Interventional Prediction Evaluation
Overview
Provides methods to evaluate predictive performance of models that estimate risks under hypothetical intervention scenarios (interventional/causal/counterfactual predictions) with observational data subject to treatment-outcome confounding. Inverse probability of treatment weighting (IPTW) is used to construct a pseudopopulation in which all individuals receive a specified intervention, enabling assessment of agreement between predicted risks under the intervention and observed outcomes in the pseudo-population corresponding to that intervention. Supports interventions with binary or categorical treatment levels, applied at a single time point. Performance measures supported are AUC (Area Under the receiving operating characteristic Curve), Brier score, observed-expected ratio, and calibration plots. Methods implemented in this package are based on work by Keogh and Van Geloven (2024) DOI:10.1097/EDE.0000000000001713.
- fix: null model is now refitted during every bootstrap iteration.
- fix: stop early with error if duplicate names are given to models to validate.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK7 OK2026-05-07
Documentation
- Help pages
- 4 (1 internal)includes a package overview page
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
- ipeval HTML
- time-to-event HTML
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- 17
- Median days to close, 50 most recently updated closed PRs
- 11
Issues over time
Commits over time
Commit identities over time
- github.com/jvelumc/ipeval · last recorded on 2026-08-23
8 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/survival-lumc/ipeval on 2026-10-22.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2026-09-13 · The repository has a site deploy workflow
pkgdown site last built 2026-09-13
Dependencies
Installing ipeval adds 32 packages (12 with compiled code, 26 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, Rcpp 1.8 MB.
Code & Tests
People & History
Package metadata
- First published
- 2026-05-06
- Total releases
- 3 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5
- Download size
- 152 KB
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