Publications

Search
Author Title Type [ Year(Asc)]
Accepted
Kong, X. , Daly, C. H. , & Béliveau, A. . (Accepted). Generalized Fused Lasso for Treatment Pooling in Network Meta-Analysis. Statistics in Medicine.
Wang, Y. , Lysy, M. , & Béliveau, A. . (Accepted). Plant-Capture Methods for Estimating Population Size from Uncertain Plant Captures. Epidemiology. Retrieved from https://arxiv.org/abs/2403.04058
2024
Wigle, A. , Béliveau, A. , Blackmore, D. , Lapeyre, P. , Osadetz, K. , Lemieux, C. , & Daun, K. J. . (2024). Estimation and Applications of Uncertainty in Methane Emissions Quantification Technologies: A Bayesian Approach. ACS ES&T Air, 1(9), 1000-1014.
Daun, K. J. , Lemieux, C. , Béliveau, A. , Blackmore, D. , Narayanan, N. , Wigle, A. , Fritz, K. , et al. (2024). Evaluation of Emission Quantification Technologies: Final Report (Prepared for: Petroleum Technology Alliance Canada and Clean Resources Innovation Network., pp. 1-76).
2023
Kong, X. , & Béliveau, A. . (2023). Generalized Fused Lasso for Treatment Pooling in Network Meta-Analysis. Joint Statistical Meetings Proceedings. Retrieved from https://doi.org/10.5281/zenodo.8435663
Liu, Y. , Béliveau, A. , Wei, Y. , Chen, M. Y. , Record-Lemon, R. , Kuo, P. L. , Pritchard, E. , et al. (2023). A Gentle Introduction to Bayesian Network Meta-Analysis Using an Automated R Package. Multivariate Behavioral Research, 58(4), 706-722.
2022
Wigle, A. , & Béliveau, A. . (2022). Bayesian Unanchored Additive Models for Component Network Meta-Analysis. Statistics in Medicine, 21(22), 4444-4466.
2021
Liu, Y. , Béliveau, A. , Besche, H. , Wu, A. D. , Zhang, X. , Stefan, M. , Gutlerner, J. , et al. (2021). Bayesian Mixed Effects Model and Data Visualization for Understanding Item Response Time and Response Order in Open Online Assessment. Frontiers in Education, section Assessment, Testing and Applied Measurement, 5:607260.
Béliveau, A. , & Gustafson, P. . (2021). A Theoretical Investigation of How Evidence Flows in Bayesian Network Meta-Analysis of Disconnected Networks. Bayesian Analysis, 16(3), 803-823.
2019
Béliveau, A. , Boyne, D. , Slater, J. , Brenner, D. , & Arora, P. . (2019). BUGSnet: An R Package to Facilitate the Conduct and Reporting of Bayesian Network Meta-Analyses. BMC Medical Research Methodology, 19:196.
Gupta, A. , Slater, J. , Boyne, D. , Mitsakakis, N. , Béliveau, A. , Druzdzel, M. , Brenner, D. , et al. (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.
Zhang, K. , Arora, P. , Sati, N. , Béliveau, A. , Troke, N. , Veroniki, A. Angeliki, Rodrigues, M. , et al. (2019). Characteristics and methods of incorporating randomized and nonrandomized evidence in network meta-analyses: a scoping review. Journal of Clinical Epidemiology, 113, 1-10.
2018
Liu, Y. , Besche, H. , Béliveau, A. , Zhang, X. , Kroc, E. , Stefan, M. , Gutlerner, J. , et al. (2018). Challenges from Modeling Open Online Assessment Data. Proceedings of the Joint Statistical Meetings 2018.
2017
Atlas, W. I. , Housty, W. G. , Béliveau, A. , DeRoy, B. , Callegari, G. , Reid, M. , & Moore, J. W. . (2017). Ancient fish weir technology for modern stewardship: lessons from community-based salmon monitoring. Ecosystem Health and Sustainability, 3(6).
Béliveau, A. , Goring, S. , Platt, R. W. , & Gustafson, P. . (2017). Network meta-analysis of disconnected networks: How dangerous are random baseline treatment effects?. Research Synthesis Methods, 8(4), 465-474.
2016
Béliveau, A. . (2016). Data integration methods for studying animal population dynamics. PhD thesis. Summit: Simon Fraser University research repository. Retrieved from http://summit.sfu.ca/item/16125
2015
Béliveau, A. , Lockhart, R. A. , Schwarz, C. J. , & Arndt, S. K. . (2015). Adjusting for Undercoverage of Access-Points in Creel Surveys with Fewer Overflights. Biometrics, 71(4), 1050–1059.
Beaumont, J. - F. , Béliveau, A. , & Haziza, D. . (2015). Clarifying Some Aspects of Variance Estimation in Two-Phase Sampling. Journal of Survey Statistics and Methodology, 3(4), 524–542.