Glen McGee



I am an Assistant Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. I completed my PhD in Biostatistics at Harvard University and previously received a BScH in Mathematics from Queens University.

I’m interested in developing statistical tools to solve problems in epidemiology, environmental health, and health policy. I’m currently working on developing Bayesian frameworks for modelling multi-pollutant exposure mixtures, and on designing and analyzing multigenerational studies.

research

Recent methods papers:

McGee, G., Weisskopf, M. G., Kioumourtzoglou, M. A., Coull, B. A., and Haneuse, S. (2019). “Informatively empty clusters with application to multigenerational studies”. Biostatistics.

Coull, B., Lee, S., McGee, G., Manjourides, J., Mittleman, M., and Wellenius, G. (2019). “Corrections for Measurement Error Due to Delayed Onset of Illness for Case-Crossover Designs.” Biometrics.

McGee, G., Schildcrout, J., Normand, S.-L. and Haneuse, S. (2020). “Outcome-Dependent Sampling in Cluster-Correlated Data Settings with Application to Hospital Profiling.” Journal of the Royal Statistical Society: Series A.

McGee, G., Kioumourtzoglou, M.-A., Weisskopf, M., Haneuse, S., and Coull, B. (2020) “On the Interplay Between Exposure Misclassification and Informative Cluster Size in Multigenerational Studies.” Journal of the Royal Statistical Society: Series C.

McGee, G., Perkins, N., Mumford, S., Kioumourtzoglou, M.-A., Weisskopf, M., Schildcrout, J., Coull, B., Schisterman, E., and Haneuse, S. (2020) “Methodological Issues in Population-Based Studies of Multigenerational Effects.” American Journal of Epidemiology.

See here for more details.

teaching

Introductory Probability
Instructor, Summer 2018, Summer 2017
Harvard T.H. Chan School of Public Health
Month-long preparatory course for incoming biostatistics doctoral students. Topics: Set theory, Kolmogorov’s axioms, combinatorics, conditional probability, independence, Bayes theorem, moments, functions of random variables.

Statistical Methods*
Teaching Assistant, Fall 2018
BST/BIOSTAT 232, Harvard T.H. Chan School of Public Health
Redesigned in 2018 (combined 232 and 233). First year methods course for biostatistics graduate students (required for PhD). Topics: least squares; penalized regression; permutation and resampling inference; GLMs; continuous, binary, count, and polytomous data; survival analysis.
* received Certificate of Distinction in Teaching

Analysis of Multivariate and Longitudinal Data
Teaching Assistant, Spring 2017
BST/BIOSTAT 245, Harvard T.H. Chan School of Public Health
Advanced doctoral course on correlated data methods. Topics: Visualizing correlated data, marginal models and generalized estimating equations, generalized linear mixed-effects models, missing data, time-dependent confounding.

Statistical Methods I*
Teaching Assistant, Fall 2016
BST/BIOSTAT 232, Harvard T.H. Chan School of Public Health
First year methods course in linear/logistic regression for biostatistics graduate students (required for PhD). Topics: Linear regression, model checking and diagnostics, model building, hypothesis testing and permutation-based inference, contingency tables and exact inference, logistic regression, causal inference and confounding.
* received Certificate of Distinction in Teaching

Regression & Analysis of Variance in Experimental Research
Teaching Assistant, Fall 2015
BIO 211, Harvard T.H. Chan School of Public Health
Intermediate statistics course aimed at public health (MPH) students. Topics: simple and multiple linear regression, regression diagnostics and model fit, ANOVA, hypothesis testing, factorial and randomized block designs.

cv

Download my CV here.