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@Boileau-Group

Boileau Group

We're biostatisticians developing causal machine learning methods at McGill University

The Boileau Group is led by Philippe Boileau, an Assistant Professor of Biostatistics at McGill University and Junior Scientist at the Research Institute of the McGill University Health Centre. We develop flexible causal machine learning methods motivated by real-world scientific questions, with a particular focus on identifying and characterizing treatment effect heterogeneity in clinical studies.

This organization hosts the group's research code. It brings together software packages, research tools, and code accompanying our publications to support transparency, accessibility, and reproducibility in scientific research.

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  1. cmldiffvar cmldiffvar Public

    Forked from PhilBoileau/cmldiffvar

    Causal Machine Learning Methods for Differential Variability Analyses in R

    R

  2. unihtee unihtee Public

    Forked from insightsengineering/unihtee

    Tools for uncovering treatment effect modifiers in high-dimensional data.

    R

  3. cvCovEst cvCovEst Public

    Forked from PhilBoileau/cvCovEst

    An R package for nonparametric covariance matrix estimation in high dimensions

    R

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