Research summary
Understanding the real-world impact of health interventions requires the use of advanced statistical methods that can account for complex data structures. As Canada Research Chair in Causal Inference and Machine Learning in Health Science, Dr. Mireille Schnitzer is developing advanced statistical methods that can help determine whether medical treatments cause improvements in health or are merely associated with them.
She and her research team are working on statistical tools for analyzing complex study designs related to epidemiology (the study of the incidence, distribution and control of diseases). By developing better ways to estimate the true impacts of treatments and identify important patient differences, their research will lead to more accurate, unbiased assessments of how medical interventions actually affect health outcomes. Ultimately, it will drive innovation in statistical theory and software, enabling more reliable decision-making in health policy and medical treatment.