Kilani, A (2021). Authoritarian regimes' propensity to manipulate Covid-19 data: a statistical analysis using Benford's Law. Commonwealth & Comparative Politics 59(3), pp. 318-333.
This work is cited by the following items of the Benford Online Bibliography:
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Agyemang, EF, Mensah, JA and Nyarko, E (2023). How dependable is World Continental COVID-19 data? Disclosure of Inconsistencies in Daily Reportage Confirmed Cases, Recovered and Deaths During First Wave. Preprint – submitted to Heliyon. DOI:10.2139/ssrn.4516032.
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Atakan, S and Orman, G (2023). On the usage of Benford’s Law on coronavirus data statistics. Proceedings of 2023 IEEE International Conference on Big Data (BigData), pp. 4848-4853. DOI:10.1109/BigData59044.2023.10386606.
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Etim, ES, Daferighe, EE, Inyang, AB and Ekikor, ME (2023). Application of Benford’s Law and the Detection of Accounting Data Fraud in Nigeria. International Journal of Auditing and Accounting Studies 5(2) pp. 119-163. DOI:10.47509/IJAAS.2023.v05i02.01.
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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.
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Kilani, A (2021). An interpretation of reported COVID-19 cases in post-Soviet states. Journal of Public Health, fdab091. DOI:10.1093/pubmed/fdab091.
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Kolias, P (2022). Applying Benford’s law to COVID-19 data: the case of the European Union. Journal of Public Health 44(2), pp. e221-e226. DOI:10.1093/pubmed/fdac005.
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Us, D (2021). Benford's Law: An Empirical Analysis of Reported Covid-19 Cases and Institutional Structures Around the Globe
. Undergraduate Thesis, Università commerciale Luigi Bocconi, Milan. DOI:10.13140/RG.2.2.28839.88488.
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