A new article entitled "The causal inference paradigm for network meta-analysis with implications for feasibility and practice" is currently available (pre-peer review) on arXiv stat: 
http://arxiv.org/abs/1506.01583

Network meta-analysis involves the aggregation of study results in order to contrast the effects of different treatments for a common condition. While standard meta-analysis only summarizes over one pair of treatment contrasts, network meta-analysis can combine a multitude of different treatments. 

In this article, we define a nonparametric "effect of interest" in a network meta-analysis over heterogeneous underlying populations. We then develop a set of restrictions that allow for estimation of this effect. We propose several estimators and compare their realistic small-sample performance in a simulation study. Finally, we demonstrate this approach in a real data example to evaluate the relative effectiveness of antibiotics on methicillin-resistant Staphylococcus aureus (MRSA) infection.

Je suis très heureuse d'annoncer que j'ai reçu la bourse de carrière Chercheur boursier (Junior 1) du Fonds de recherche du Québec, Santé (FRQS). Le titre de mon programme de recherche est

"Développement de méthodes avancées pour l'évaluation de l'efficacité et de l'innocuité des médicaments utilisant des bases de données électroniques."



I'm very pleased to announce that I received a Research Fellowship from the Fonds de recherche du Québec, Santé (FRQS) under the Chercheur boursier Junior 1 competition. The title of my research program is

"Advanced methods development for the evaluation of medication efficacy and safety using electronic medical databases."

I'm very pleased to announce that my program "Data-adaptive learning in causal inference for high-dimensional data structures" was awarded funding through NSERC's 2015 Discovery Grant and Discovery Grant Accelerator programs.

I am therefore recruiting PhD and/or masters students to begin work on projects related to causal inference in high-dimensional settings, Targeted minimum loss-based estimation for longitudinal data, and causal variable selection. 

Interested students should apply by emailing me a short (but specific) statement of interest and their CV.