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.
|
|
|
|
|
Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572.
|
|
|
|
|
Brown, RJC (2005). Benford's Law and the screening of analytical data: the case of pollutant concentrations in ambient air. Analyst 130(9), pp. 1280-1285. ISSN/ISBN:0002-2654. DOI:10.1039/B504462F.
|
|
|
|
|
Brown, RJC (2007). The use of Zipf's law in the screening of analytical data: a step beyond Benford. Analyst 132(4), pp. 344-349. ISSN/ISBN:0003-2654. DOI:10.1039/B618255K.
|
|
|
|
|
Buyse, M, George, SL, Evans, S, Geller, NL, Edler, L and Hutton, J (1999). The Role of Biostatistics in the Prevention, Detection and Treatment of Fraud in Clinical Trials. Statistics in Medicine 18 (24), pp. 3435-3451. ISSN/ISBN:0277-6715. DOI:10.1002/(SICI)1097-0258(19991230)18:24<3435::AID-SIM365>3.0.CO;2-O.
|
|
|
|
|
Hill, TP (1995). A Statistical Derivation of the Significant-Digit Law. Statistical Science 10(4), pp. 354-363. ISSN/ISBN:0883-4237.
|
|
|
|
|
Hill, TP (1999). The difficulty of faking data. Chance 12(3), pp. 27-31. DOI:10.1080/09332480.1999.10542154.
|
|
|
|
|
Hoyle, DC, Rattray, M, Jupp, R and Brass, A (2002). Making sense of microarray data distributions. Bioinformatics 18(4), pp. 576-584. ISSN/ISBN:1367-4803. DOI:10.1093/bioinformatics/18.4.576.
|
|
|
|
|
Newcomb, S (1881). Note on the frequency of use of the different digits in natural numbers. American Journal of Mathematics 4(1), pp. 39-40. ISSN/ISBN:0002-9327. DOI:10.2307/2369148.
|
|
|
|
|
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.
|
|
|
|
|
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.
|
|
|
|
|