Denis Talbot, Université de Montréal

Research

Biostatistical Methods Case-Control Causal Inference Propensity Score Simulation Study Test-Negative Design

Latest papers

Authors' reply to comments on "a cautionary note concerning the use of stabilized weights in marginal structural models".
Statistics in medicine · 2015 · first author

All 1 publications

Latest funding

The test-negative design for the estimation of COVID-19 vaccine effectiveness: design evaluation and development of statistical methods in the evolving context
CIHR · 2022 · Principal investigator
$275,400
DecreAsing sedentary behaviour and inCreasing physical acTIvity fOr healthy ageing (ACTION) study
CIHR · 2016 · Co-investigator
$100,000

All 2 grants and awards

1 publications.

01

Authors' reply to comments on "a cautionary note concerning the use of stabilized weights in marginal structural models".

Talbot D, Atherton J, Lefebvre G, Rossi AM, Bacon SL

Statistics in medicine2015First author

DOI: 10.1002/sim.6512 PMID: 26147568

The test-negative design for the estimation of COVID-19 vaccine effectiveness: design evaluation and development of statistical methods in the evolving context

Principal investigatorCIHR2022Project Grant

Principal investigators: Schnitzer, Mireille E; Talbot, Denis

Keywords: Biostatistical Methods; Case-Control; Causal Inference; Propensity Score; Simulation Study; Test-Negative Design

$275,400

DecreAsing sedentary behaviour and inCreasing physical acTIvity fOr healthy ageing (ACTION) study

Co-investigatorCIHR2016Project Grant

Principal investigators: Bacon, Simon L; Lavoie, Kim

Keywords: Ageing; Behavioural Trial Development; Disability Free Life Expectancy; Physical Activity; Sedentary Behaviour

$100,000

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

Frequent collaborators

Denis Talbot

Faculty

1 shared papers, latest 2015

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Mention their CIHR grant from 2022

Subject: Prospective PhD student: Biostatistical Methods Dear Professor Talbot, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "Authors' reply to comments on "a cautionary note concerning the use of stabilized weights in marginal structural models"." (2015), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your CIHR-funded project "The test-negative design for the estimation of COVID-19 vaccine effectiveness: design evaluation and development of statistical methods in the evolving context" (2022), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]