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Biostatistics

What is Biostatistics? The field involves the development and application of statistical methods to scientific research in areas such as medicine, epidemiology, environmental health, genetics, and ecology. Biostatisticians play key roles in designing studies – from helping to formulate the questions that can be answered by data collection to the decisions on how best to collect the data – and in analyzing the resulting data. They also develop new statistical methods for such data.

Career Opportunities: There is a shortage of biostatisticians in Canada, and a large variety of employment opportunities: government (e.g., the Public Health Agency of Canada, Statistics Canada, NRC, Santé Québec, INSPQ, regional departments of public health, health technology assessment units); the pharmaceutical industry and the contract research organizations (CROs) that perform statistical work for industry; academia, including Biostatistics, Epidemiology, and Statistics departments, as well as hospital and other medical research institutes.


Biostatistics at McGill

Situated within the Faculty of Medicine, our department has a long history in epidemiologic and biostatistical research. In 1984, the term Biostatistics was added to the department name to reflect the largest concentration of PhD level statisticians of any such department in Canada. In 1995 we accepted the first students into a Biostatistics 'stream' where the mix of courses was about two thirds biostatistics, one third epidemiology and epidemiologic methods.

The training program for students entering in 2007 has been revised to require increased depth in statistics and to offer a broader array of statistics and biostatistics courses, while maintaining some of the 'statistical methods for epidemiology' strengths of the department. Ultimately, we expect to be able to also provide biostatistical training in emerging areas in other biomedical fields.

Training in Biostatistics is available within two programs: M.Sc. and Ph.D. Students are expected to be full-time unless there is a compelling reason for half- time or part-time status.

Along with courses in mathematical statistics and statistical inference, students will gain experience in applied areas such as statistical methods for epidemiology, generalized linear models, survival analysis, longitudinal data, and clinical trials. Skills in data analysis, statistical consulting, and report writing will be emphasized.

Faculty research areas include survival analysis, non-parametric and semi-parametric modelling, analysis of longitudinal data, causal inference, statistical computing, classification and regression trees, methods for evaluating diagnostic accuracy, Bayesian statistics in medicine, statistical methods for clinical trials, and the design and analysis of epidemiologic studies.

Links to web-pages or research interests of individual faculty members:

Andrea Benedetti
Antonio Ciampi
Celia Greenwood
Nandini Dendukuri
James Hanley
Lawrence Joseph
Aurélie Labbe
Erica Moodie
Robert Platt