Empirical Assessment of Minimum Clinically Important Differences in Network Meta-Analysis
This research project aims to evaluate the interpretation of network meta-analysis (NMA) results according to different minimal clinically important difference (MCID) thresholds.
Lead: Areti Angeliki Veroniki
Affiliates: Sharon E Straus
Dr. Veroniki is a mathematician, holds an MSc in Statistics and Operations Research, and a PhD in Biostatistics and Epidemiology. She is a Scientist at St. Michael’s Hospital, Unity Health Toronto and a co-Convenor of the Cochrane Statistical Methods Group. Her research interests are in optimizing the processes of evidence-based medicine, and in particular, in the statistical modelling for knowledge synthesis, including network meta-analysis.
- Statistical modelling for standard and network meta-analysis
- Assessing heterogeneity in meta-analysis
- Addressing inconsistency in network meta-analysis
- Modelling treatment dosages and complex interventions in network meta-analysis
- Incorporating diagnostic test accuracy studies in evidence synthesis
Scientist, St. Michael’s Hospital, Unity Health Toronto
Co-convenor, Cochrane Statistical Methods Group