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Code and simulated data for the paper “Revisiting Performance Metrics for Prediction with Rare Outcomes”

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Revisiting Performance Metrics for Prediction with Rare Outcomes

Code and simulated data for the paper "Revisiting Performance Metrics for Prediction with Rare Outcomes" in Statistical Methods in Medical Research by Samrachana Adhikari, Sharon-Lise Normand, Jordan Bloom, David Shahian, and Sherri Rose (2021), doi:10.1177/09622802211038754.

Organization of the repository is as follows:

  • SimulatedData: A subfolder with simulated data used in the paper for one of the cohorts under all three conditions as well as for different event rates.
  • SimulationStudy: A subfolder with .R scripts to fit super learner algorithms on the simulated data and to summarize fitted algorithms.
  • SLwrappersAVR.R: A .R file with new super learner wrapper functions and functions for computing performance metrics.

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Code and simulated data for the paper “Revisiting Performance Metrics for Prediction with Rare Outcomes”

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