 missing observations on the white variable from the ECDB were Hispanic, but it was unknown whether they were white Hispanic or black Hispanic. In order to remain consistent with comparison cases from the SHR—which classifies victims as white, black, Native American, or Asian, with a separate field for Hispanic ethnicity for whites and blacks—we classified as missing any cases in which the person was Hispanic but it was unknown whether they were white or black.

  9. See Rubin (1987) for more information about FMI; White et al. (2011) for using the FMI to determine the appropriate number of imputations to carry out; and Wagner (2010) for a discussion of employing the FMI as a tool for gauging the quality of survey data.

  10. Whereas the EM approach is based on maximum-likelihood estimates that describe a likelihood function that is averaged over a predictive distribution for the missing values, multiple imputation employs the same type of averaging but uses Monte Carlo methods.

References

  • Aho JA (1990) The politics of righteousness: Idaho Christian patriotism. University of Washington Press, Seattle

    Google Scholar 

  • Barkun M (1997) Religion and the racist right: the origins of the Christian Identity movement, 2nd edn. University of North Carolina Press, Chapel Hill

    Google Scholar 

  • Berlet C, Lyons MN (2000) Right-wing populism in America: too close for comfort. The Guilford Press, New York

    Google Scholar 

  • Borgeson K, Valeri R (eds) (2009) Terrorism in America. Jones and Bartlett Publishers, Sadbury

    Google Scholar 

  • Bradley-Engen MS, Damphousse KR, Smith BL (2009) Punishing terrorists: a re-examination of US federal sentencing in the postguidelines era. Int Crim Justice Rev 19:433–455

    Article  Google Scholar 

  • Brearly HC (1932) Homicide in the United States. North Carolina Press, Chapel Hill

    Google Scholar 

  • Breslow N (1982) Design and analysis of case-control studies. Annu Rev Public Health 3:29–54

    Article  Google Scholar 

  • Chermak SM, Freilich JD, Shemtob Z (2009) Law enforcement training and the domestic far right. Crim Justice Behav 36(12):1305–1322

    Article  Google Scholar 

  • Decker SH (1993) Exploring victim-offender relationships in homicide: the role of individual and event characteristics. Justice Q 10:585–612

    Article  Google Scholar 

  • Decker SH, Curry GD (2002) Gangs, gang homicides, and gang loyalty: organized crimes or disorganized criminals. J Crim Justice 30:343–352

    Article  Google Scholar 

  • Deflem M (2004) Terrorism and counter-terrorism: criminological perspectives. Elsevier/JAI Press, Amsterdam

    Google Scholar 

  • Emerson S (2002) American jihad: the terrorists living among us. The Free Press, New York

    Google Scholar 

  • Federal Bureau of Investigation (FBI) (2004) Crime in the United States, 2004. United States Department of Justice: Federal Bureau of Investigation

  • Federal Bureau of Investigation (FBI) (2006) Terrorism in the United States, 2003. United States Department of Justice: Federal Bureau of Investigation, Washington

    Google Scholar 

  • Federal Bureau of Investigation (FBI) (2009) Uniform Crime Report Hate Crime Statistics, 2008. United States Department of Justice: Federal Bureau of Investigation, Washington

    Google Scholar 

  • Ferber A (1998) White man falling: race, gender, and white supremacy. Rowman & Littlefield Publishers, Lanham

    Google Scholar 

  • Flewelling RL (2004) A non-parametric imputation approach for dealing with missing variables in supplementary homicide record (SHR) data. Homicide Stud 8:255–266

    Article  Google Scholar 

  • Flewelling RL, Williams KR (1999) Categorizing homicides. In: Smith MD, Zahn MA (eds) Homicide, a sourcebook of social research. Sage Publications, Thousand Oaks, pp 96–106

    Google Scholar 

  • Freilich JD (2003) American militias: state-level variations in militia activities. LFB Scholarly Publishing LLC, New York

    Google Scholar 

  • Freilich JD, Chermak SM (2007) Final DHS summer faculty and student research team grant report: creation of a database of US extremist crime, 1995–2005. Department of Homeland Security, Science and Technology Directorate, Washington

    Google Scholar 

  • Freilich JD, Chermak SM (2009) Extremist Crime Database (ECDB): 1990–2008: preliminary results. Paper presented at the annual Department of Homeland Security University Network Research and Education Summit, Washington

    Google Scholar 

  • Freilich JD, Chermak SM, Simone J (2009) Surveying American state police agencies about terrorism threats, terrorism sources, and terrorism definitions. Terror Political Sci 21:450–475

