https://jvelumc.r-universe.devRecent package updates in jvelumcR-universehttps://github.com/jvelumc.pnghttps://jvelumc.r-universe.devMon, 08 Jun 2026 16:53:53 GMTj.w.a.van_egeraat@lumc.nl (Jasper van Egeraat)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. Package supports binary and time-to-event outcomes under binary interventions made 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>.https://github.com/r-universe/jvelumc/actions/runs/27164478152Mon, 08 Jun 2026 16:53:53 GMTipeval0.1.0.9000successhttps://jvelumc.r-universe.devhttps://github.com/jvelumc/ipevallongitudinal.Rmdlongitudinal.htmlEvaluating predictions under longitudinal interventions2026-06-08 16:41:382026-06-08 16:41:38longitudinal-data-and-cox-models.Rmdlongitudinal-data-and-cox-models.htmlGenerating time-dependent confounding data and fitting Marginal Structural Cox Models2026-06-08 08:26:512026-06-08 13:55:52ipeval.Rmdipeval.htmlipeval: an R package for evaluating predictions under interventions2026-04-17 09:11:522026-06-08 16:29:53time-to-event.Rmdtime-to-event.htmlEvaluating performance in time-to-event data2026-04-16 11:56:242026-05-05 07:33:39