CHANCE

, Volume 23, Issue 1, pp 6–15 | Cite as

Fraud in the 2009 presidential election in Iran?

  • Walter R. MebaneJr.
Articles

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Further Reading

  1. Ansari, Ali, Daniel Berman, and Thomas Rintoul. 2009. Preliminary analysis of the voting figures in Iran’s 2009 presidential election. Chatham House, www.chathamhouse.org.uk/publications/papers/view/-/id/755.Google Scholar
  2. Associated Press. 2009. Former leader says Iran trial a sham. August 2.Google Scholar
  3. Bahrampour, Tara. 2009. Militia adds fear to time of unrest. The Washington Post. June 19.Google Scholar
  4. Benjamini, Yoav, and Yosef Hochberg. 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B 57(1):289–300.MATHMathSciNetGoogle Scholar
  5. Bowman, Adrian W., and Adelchi Azzalini. 1997. Applied smoothing techniques for data analysis: The kernel approach with S-Plus illustrations. Oxford: Clarendon Press.MATHGoogle Scholar
  6. Cho, Wendy Tam, and Brian Gaines. 2007. Breaking the (Benford) law: Statistical fraud detection in campaign finance. The American Statistician 61:218–223.CrossRefMathSciNetGoogle Scholar
  7. Erdbrink, Thomas, and William Branigin. 2009. Iran’s leaders warn more election protests will not be tolerated. The Washington Post. June 30.Google Scholar
  8. Erdbrink, Thomas, and William Branigin. 2009. Obama, in boldest terms yet, presses Iran to halt violence against own people. The Washington Post. June 21.Google Scholar
  9. Hill, Theodore P. 1995. A statistical derivation of the significant-digit law. Statistical Science 10:354–363.MATHMathSciNetGoogle Scholar
  10. McCullagh, Peter, and John A. Nelder. 1989. Generalized linear models. New York: Chapman & Hall.MATHGoogle Scholar
  11. Mebane, Walter R. Jr., and Jasjeet S. Sekhon. 2004. Robust estimation and outlier detection for overdispersed multinomial models of count data. American Journal of Political Science 48:392–411.CrossRefGoogle Scholar
  12. Mebane, Walter R. Jr. 2006. Detecting attempted election theft: Vote counts, voting machines, and Benford’s law. Paper prepared for the 2006 Annual Meeting of the Midwest Political Science Association, Chicago.Google Scholar
  13. Mebane, Walter R. Jr. 2006. Election forensics: Vote counts and Benford’s law. Paper prepared for the 2006 Summer Meeting of the Political Methodology Society, University of California-Davis.Google Scholar
  14. Mebane, Walter R. Jr. 2006. Election Forensics: The Second-digit Benford’s law test and recent American presidential elections. Paper prepared for the Election Fraud Conference, Salt Lake City.Google Scholar
  15. Mebane, Walter R. Jr. 2007. Election forensics: Statistics, recounts, and fraud. Paper presented at the 2007 Annual Meeting of the Midwest Political Science Association, Chicago.Google Scholar
  16. Mebane, Walter R. Jr. 2007. Evaluating voting systems to improve and verify accuracy. Paper presented at the 2007 Annual Meeting of the American Association for the Advancement of Science, San Francisco, and the Bay Area Methods Meeting, Berkeley.Google Scholar
  17. Mebane, Walter R. Jr. 2007. Statistics for digits. Paper presented at the 2007 Summer Meeting of the Political Methodology Society, Pennsylvania State University.Google Scholar
  18. Mebane, Walter R. Jr. 2008. Election forensics: The second-digit Benford’s law test and recent American presidential elections. In The Art and Science of Studying Election Fraud: Detection, Prevention, and Consequences, ed. R. Michael Alvarez, Thad E. Hall, and Susan D. Hyde. Washington, DC: Brookings Institution.Google Scholar
  19. Mebane, Walter R. Jr. 2009. Note on the presidential election in Iran, www.umich.edu/~wmebane/note29jun2009.pdf.Google Scholar
  20. Mebane, Walter R. Jr., and Kirill Kalinin. 2009. Comparative election fraud detection. Paper presented at the 2009 Annual Meeting of the Midwest Political Science Association, Chicago.Google Scholar
  21. Press TV. 2009. Guardian council: Over 100% voted in 50 cities. Associated Press. June 21.Google Scholar
  22. R Development Core Team. 2009. R: A Language and Environment for Statistical Computing. http://cran.r-project.org/doc/manuals/refman.pdf.
  23. Rodriguez, Ricardo J. 2004. First significant digit patterns from mixtures of uniform distributions. The American Statistician 58:64–71.MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© American Statistical Association 2010

Authors and Affiliations

  • Walter R. MebaneJr.

There are no affiliations available

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