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

Balashov, VS, Yan, Y and Zhu, X (2020). Who Manipulates Data During Pandemics? Evidence from Newcomb-Benford Law. Preprint arXiv:2007.14841 [econ.GN]; last accessed March 10, 2021. | ||||

Balashov, VS, Yan, Y and Zhu, X (2021). Using the Newcomb–Benford law to study the association between a country’s COVID-19 reporting accuracy and its development. Scientific Reports 11, pp. 22914. DOI:10.1038/s41598-021-02367-z. | ||||

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. | ||||

Bond, KD, Conrad, CR, Moses, D and Simmons, JW (2021). Detecting anomalies in data on government violence. Political Science Research and Methods, pp. 1-8. DOI:10.1017/psrm.2021.40. | ||||

Campanelli, L (2022). On the Euclidean distance statistic of Benford’s law. Communications in Statistics - Theory and Methods, pp. 1-24. DOI:10.1080/03610926.2022.2082480}. | ||||

Campanelli, L (2022). A Statistical Cryptanalysis of the Beale Ciphers. Cryptologia. DOI:10.1080/01611194.2022.2116614. | ||||

Campanelli, L (2022). Testing Benford's Law: from small to very large data sets. Spanish Journal of Statistics 4(1), pp. 41-54. DOI:10.37830/SJS.2022.1.03. | ||||

Campanelli, L (2022). Breaking Benford’s law: A statistical analysis of Covid-19 data using the Euclidean distance statistic. Preprint submitted to Statistics in Transition. | ||||

Campanelli, L (2022). Tuning up the Kolmogorov-Smirnov test for testing Benford’s law. Preprint on ResearchGate. | ||||

Cerasa, A (2022). Testing for Benford’s Law in very small samples: Simulation study and a new test proposal. PLoS ONE 17(7), pp. e0271969. DOI:10.1371/journal.pone.0271969. | ||||

Dang, CT, Burger, R and Owens, T (2019). Do better-performing nongovernmental organizations report more accurately? Evidence from financial accounts in Uganda. 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; published (2020) in Journal of Economic Behavior & Organization 172, pp. 314–343. | ||||

Davic, RD (2022). Correspondence of Newcomb-Benford law with ecological processes . Posted on bioRxiv preprint server of Cold Springs Harbor Laboratory June 27, 2022 . DOI:10.1101/2022.06.27.497806. | ||||

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]. Published in Mathématiques appliquées et stochastiques, 3(1). FRE | ||||

Eutsler, J, Harris, MK, Williams, LT and Cornejo, OE (2023). Accounting for partisanship and politicization: Employing Benford's Law to examine misreporting of COVID-19 infection cases and deaths in the United States. Accounting, Organizations and Society, in press. DOI:10.1016/j.aos.2023.101455. | ||||

Farhadi, N and Lahooti, H (2022). Forensic Analysis of COVID-19 Data from 198 Countries Two Years after the Pandemic Outbreak. COVID 2(4), pp. 472-484. DOI:10.3390/covid2040034. | ||||

Giannakis, N and Burlac, L (2021). Benford’s Law: Analysis of the trustworthiness of COVID-19 reporting in the context of different political regimes. Bachelor’s Degree Project in Mathematics, Division of Mathematics and Physics Mälardalen University, Sweden. | ||||

Herbst, IW, Møller, J and Svane, AM (2023). How many digits are needed?. Preprint arXiv:2307.06685 [math.PR]; last accessed July 30, 2023. | ||||

Horton, J, Kumar, DK and Wood, A (2020). Detecting academic fraud using Benford law: The case of Professor James Hunton. Research Policy 49(8), 104084 . DOI:10.1016/j.respol.2020.104084. | ||||

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. | ||||

Koch, C and Okamura, K (2020). Benford's Law and COVID-19 Reporting. Posted on SSRN April 28, 2020; last accessed November 17, 2020. Published in Econ Lett 2020;196(109973) . | ||||

Kössler, W, Lenz, H-J and Wang, XD (2021). Is the Benford Law Useful for Data Quality Assessment?. In: Knoth, S., Schmid, W. (eds) Frontiers in Statistical Quality Control 13. ISQC 2019, Springer, Cham, pp. 391-406. ISSN/ISBN:978-3-030-67856-2. DOI:10.1007/978-3-030-67856-2_22. | ||||

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. | ||||

McCarville, D (2021). A data transformation process for using Benford’s Law with bounded data. Preprint [version 1; peer review: awaiting peer review], Emerald Open Research 3(29). DOI:10.35241/emeraldopenres.14374.1. | ||||

McDonald, BD and Goodman, CB (2020). The Truth about Honesty in the Nonprofit Sector. SocArXiv 48g5c, Center for Open Science. DOI:10.31219/osf.io/48g5c. | ||||

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. | ||||

Patel, PC, Tsionas, MG and Guedes, MJ (2022). Benford's law, small business financial reporting, and survival. Managerial and Decision Economics. DOI:10.1002/mde.3595. | ||||

Starunova, OA, Rudney, SG, Ivanova, AE, Semenova, VG and Starodubov, VI (2022). Application of Benford's Law for Quality Assessment of Preventive Screening Data. Mathematical Biology and Bioinformatics 17(2), pp. 230-249. DOI:10.17537/2022.17.230. RUS | ||||

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. | ||||

Vovor-Dassu, KC (2021). Tests d'adéquation à la loi de Newcomb-Benford comme outils de détection de fraudes. PhD Thesis L’Universite de Montpellier. DOI:10.13140/RG.2.2.12559.25764. FRE | ||||

Zdraveski, D, Janeska, M and Avramovski, P (2022). Determination of the Reliability of Covid-19 Data in the Republic of North Macedonia Using Benford’s law. EC Pulmonology and Respiratory Medicine 11(1), pp. 31-46. |