Biostatistical & Computational Methods
Description
Biostatistical and computational methods underpin our quantitative understanding of health. Members of our cluster develop and apply methodology for the design and analysis of trial and observational studies to answer a wide variety of questions in challenging settings where data are difficult to obtain, complex in structure, very noisy, and very large. Our members also develop simulation techniques to help better understand the mechanisms and outcomes that impact health. The methods we develop advance knowledge in subject areas including primary care, public health, addictions and mental health, multimorbidity, LGBTQ2+ health, and many more, by translating raw data into actionable decision support for all levels of the health care system from the clinic to public health to policy.
Vision
To develop and apply biostatistical and computational methods for cutting-edge health problems, thereby generating new knowledge and improving the health of people in Canada and globally.
Goals
- Promoting the strengths and expertise of our group both within Western and abroad.
- Creating a core team with members of the Epidemiological & Observational Studies cluster to look at problems of causality within electronic health record (EHR) data.
