Conclusion

Understanding Crime Statistics: Revisiting the Divergence of the NCVS and UCR

Volumn , Issue , 2006, Pages 297-334

  Lynch, James P ^a   Addington, Lynn A ^b  

^a JOHN JAY COLLEGE OF CRIMINAL JUSTICE   (United States)

^b AMERICAN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84927014795     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1017/CBO9780511618543.011     Document Type: Chapter

References (31)

1. Addington, L. A. (2005). “Disentangling the effects of bounding and mobility on reports of criminal victimization.” Journal of Quantitative Criminology 21:321-343.
2. Baumer, E., Felson, R., & Messner, S. (2003). “Changes in police notification for rape.” Criminology 41:841-872.
3. Biderman, A. D., & Cantor, D. (1984, August). “Alongitudinal analysis of bounding, respondent conditioning and mobility as a source of panel bias in the National Crime Survey.” Presented at the American Statistical Association, Social Statistics Section, Philadelphia.
4. Biderman, A. D., Cantor, D., & Reiss, A. J. (1982). “A quasi-experimental analysis of personal victimization in the National Crime Survey.” Proceedings of the American Statistical Association, Section on Survey Methods (pp. 516-521). Washington, DC: American Statistical Association.
5. Biderman, A. D., & Lynch, J. P. (1991). Understanding crime incidence statistics: Why the UCR diverges from the NCS. New York: Springer-Verlag.
6. Blumstein, A., & Wallman, J. (2005). The crime drop in America. New York: Cambridge University Press.
7. Cantor, D., & Lynch, J. P. (2005). “Exploring the effects of changes in design on the analytical uses of the NCVS data.” Journal of Quantitative Criminology 21:293-319.
8. Claritas, Inc. (2005). American Red Cross: Customer segmentation pumps new life into blood donation efforts. San Diego, CA: Author.
9. Currivan, D. B., & Roe, D. J. (2004, May). Using a dualframe sampling design increase the efficiency of reaching population subgroups in a telephone survey. Paper presented at the Annual Meetings of the American Association of Public Opinion Researchers, Phoenix, AZ.
10. Edison Media Research and Mitofsky International. (2004). Evaluation of Edison-Mitofsky Election System 2004. Washington, DC.
11. Henderson, N. (2005, October 8). “Storms took toll on jobs in September: Unemployment rate up to 5.1%.” Washington Post, p. D01.
12. Hubble, D., & Wilder, B. E. (1988). “Preliminary results from the NCVS CATI experiment.” American Statistical Association Proceedings of the Survey Research Section. Washington, DC: American Statistical Association.
13. Kelling, G., & Wilson, J. Q. (1982, March). “Broken windows: The police and public safety.” Atlantic Monthly, pp. 1-10.
14. Kinderman, C., Lynch, J. P., & Cantor, D. (1997). The effects of the redesign on victimization estimates: Data brief. Washington, DC: Bureau of Justice Statistics.
15. Koss, M. (1996). “The measurement of rape victimization in crime surveys.” Criminal Justice and Behavior 23:55-69.
16. Langan, P., & Durose, M. (2004, December). The remarkable drop in crime in New York. Paper presented at the meeting of Italy’s National Institute of Statistics.
17. Lauritsen, J. (2001). “The social ecology of violent victimization: Individual and contextual effects.” Journal of Quantitative Criminology 17:3-32.
18. Lauritsen, J., & Schaum, R. J. (2005). Crime and victimization in the three largest metropolitan areas, 1980—1998. Washington, DC: Bureau of Justice Statistics.
19. Lynch, J. P. (2002). Trends in juvenile offending: An analysis of victim survey data. Washington, DC: Office of Juvenile Justice Delinquency Prevention.
20. Lynch, J., & Jarvis, J. P. (2003, November). Exploring the sources of nonresponse in the Uniform Crime Reports. Paper presented at the Annual Meetings of the American Society of Criminology, Denver, CO.
21. Lynch, J., & Jarvis, J. P. (2005). Towards an error profile of the Uniform Crime Reports: Assessing the magnitude of missing data and the effects of imputation. Unpublished manuscript, John Jay College, New Ybrk.
22. Maltz, M. (1999). Bridging the gaps: Estimating crime rates from police data. Washington, DC: Bureau of Justice Statistics.
23. Mankewi, N. G., & Matthew W. (2004). Dynamic scoring: A back of the envelope guide (Working Paper 11000). Cambridge, MA: National Bureau of Economic Research.
24. McCleary, R., Nienstedt, B. C., & Erven, J. M. (1982). Uniform Crime Reports as organizational outcomes: Three time series experiments. Social Problems 29:361-372.
25. Penick, B., & Owens, M. (1976). Surveying crime. Washington, DC: National Academy Press.
26. Prewitt, K. (2003). Politics and science in census taking. Washington, DC: Population Research Bureau.
27. Robinson, J. P. (1997). Time for life: The surprising way that Americans use their time. College Park: Pennsylvania State University Press.
28. Simmons, J., & Dodd, T. (2003). Crime statistics England and Wales, 2002/2003. London: Home Office.
29. Taylor, R. B. (2001). Breaking away from broken windows: Baltimore neighborhoods and the nationwide fight against crime, grime, fear, and decline. Boulder, CO: Westview Press.
30. Tjaden, P., & Thoennes, N. (1998). Prevalence, incidence and consequences of violence against women: Findings from the National Survey of Violence Against Women. Washington, DC: National Institute of Justice.
31. Wiersema, B., McDowall, D., & Loftin, C. (August, 2000). Comparing metropolitan area estimates of crime from the NCVS and UCR. Paper presented at the Joint Statistical Meetings, American Statistical Association, Indianapolis, Indiana.