Bibliography
- Kahn SD. On the future of genomic data. Science 2011;331:728-9
- Steen RG. Retractions in the scientific literature: is the incidence of research fraud increasing? J Med Ethics 2011;37:249-53
- Buyse M, George SL, Evans S, The role of biostatistics in the prevention, detection and treatment of fraud in clinical trials. Stat Med 1999;18:3435-51
- Taylor R, McEntegart D, Stillman E. Statistical techniques to detect fraud and other data irregularities in clinical questionnaire data. Drug Inform J 2002;36:115-25
- Al-Marzouki S, Evans S, Marshall T, Are these data real? Statistical methods for the detection of data fabrication in clinical trials. BMJ 2005;331:267-70
- Orita M, Moritomo A, Niimi T, Use of Benford's law in drug discovery data. Drug Discov Today 2010;15:328-31
- Newcomb S. Note on the frequency of use of dierent digits in natural numbers. Amer J Math 1881;4:39-40
- Benford F. The law of anomalous numbers. Proc Am Philos Soc 1938;78:551-72
- Hill T. A statistical derivation of the significant-digit law. Stat Sci 1996;10:354-63
- Hill T. The difficulty of faking data. Chance 1999;12:27-31
- Brown RJC. The use of Zipf's law in the screening of analytical data: a step beyond Benford. Analyst 2007;132:344-9
- Brown RJC. Benford's law and the screening of analytical data: the case of pollutant concentrations in ambient air. Analyst 2005;130:1280-5
- Hoyle DC, Rattray M, Jupp R, Making sense of microarray data distributions. Bioinformatics 2002;18:576-84
- Howe JT, Mahieu G, Marichal P, Data reduction and representation in drug discovery. Drug Discov Today 2007;12:45–5