Méthode scientifique – Bibliographie

Meng Cai, Chunbing Bao, Qingchun Meng, Overview of risk aggregation approach in different risk scenarios, Procedia Computer Science, Volume 214, 2022, Pages 1353-1360, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2022.11.316.

Einav S, O’Connor M. P-values and significance: The null hypothesis that they are not related is correct. J Crit Care. 2019 Dec;54:159-162.

Colquhoun D. The reproducibility of research and the misinterpretation of p-values. R Soc Open Sci. 2017 Dec 6;4(12):171085. Erratum in: R Soc Open Sci. 2018 Mar 7;5(3):180100.

Marino MJ. How often should we expect to be wrong? Statistical power, P values, and the expected prevalence of false discoveries. Biochem Pharmacol. 2018 May;151:226-233.

Bell RJ. What is wrong with the medical literature? Climacteric. 2017 Feb;20(1):22-24.

Ioannidis JP. Why Most Clinical Research Is Not Useful. PLoS Med. 2016 Jun 21;13(6):e1002049.

Greenland S et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016 Apr;31(4):337-50.

Goodman S. A dirty dozen: twelve p-value misconceptions. Semin Hematol. 2008 Jul;45(3):135-40. Erratum in: Semin Hematol. 2011 Oct;48(4):302.

Chen, Henian, Patricia Cohen and Sophie Chen. “How Big is a Big Odds Ratio? Interpreting the Magnitudes of Odds Ratios in Epidemiological Studies.” Communications in Statistics – Simulation and Computation 39 (2010): 860 – 864.

Roberts P, Priest H. Reliability and validity in research. Nurs Stand. 2006 Jul 12-18;20(44):41-5.

Ioannidis JP. Why most published research findings are false. PLoS Med. 2005 Aug;2(8):e124.

Colhoun HM et al. Problems of reporting genetic associations with complex outcomes. Lancet. 2003 Mar 8;361(9360):865-72.

Ioannidis JP. Genetic associations: false or true? Trends Mol Med. 2003 Apr;9(4):135-8.Sterne JA, Davey Smith G. Sifting the evidence-what’s wrong with significance tests? BMJ. 2001 Jan 27;322(7280):226-31.

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