Current or incoming graduate students in Stats/Data Science/Math/Epidemiology at UoGuelph are welcome to contact me regarding supervision.
JJ Slater, PE Brown, JS Rosenthal, J Mateu (2023+). Leveraging cellphone-derived mobility networks to assess COVID-19 travel risk. In review. (pdf)
Peer-reviewed journal articles
JJ Slater, A. Bansal, H. Campbell, JS Rosenthal, P. Gustafson, PE Brown (2023+). A Bayesian approach to estimating COVID-19 incidence and infection fatality rates. To appear in Biostatistics. (paper)
JJ Slater, PE Brown, JS Rosenthal, J Mateu (2022). Capturing spatial dependence of COVID-19 case counts with cellphone mobility data. Spatial Statistics 49: 100540.(paper)
JJ Slater, PE Brown, JS Rosenthal, J Mateu (2021). Forecasting subnational COVID-19 mortality using a day-of-the-week adjusted Bayesian hierarchical model. Stat, 10(1), e328 (paper) *Top 10 Wiley downloaded article.
A Béliveau, DJ Boyne, JJ Slater, D Brenner, P Arora (2019). BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses. BMC Medical Research Methodology, 19(1), 196. paper, R-package
Applied papers (select). See my Google Scholar page for a complete list.
M Silverman, JJ Slater, R Jandoc, S Koivu, AX Garg, MA Weir (2020). Hydromorphone and the risk of infective endocarditis among people who inject drugs: a population-based, retrospective cohort study. The Lancet Infectious Diseases, 20(4), 487-497.
M Ordon, J Dirk, JJ Slater, J Kroft, S Dixon, B Welk (2020). Incidence, Treatment, and Implications of Kidney Stones During Pregnancy: A Matched Population-Based Cohort Study. Journal of Endourology, 34(2), 215-221.
MA Weir, JJ Slater, R Jandoc, S Koivu, AX Garg, M Silverman (2019). The risk of infective endocarditis among people who inject drugs: a retrospective, population-based time series analysis. CMAJ, 191(4), E93-E99.
Gupta, A., JJ Slater, Boyne, D., and others (2019). Probabilistic Graphical Modeling for Estimating Risk of Coronary Artery Disease: Applications of a Flexible Machine-Learning Method. Medical Decision Making, 39(8), 1032-1044.
P Arora, D Boyne, JJ Slater, A Gupta, DR. Brenner, and M Druzdzel (2019). "Bayesian networks for risk prediction using real-world data: a tool for precision medicine." Value in Health 22, no. 4: 439-445.
S Kang, JJ Slater (2022). Pop Quizzical: Does Authoring questions for peers improve learning in Introductory Statistics?
Peer-reviewed conference paper/talk at the 11th International Conference on Teaching Statistics. (paper)
Research Talks, Posters, and Workshops
Quantifying the risk associated with travelling during a pandemic using cellphone-derived mobility networks (based on joint work with PE Brown, JS Rosenthal, and J Mateu)
Invited seminar talk at the University of Waterloo - November 2022 (slides)
A Bayesian approach to estimating COVID-19 incidence and infection fatality rates (based on joint work with A Bansal, H Campbell, JS Rosenthal, P Gustafson, PE Brown)
Poster presentation at the 2022 ISBA World Meeting in Montreal - June 2022. (poster)
Contributed talk at SSC 2022 annual meeting - May 2022. (slides)
Modelling the COVID-19 pandemic using population mobility data (based on joint work with PE Brown, JS Rosenthal, J Mateu)
Invited talk at the ISI World Statistics Congress - July 2021
Contributed talk at Canadian Statistics Student Conference – June 2021
Invited 3-minute lightning talk at the Stellar Stats workshop – May 2021
Contributed talk at the University of Toronto's Statistics Graduate Student Research Day – April 2021
BUGSnet: A New Comprehensive R Package for Network Meta-Analysis (based on joint work with A Beliveau, DJ Boyne, DR Brenner, P Arora)
Poster presentation at ISPOR 2019 in New Orleans.
Half-day workshop at the 2019 CADTH symposium in Edmonton.
My contribution was a ~30 minute segment where I introduced basic network meta-analysis concepts followed by a step-by-step tutorial on how to apply these concepts in BUGSnet.