null Michal Abrahamowicz, PhD
biostatistics • cohort studies • comparative effectiveness • confounding • instrumental variables • non-parametric regression • pharmaco-epidemiology • splines • statistical modeling • survival analysis
My research focuses on the development of new and flexible methods for the analysis of clinical and biomedical data, in particular of survival analysis, and on their applications in the studies of safety and effectiveness of drugs and treatments, cancer, arthritis and cardiovascular epidemiology.
My research activities combine development of new statistical models for survival analysis and longitudinal population-based analyses of human health with collaborative research in which these new methods are applied in real-life clinical and epidemiological studies. The main objectives of my fundamental research in statistical methodology are the modeling of time-varying and cumulative effects of risk/prognostic factors and treatments, and correcting for different biases inherent in observational (non-randomized) studies. I am a co-founder and, since 2013, the co-Chair of the international STRATOS initiative for improving the analyses of observational studies (www.stratos-initiative.org), involving more than 100 experts in different areas of statistics from 18 countries. My collaborative research includes large clinical trials and longitudinal population-based studies of arthritis, cardiovascular diseases and cancer, as well as pharmacoepidemiology. I created and have been the nominated principal investigator (2011-2019) of the CAN-AIM network for prospective studies of drug safety and effectiveness. Funded by the Drug Safety and Effectiveness Network of the Canadian Institutes for Health Research, CAN-AIM brings together over 45 faculty members from 12 universities across Canada.
Click on to see my current publications list
Chaillet N, Dumont A, Abrahamowicz M, Pasquier JC, Audibert F, Monnier P, Abenhaim HA, Dubé E, Dugas M, Burne R, Fraser WD; for the QUARISMA Trial research group. A cluster-randomized trial for safely reducing caesarean in Québec. N Engl J Med (NEJM). 2015 Apr;372:1710-1721.
Wynant W, Abrahamowicz M. Flexible estimation of survival curves conditional on non-linear and time-dependent predictor effects. Stat Med. 2016 Feb;35(4):553-65.
Abrahamowicz M, Bjerre L, Beauchamp M-E, LeLorier J, Burne R. The missing cause approach to unmeasured confounding in pharmacoepidemiology. Stat Med. 2016 Mar;35(7):1001-16.
Danieli C, Abrahamowicz M. Competing risks modelling of cumulative effects of time-varying drug exposures. Stat Methods Med Res. 2019 Jan;28(1):248-262.
Burne R, Abrahamowicz M. Adjustment for time-dependent unmeasured confounders in marginal structural Cox models using validation sample data. Stat Methods Med Res. 2019 Feb;28(2):357-371.