Dr. Areti Angeliki Veroniki is a mathematician, holds an MSc in Statistics and Operations Research, and a PhD in Epidemiology. She is a Research Fellow at the University of Ioannina in Greece, a Research Associate Statistician at the Imperial College in London, UK, and an Affiliate Scientist at St. Michael’s Hospital in Toronto, Canada. Her research focuses on the statistical modelling for evidence synthesis and the methodology of systematic reviews. She is a co-Convenor of the Cochrane Statistical Methods Group and an Associate Editor for the BMC Systematic Reviews journal and the BMC Pilot and Feasibility Studies journal.
Dr. Areti Angeliki Veroniki holds a BSc in Mathematics, a MSc in Statistics and Operations Research, and a PhD in Epidemiology from the University of Ioannina in Greece. She completed her PhD entitled “Study of the heterogeneity and inconsistency in networks of interventions” in May 2014 under the supervision of professor Georgia Salanti. She worked as a post-doctoral fellow (July 2014 – July 2017) at St. Michael’s Hospital in Toronto, Canada, under the supervision of Dr. Sharon Straus, and in July 2017 she was appointed as a Scientist. She became an Affiliate Scientist in January 2018, and since June 2018 she has been working as a research fellow at the University of Ioannina in Greece and the Imperial College London in UK.
Dr. Veroniki’s research interests are in optimizing the processes of evidence-based medicine, and in particular, in the statistical modelling for knowledge synthesis. She is interested in enhancing methods for meta-analysis and network meta-analysis with aggregated data and/or individual patient data, as well as in developing models to incorporate dosages and complex interventions in network meta-analysis. She is a co-Convenor of the Cochrane Statistical Methods Group and an Associate Editor for the BMC Systematic Reviews journal and the BMC Pilot and Feasibility Studies journal. She is a Statistical Editor for the Cochrane Depression, Anxiety and Neurosis Group, and the Cochrane Developmental, Psychosocial and Learning Problems Group.
Research Key words
- Evidence synthesis
- Network meta-analysis
- Individual patient data
- Veroniki A.A., Jackson D., Viechtbauer W., Bender R., Bowden J., Knapp G., Kuss O., Higgins J.P.T., Langan D., Salanti G., Methods to calculate uncertainty in the estimated overall effect size from a random-effects meta-analysis. Res. Synth. Meth; 2018; doi: 10.1002/jrsm.1319
- Veroniki A.A., Straus S.E., Rücker G., Tricco A.C., Commentary: Is uncertainty in treatment ranking helpful in a network meta-analysis? J. Clin. Epidemiol; 2018; pii: S0895-4356(17)30801-6
- Veroniki A.A., Cogo E., Rios R., Straus S.E., Finkelstein Y., Kealy R., Reynen E., Soobiah C., Thavorn K., Hutton B., Hemmelgarn B., Yazdi F., D’Souza J., MacDonald H., Tricco A.C. Comparative safety of anti-epileptic drugs during pregnancy: a systematic review and network meta-analysis of congenital malformations and prenatal outcomes. BMC Medicine. 2017; 15: 95. https://doi.org/10.1186/s12916-017-0845-1
- Veroniki A.A., Straus S.E, Soobiah C., Elliott M.J., Tricco A.C., A scoping review of indirect comparison methods and applications using individual patient data. BMC Medical Research Methodology; 2016; 16(47): 1-14
- Veroniki A.A., Straus S.E, Fyraridis A., Tricco A.C., The rank-heat plot is a novel way to present the results from a network meta-analysis including multiple outcomes. J. Clin. Epidemiol.; 2016; 16: 00153-0. doi: 10.1016/j.jclinepi.2016.02.016
- Veroniki A.A., Jackson D., Viechtbauer W., Bender R., Bowden J., Knapp G., Kuss O., Higgins J.P.T., Langan D., Salanti G., Methods to estimate heterogeneity variance and its uncertainty in meta-analysis. Res. Synth. Method; 2016; 7(1); 55-79. doi: 10.1002/jrsm.1164
- Veroniki A.A., Mavridis D., Higgins J.P.T., Salanti G., Characteristics of a loop of evidence that affect detection and estimation of inconsistency: a simulation study. BMC Medical Research Methodology; 2014; 14(106): 12.
- Veroniki A.A., Vasiliadis HS, Higgins J.P.T., Salanti G. Evaluation of inconsistency in networks of interventions. Int J Epidemiol 2013; 42(1):332-345; doi: 10.1093/ije/dys222