This work is cited by the following items of the Benford Online Bibliography:

Baryła, M and Pociecha, J (2019). Euclidean distance as a measure of conformity to Benford's law in digital analysis for fraud detection. Book of Short Papers, Proceedings of the 12th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), pp. 75-78. | ||||

Dang, CT, Burger, R and Owens, T (2019). Better Performing NGOs Do Report More Accurately: Evidence from Investigating Ugandan NGO Financial Accounts. Economic Development and Cultural Change, forthcoming. DOI:10.1086/703099. | ||||

Dang, CT and Owens, T (2019). Does transparency come at the cost of charitable services? Evidence from investigating British charities. CREDIT Research Paper 19/02. | ||||

Deleanu, IS (2017). Do Countries Consistently Engage in Misinforming the International Community about Their Efforts to Combat Money Laundering? Evidence Using Benford's Law. PLoS One 12(1), p. e0169632. DOI:10.1371/journal.pone.0169632. | ||||

Druica, E, Oancea, B and Valsan, C (2018). Benford's law and the limits of digit analysis. International Journal of Accounting Information Systems 31, pp. 75–82. DOI:10.1016/j.accinf.2018.09.004. | ||||

Ducharme, RG, Kaci, S and Vovor-Dassu ,C (2020). Smooths Tests of Goodness-of-fit for the Newcomb-Benford distribution. Preprint: arXiv:2003.00520v1 [math.ST]. FRE | ||||

Kienle, S (2015). What Benford Can Tell Us About Cover Pools – An Empirical Analysis. International Business & Economic Research Journal 14(6), pp. 829-834. DOI:10.19030/iber.v14i6.9489. | ||||

Mainusch, NM (2020). On Benford's law - Computing a Bayes factor with the Savage-Dickey method to quantify conformance of numerical data to Benford's law. Bachelor's Thesis, University of Osnabrueck, Institute of Cognitive Science, Germany. | ||||

Palanca, TJ (2014). On Benford's Law: Determining import fraud risk using customs data. Blog posted on tjpalanca.com, November 17, 2014; last accessed Jun 8, 2019. | ||||

Suzuki, T, Kamimasu, T, Nakatoh, T and Hirokawa, S (2018). Identification of Unnatural Subsets in Statistical Data. 7th International Congress on Advanced Applied Informatics (IIAI-AAI), pp. 74-80. DOI:10.1109/IIAI-AAI.2018.00024. |