Paul Gustafson

Professor

The University of British Columbia

Canada

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Professor Paul Gustafson is a faculty member at the University of British Columbia, Canada. His research focuses on comparative effectiveness research, particularly in the areas of opioid agonist treatment and Bayesian statistical methods. Recent articles include investigations into treatment protocols for opioid use and statistical methodologies for risk prediction model validation. His contributions to the field have significantly influenced the understanding of treatment effects and epidemiological modeling.

Paul Gustafson

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Articles (17)

Comparative effectiveness of missed dose protocols of opioid agonist treatment in British Columbia, Canada: protocol for a population-based target trial emulation

Expected Value of Sample Information Calculations for Risk Prediction Model Validation

Comparative effectiveness of methadone take-home dose initiation in British Columbia, Canada: protocol for a population-based retrospective cohort study using target trial guidelines

The Bayes factor, HDI-ROPE, and frequentist equivalence tests can all be reverse engineered—Almost exactly—From one another: Reply to Linde et al. (2021).

What is the ideal time to begin tapering opioid agonist treatment? A protocol for a retrospective population-based comparative effectiveness study in British Columbia, Canada

Discussion on “Bayesian meta-analysis of penetrance for cancer risk” by Thanthirige Lakshika M. Ruberu, Danielle Braun, Giovanni Parmigiani, and Swati Biswas

Discussion on “LEAP: the latent exchangeability prior for borrowing information from historical data” by Ethan M. Alt, Xiuya Chang, Xun Jiang, Qing Liu, May Mo, H. Amy Xia, and Joseph G. Ibrahim

Closed-Form Solution of the Unit Normal Loss Integral in 2 Dimensions, with Application in Value-of-Information Analysis

Value-of-Information Analysis for External Validation of Risk Prediction Models

Comparative effectiveness of urine drug screening strategies alongside opioid agonist treatment in British Columbia, Canada: A population-based observational study protocol

Combining parametric and nonparametric models to estimate treatment effects in observational studies

Bayes Factors and Posterior Estimation: Two Sides of the Very Same Coin

A Bayesian approach to estimating COVID-19 incidence and infection fatality rates

Dealing with missing data using the Heckman selection model: methods primer for epidemiologists

Reflections on Bayesian inference and Markov chain Monte Carlo

Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies

A few things to consider when deciding whether or not to conduct underpowered research

Collaborators (5)

Paxton Bach

Mohsen Sadatsafavi

Laure Wynants

Thomas P. A. Debray

Hannah Goymann

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