Virginie Rondeau

Director Of Research In Biostatistic

Greater Bordeaux Metropolitan Area France
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Summary

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Senior
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Top School
Virginie Rondeau is a Director of Research in Biostatistics at INSERM with over two decades of leadership in designing and analyzing epidemiological and clinical studies. She holds a PhD and an HDR from Université de Bordeaux and completed postdoctoral work at USC, combining deep methodological rigor with applied public-health impact. Her expertise spans joint models for recurrent events, biomarkers and competing risks, prognostic model development and validation, surrogate endpoint assessment, and methods for correlated and clustered environmental data. She advises independent data monitoring committees and develops R packages to make advanced correlated-data methods accessible to practitioners. Known for bridging theory and practice, she applies meta-analytic and joint-modelling techniques to real-world clinical problems, often revealing non-obvious dependencies between recurrent events and terminal outcomes. Based in the Greater Bordeaux area, she brings an unusually broad toolkit for both methodological innovation and regulatory-strength evidence generation.
code8 years of coding experience
bookUniversity of Southern California
bookDoctor of Philosophy - PhD, Biostatistics, Doctor of Philosophy - PhD, Biostatistics at Université de Bordeaux
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Github Skills (7)

index-html3
prediction3
endpoints3
r-package3
surrogate3
cran2
evaluation2

Programming languages (1)

Fortran

Github contributions (2)

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cran/frailtypack

Sep 2017 - Jun 2020

Contributions:16 commits in 2 years 9 months
socale/frailtypack

Apr 2020 - Apr 2020

General Frailty Models: Shared, Joint and Nested Frailty Models with Prediction; Evaluation of Failure-Time Surrogate Endpoints. The R package frailtypack is available on cran at https://cran.r-project.org/web/packages/frailtypack/index.html
Contributions:3 commits, 1 push, 1 branch in 1 day
r-packagecran-rpredictioncranindex
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Virginie Rondeau - Director Of Research In Biostatistic