qra

Uncertainty-aware quantitative risk assessment (QRA)

This project studies uncertainty in estimates of the probability of adverse events based on the SUVmax biomarker. The main focus is polynomial logistic regression, including monotonicity constraints, regularization, goodness-of-fit assessment, and asymptotic and bootstrap uncertainty estimates.

Repository structure

• src/irae_risk/: core implementation of the logistic-regression models and supporting numerical methods.
• notebooks/: analyses used to generate and review the results.
  • logit_all_models.ipynb: comparison of the fitted logistic-regression models.
  • logit_mono-cubic4paper.ipynb: monotonic cubic analysis used for the manuscript.
  • logit_review_boots.ipynb: review of bootstrap-based uncertainty estimates.
• tests/: automated tests for the core implementation.
• data/: raw, interim, and processed data.
• results/: generated tables, figures, and cached calculations.
• manuscript/: manuscript sources and related material.

Team

• Marija Delić makidelic@gmail.com
• Zahra Alirezaei Zahra.Alirezaei@fmf.uni-lj.si
• Katja Strašek Katja.Strasek@fmf.uni-lj.si
• Martin Horvat martin.horvat@fmf.uni-lj.si
• Robert Jeraj robert.jeraj@fmf.uni-lj.si

Online resources

• Meeting minutes
• Original project repository, prepared by Katja Strašek. This repository is currently unavailable.