This work is cited by the following items of the Benford Online Bibliography:
Al-Marzouki, S, Evans, S, Marshall, T and Roberts, I (2005). Are these data real? Statistical methods for the detection of data fabrication in clinical trials. Brit. Med. J 331, pp. 267-270. DOI:10.1136/bmj.331.7511.267. | ||||
Arshadi, L and Jahangir, AH (2014). Benford's law behavior of Internet traffic. Journal of Network and Computer Applications, Volume 40, April 2014, pp. 194–205. ISSN/ISBN:1084-8045. DOI:10.1016/j.jnca.2013.09.007. | ||||
Berger, A and Hill, TP (2015). An Introduction to Benford's Law. Princeton University Press: Princeton, NJ. ISSN/ISBN:9780691163062. | ||||
Bolton, RJ and Hand, DJ (2002). Statistical Fraud Detection: a review. Statistical Science 17(3), 235-249. | ||||
Brown, RJC (2005). Benford's Law and the screening of analytical data: the case of pollutant concentrations in ambient air. Analyst 130(9), 1280-1285. ISSN/ISBN:0002-2654. | ||||
Goodman, WM (2013). Reality Checks for a Distributional Assumption: The Case of “Benford’s Law”. JSM Proceedings. Alexandria, VA: American Statistical Association (2013), pp. 2789-2803. (Also published on the Statistical Literacy website, at URL: http://www.statlit.org/pdf/2013-Goodman-ASA.pdf) . | ||||
Orita, M, Hagiwara, Y, Moritomo, A, Tsunoyama, K, Watanabe, T and Ohno, K (2013). Agreement of drug discovery data with Benford's law. Expert Opinion on Drug Discovery 8(1), pp. 1-5. DOI:10.1517/17460441.2013.740007. | ||||
Orita, M, Moritomo, A, Niimi, T and Ohno, K (2010). Use of Benford's law in drug discovery data. Drug Discovery Today, Vol. 15, Nos. 9–10, pp. 328–331. ISSN/ISBN:1359-6446. DOI:10.1016/j.drudis.2010.03.003. | ||||
Schüpfer, G, Hein, J, Casutt, M, Steiner, L and Konrad, C (2012). Vom Finanz- sum Wissenschaftsbetrug [From financial to scientific fraud : methods to detect discrepancies in the medical literature]. Der Anaesthesist 61(6):537-42. ISSN/ISBN:0003-2417. DOI:10.1007/s00101-012-2028-y. GER | ||||
Taylor, RN, McEntegart, DJ and Stillman, EC (2002). Statistical techniques to detect fraud and other data irregularities in clinical questionnaire data. Drug Information Journal 36, 115-125. DOI:10.1177/009286150203600115. |