Dr. Denis Talbot, Ph.D., is a regular investigator at the CHU de Québec – Laval University Research Center and professor in biostatistics at the Department of Social and Preventive Medicine of Laval University’s School of Medicine. His research interests focus on the development of statistical methods to perform causal inference and the application of such methods in health research, particularly in cardiovascular health research. Causal inference seeks to predict the effect that a potential intervention would have, for instance the effect of a public health policy or a medical treatment.
Model selection for causal inference
When observational data are utilized to investigate the relationship between an exposure and a disease, there can be variables that are both associated with the exposure and the disease. Such variables, called confounders, may distort the observed relationship between the exposure and the disease, unless adequate control is performed. Unfortunately, identifying confounders solely based on substantive knowledge can be difficult. Moreover, once confounders are identified, an appropriate statistical modeling approach must be employed to eliminate the bias that confounders produce.
One strategy to circumvent these problems would be to use statistical methods to supplement scientific knowledge with the information available in the data. Such methods would facilitate the identification and the control for confounders, and thus facilitate the identification of the causal relationship between the exposure and the disease. An important part of Dr. Talbot’s research program, funded by the Natural Sciences and Engineering Research Council of Canada, targets the development of such statistical methods.
Other interests in causal inference
Dr. Talbot is also interested in many other aspects of causal inference, notably in causal mediation methods and treatment regime effects (for example, cumulative exposure, and marginal structural models). He is involved in various collaborative research projects, for instance on health at work, nutrition or physical activity.
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Québec, Québec
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A randomized, crossover, head-to-head comparison of eicosapentaenoic acid and docosahexaenoic acid supplementation to reduce inflammation markers in men and women: the Comparing EPA to DHA (ComparED) Study
Journal ArticleAm J Clin Nutr, 104 (2), 2016.
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The relations between implicit intelligence beliefs, autonomous academic motivation, and school persistence intentions: a mediation model
Journal ArticleSoc Psychol Educ, 18 (2), 2015.
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The Bayesian Causal Effect Estimation Algorithm
Journal ArticleJ Causal Inference, 3 (2), 2015.
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A cautionary note concerning the use of stabilized weights in marginal structural models
Journal ArticleStat Med, 34 (5), 2015.
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Authors' reply to comments on "a cautionary note concerning the use of stabilized weights in marginal structural models"
Journal ArticleStat Med, 34 (18), 2015.
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The effect of the prior distribution in the Bayesian Adjustment for Confounding algorithm
Journal ArticleComput Stat Data Anal, 70 , 2013.
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Variance estimation and confidence intervals for the standardized mortality ratio with application to the assessment of a cancer screening program
Journal ArticleStat Med, 30 (25), 2011.
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Active projects
- Causal inference methods for adaptive treatment strategies, from 2023-04-01 to 2028-03-31
- Centre de recherches mathématiques (CRM), from 2022-04-01 to 2028-03-31
- Favoriser l'engagement des femmes ayant eu un cancer du sein dans les décisions concernant l'hormonothérapie adjuvante prolongée, from 2023-10-01 to 2027-05-31
- Méthodes d'inférence causale pour l'analyse de données médico-administratives et pour la médecine personnalisée, from 2022-07-01 to 2026-06-30
- Personalized risk-stratified breast cancer follow-up care: a feasibility and acceptability study, from 2023-06-26 to 2026-06-30
- Prévenir l’hypertension, le diabète de type 2 et les maladies cardiovasculaires en ciblant les stresseurs psychosociaux au travail, les longues heures de travail et les mauvaises habitudes de vie : Des fractions, from 2022-10-01 to 2026-03-31
- The right care, for the right patient, at the right time, by the right provider: A value-based comparison of the management of ambulatory respiratory diseases in walk-in clinics, primary care physician practices and emergency departments, from 2021-10-01 to 2025-03-31
- The test-negative design for the estimation of COVID-19 vaccine effectiveness: design evaluation and development of statistical methods in the evolving context, from 2022-10-01 to 2025-09-30
- Urogenital tissue engineering solutions for transgender surgeries, from 2024-03-31 to 2026-03-30
- Utilisation de l’inférence causale pour l’attribution des ventes en assurance de dommage, from 2023-10-02 to 2024-10-01
- Vers des trajectoires de soins en cancer du sein personnalisées en fonction du risque et des besoins des patientes: une étude de faisabilité et d'acceptabilité, from 2023-04-01 to 2025-03-31
Recently finished projects
- Déterminer la qualité de la polypharmacie chez les aînés : une approche basée sur l’intelligence artificielle, from 2020-04-01 to 2023-03-31
- Funding to support this manuscript development was provided by the International Society for Pharmacoepidemiology (ISPE)., from 2021-12-01 to 2022-12-31
- Model and variable selection for causal inference., from 2016-04-01 to 2023-03-31
- Prize 202203PJT - The test-negative design for the estimation of COVID-19 vaccine effectiveness: design evaluation and development of statistical methods in the evolving context, from 2022-10-01 to 2023-03-31
- Real-World Evaluation of the Efficacy, Safety and Cost-Effectiveness of Statins for Primary Prevention of Cardiovascular Disease Among the Elderly – A Causal Perspective to Treatment Trajectory Analysis, from 2019-10-01 to 2023-03-31
- The right care, for the right patient, at the right time, by the right provider: A value-based comparison of the management of ambulatory respiratory diseases in walk-in clinics, primary care physician practices and emergency departments, from 2020-04-01 to 2024-03-31