    Google Scholar 

  • Garofalo J, Martin SE (1993) Bias-motivated crimes: the law enforcement response. Center for the Study of Crime, Delinquency, and Corrections, Carbondale

    Google Scholar 

  • Global Terrorism Database (2010) The global terrorism database. Retrieved from http://www.start.umd.edu/gtd/

  • Graham JW, Olchowski AE, Gilreath TD (2007) How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci 8:206–213

    Article  Google Scholar 

  • Gruenewald J (2011) A comparative examination of homicides perpetrated by far-right extremists. Homicide Stud 15(2):177–203

    Article  Google Scholar 

  • Gruenewald JA, Pridemore WA (2009) Stability and change in homicide victim, offender, and event characteristics in Chicago, 1900 and 2000. Homicide Studies 13:355–384

    Article  Google Scholar 

  • Gruenewald JA, Freilich JD, Chermak SM (2009) A review of the far-right extremism literature. In: Blazak R, Perry B (eds) Hate crime issues and perspectives (1–21). Praeger, Westport

    Google Scholar 

  • Hamm MS (1993) American skinheads: the criminology and control of hate crime. Praeger, Westport

    Google Scholar 

  • Hewitt C (2003) Understanding terrorism in America. Routledge, New York

    Google Scholar 

  • Hoffman FL (1925) The homicide problem. Prudential Press, Newark, NJ

    Google Scholar 

  • Journal of Quantitative Criminology (1999) Special issue on the “National Incident-Based Reporting System”. J Quant Criminol 15:115–248

    Article  Google Scholar 

  • Kaplan J (1995) Right wing violence in North America. Terror Political Sci 7:44–95

    Google Scholar 

  • LaFree G, Dugan L (2004) How does studying terrorism compare to studying crime? Sociol Crime Law Deviance 5:53–74

    Article  Google Scholar 

  • Last JM (1995) A dictionary of epidemiology, 3rd edn. Oxford University Press, New York

    Google Scholar 

  • Legault RL, Hendrickson JC (2009) Weapon choice and American political violence: a comparison of terrorists and other felons in federal custody. Criminol Public Policy 8(3):531–559

    Article  Google Scholar 

  • Levin J, McDevitt J (1993) Hate crimes: the rising tide of bigotry and bloodshed. Plenum, New York

    Google Scholar 

  • Little RJA, Rubin DB (2002) Statistical analysis with missing data, 2nd edn. Wiley-InterScience, Hoboken

    Google Scholar 

  • Maxson CL, Gordon MA, Klein MW (1985) Differences between gang and nongang homicides. Criminology 23:209–222

    Article  Google Scholar 

  • Maxson CL, Klein MW, Sternheimer K (2002) Homicide in Los Angeles: an analysis of the differential character of adolescent and other homicides. Final Report for United States Department of Justice Grant 97-IJ-CX-0018. Available online at www.ncjrs.gov/pdffiles1/nij/grants/193812.pdf

  • Maxwell C, Maxwell SR (1995) Youth participation in hate-motivated crimes: research and policy implications. Center for the Study and Prevention of Violence, Boulder

    Google Scholar 

  • McCarthy N, Giesecke J (1999) Case-case comparisons to study causation of common infectious diseases. Int J Epidemiol 28:764–768

    Article  Google Scholar 

  • Messner SF, Deane G, Beaulieu M (2002) A log-multiplicative association model for allocating homicides with unknown victim-offender relationships. Criminology 40:457–479

    Article  Google Scholar 

  • Messner S, McHugh S, Felson R (2004) Distinctive characteristics of assaults motivated by bias. Criminology 42:585–618

    Article  Google Scholar 

  • Pampel FC, Williams KR (2000) Intimacy and homicide: compensating for missing data in the SHR. Criminology 38:661–680

    Article  Google Scholar 

  • Pizarro JM, McGloin JM (2006) Explaining gang homicides in Newark, New Jersey: collective behavior or social disorganization? J Crim Justice 34:195–207

    Article  Google Scholar 

  • Pridemore WA, Eckhardt K (2008) A comparison of victim, offender, and event characteristics of alcohol- and non-alcohol-related homicides. J Res Crime Delinq 45:227–255

    Article  Google Scholar 

  • Pridemore WA, Chamlin MB, Trahan A (2008) A test of competing hypotheses about hypotheses about homicide following terrorist attacks: an interrupted time series analysis of September 11 and Oklahoma City. J Quant Criminol 24:381–396

