Software and Code

All open-source software and reproducible research code are made available through the group’s GitHub organization. Software contributions are listed below.

Author

  1. cmldiffvar: An R package implementing causal machine learning estimators for differential variance inference. Available on GitHub.

  2. unihtee: An R package for uncovering treatment effect modifiers in high-dimensional observational study data. Available on GitHub.

  3. uniCATE: An R package for predictive biomarker discovery in clinical trial data using univariate conditional average treatment effect estimation. Available on GitHub.

  4. cvCovEst: An R package for nonparametric covariance matrix estimation in high dimensions. Available on Github and CRAN.

  5. scPCA: An R/Bioconductor package for (sparse) contrastive principal component analysis. Available on GitHub and Bioconductor.

Contributor

  1. simChef: An R package to facilitate simulation studies. Available on GitHub.

  2. mmrm: An R package for mixed models for repeated measures. Available on GitHub and CRAN.

  3. medoutcon: An R package for efficient causal mediation analysis with natural and interventional direct/indirect effects. Available on GitHub.

  4. biotmle: An R/Bioconductor package for targeted learning with moderated statistics for biomarker discovery. Available on GitHub and Bioconductor.