JJ Slater, SG Bebeziqi. Approximating count models for epidemic curve reconstructions. Submitted. (preprint)
JJ Slater, PE Brown, JS Rosenthal, J Mateu (2025+). Leveraging cellphone-derived mobility networks to assess COVID-19 travel risk. The Annals of Applied Statistics, 19(1), 56-74. (pdf, link to journal)
JJ Slater, A. Bansal, H. Campbell, JS Rosenthal, P. Gustafson, PE Brown (2024). A Bayesian approach to estimating COVID-19 incidence and infection fatality rates. Biostatistics, 25(2), 354-384. (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 (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
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)
Bespoke Bayesian modelling using Rstan
Invited online workshop for the Statistical Society of Canada (Apr 2025) - upcoming
A statistical framework for reconstructing epidemic curves
Invited data science seminar at Thomson Rivers University (Feb 2025)
Invited biostatistics seminar at McGill University (Feb 2025)
Invited statistics seminar at McMaster University (Mar 2025) - upcoming
Invited talk at Western North American Region of the International Biometrics Society (June 2025) - upcoming
A practical look at network autoregressions for underreported infectious disease data (slides)
Invited talk at SSC 2024 annual meeting - June 2024
Invited talk at CANSSI Ontario Research Day - May 2024
Leveraging cellphone-derived mobility networks in spatiotemporal infectious disease models
Invited talk at AMMCS 2023 – August 2023
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.