    Article  Google Scholar 

  • Regoeczi WC, Riedel M (2003) The application of missing data estimation models to the problem of unknown victim/offender relationships in homicide cases. J Quant Criminol 19:155–183

    Article  Google Scholar 

  • Rosenfeld R, Bray TM, Egley A (1999) Facilitating violence: a comparison of gang- motivated, gang-affiliated, and nongang youth homicides. J Quant Criminol 15:495–516

    Article  Google Scholar 

  • Royston P (2004) Multiple imputation of missing values. Stata J 4:227–241

    Google Scholar 

  • Royston P (2009) Multiple imputation of missing values: further update of ice, with an emphasis on categorical variables. Stata J 9:466–477

    Google Scholar 

  • Royston P, Carlin JB, White IR (2009) Multiple imputation of missing values: new features for mim. Stata J 9:252–264

    Google Scholar 

  • Rubin DB (1987) Multiple imputation for non-response in surveys. Wiley, New York

    Book  Google Scholar 

  • Schmid AP (2004) Frameworks for conceptualizing terrorism. Terror Political Violence 16:197–221

    Article  Google Scholar 

  • Schmid AP, Jongman AJ (1988) Political terrorism: a new guide to actors, authors, concepts, databases, theories and literature. North-Holland Publishing Company, Amsterdam

    Google Scholar 

  • Shields CA, Damphousse KR, Smith BL (2006) Their day in court: assessing guilty plea rates among terrorists. J Contemp Crim Justice 22:261–276

    Article  Google Scholar 

  • Silke A (1996) Terrorism and the blind men’s elephant. Terror Political Violence 8:12–28

    Article  Google Scholar 

  • Silke A (2001) The devil you know: continuing problems with research on terrorism. Terror Political Violence 13:1–14

    Article  Google Scholar 

  • Smith B (1994) Terrorism in America: pipe bombs and pipe dreams. State University of New York Press, Albany

    Google Scholar 

  • Smith BL, Damphousse KR (1996) Punishing political offenders: the effect of political motive on federal sentencing decisions. Criminology 34:289–321

    Article  Google Scholar 

  • Smith BL, Damphousse KR (1999) American Terrorism Study: patterns of behavior, investigation and prosecution of American Terrorists. National Criminal Justice Reference Service, Rockville

    Google Scholar 

  • Smith BL, Damphousse KR, Yang S, Ginther C (2005) Prosecuting politically motivated offenders. The impact of the “terrorist” label on criminal case outcomes. Int J Contemp Sociol 42(2):210–216

    Google Scholar 

  • Sutherland EH (1924) Murder and the death penalty. J Am Inst Crim Law Criminol 15:522–529

    Article  Google Scholar 

  • United States Department of Justice (2002) Federal Bureau of investigation. Uniform crime reporting program data [United States]: supplementary homicide reports, 2000 [Computer file]. ICPSR03448-v1. Inter-university Consortium for Political and Social Research [distributor], Ann Arbor. doi:10.3886/ICPSR03448

  • Wadsworth T, Roberts JM Jr (2008) When missing data are not missing: a new approach to evaluating supplemental homicide report imputation strategies. Criminology 46:841–870

    Article  Google Scholar 

  • Wagner J (2010) The fraction of missing information as a tool for monitoring the quality of survey data. Public Opin Q 74:223–243

    Article  Google Scholar 

  • Weinberg L, Pedahzur A, Hirsch-Hoefler S (2004) The challenges of conceptualizing terrorism. Terror Political Violence 16:777–779

    Article  Google Scholar 

  • White IR, Royston P, Wood AM (2011) Multiple imputation using chained equations: issues and guidance for practice. Stat Med 30:377–399

    Article  Google Scholar 

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Acknowledgments

We thank Joshua D. Freilich and Steven M. Chermak for allowing us to use data from the Extremist Crime Database (ECDB). We thank Colin Loftin, Scott Long, and Jim Lynch for advice on the analyses performed here, and Gary LaFree for his helpful comments on an earlier draft.

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Gruenewald, J., Pridemore, W.A. A Comparison of Ideologically-Motivated Homicides from the New Extremist Crime Database and Homicides from the Supplementary Homicide Reports Using Multiple Imputation by Chained Equations to Handle Missing Values. J Quant Criminol 28, 141–162 (2012). https://doi.org/10.1007/s10940-011-9155-5

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