Alexander, J (2009). Remarks on the use of Benford's law. Social Science Research Network (November 13, 2009). Available at SSRN: http://ssrn.com/abstract=1505147 or . DOI:10.2139/ssrn.1505147.





Beber, B and Scacco, A (2012). What the Numbers Say: A DigitBased Test for Election Fraud. Political Analysis 20 (2), pp. 211234. DOI:10.1093/pan/mps003.





Breunig, C and Goerres, A (2011). Searching for Electoral Irregularities in an Established Democracy: Applying Benford’s Law Tests to Bundestag Elections in Unified Germany. Electoral Studies 30(3) September 2011, pp. 534545.





Buttorff, G (2008). Detecting fraud in America's gilded age. Working Paper No. 2, University of Iowa, 2008,
Cal Tech/MIT Voting Technology Project (website).





Cantu, F and Saiegh, SM (2011). Fraudulent Democracy? An Analysis of Argentina’s Infamous Decade Using Supervised Machine Learning. Political Analysis (Autumn 2011) 19 (4): 409433; doi:10.1093/pan/mpr033.





Cournane, S, Sheehy, N and Cooke, J (2014). The novel application of Benford's second order analysis for monitoring radiation output in interventional radiology. Physica Medica 30(4), pp. 413–418. DOI:10.1016/j.ejmp.2013.11.004.





Cuff, V , Lewis, A and Miller, SJ (2009). The Weibull distribution and Benford’s law. Preprint.





Deckert, J, Myagkov, M and Ordeshook, PC (2010). The Irrelevance of Benford's Law for Detecting Fraud in Elections. CALTECH working paper 9.





Deckert, J, Myagkov, M and Ordeshook, PC (2011). Benford's Law and the Detection of Election Fraud. Political Analysis 19(3), pp. 245268.





Docampo, S, del Mar Trigo, M, Aira, M, Cabezudo, B and FloresMoya, A (2009). Benford’s law applied to aerobiological data and its potential as a quality control tool . Aerobiologia 25, 275283 . ISSN/ISBN:03935965.





Jang, D, Kang, JU, Kruckman, A, Kudo, J and Miller, SJ (2008). Chains of distributions, hierarchical Bayesian models and Benford's Law. Journal of Algebra, Number Theory: Advances and Applications 1(1), pp. 3760.





Leemann, L and Bochsler, D (2014). A systematic approach to study electoral fraud. Electoral Studies, Vol. 35, Num. 0, pp. 3347. ISSN/ISBN:02613794. DOI:10.1016/j.electstud.2014.03.005.





Mebane, WR Jr (2007). Statistics for digits. 2007 Summer Meeting of the Political Methodology Society, Penn State University, University Park, PA.





Mebane, WR Jr (2007). Election Forensics: Statistical Interventions in Election Controversies. Prepared for presentation at the 2007 Annual Meeting of the American Political Science Association, Chicago, August 30–Sept 2.





Mebane, WR Jr (2008). Election Forensics: Outlier and Digit Tests in America and Russia. Prepared for presentation at The American Electoral Process conference, Center for the Study of Democratic Politics, Princeton University, May 13, 2008.





Mebane, WR Jr (2009). Note on the presidential election in Iran, June 2009. updated notes on author's website.





Mebane, WR Jr (2010). Fraud in the 2009 presidential election in Iran?. Chance 23(1), pp. 615. DOI:10.1080/09332480.2010.10739785.





Mebane, WR Jr (2010). Election Fraud or Strategic Voting? Can Seconddigit Tests Tell the Difference?. Prepared for Presentation at the 2010 Summer Meeting of the Political Methodology Society. University of Iowa.





Mebane, WR Jr (2011). Comment on “Benford's Law and the Detection of Election Fraud”. Political Analysis 19(3), pp. 269272. DOI:10.1093/pan/mpr024.





Miller, SJ and Nigrini, MJ (2008). Order Statistics and Benford's Law. International Journal of Mathematics and Mathematical Sciences, Art. ID 382948, 19 pp.. ISSN/ISBN:01611712. DOI:10.1155/2008/382948.





Nebel, JC and Pezzulli, S (2012). Distribution of Human Genes Observes Zipf's Law. Kingston University Research & Innovation Reports (KURIR), Vol. 8, 2012. ISSN/ISBN:17495652.





Shikano, S and Mack, V (2011). When does 2nd Digit Benford´s LawTest signal an election fraud? Facts or misleading test results. Jahrbücher für Nationalökonomie und Statistik 231 (5+6), 719732.




