Package: ipeval 0.1.0.9000

ipeval: Interventional Prediction Evaluation

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 either at a single time point or as longitudinal treatment strategies with sequential treatment decisions. 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>.

Authors:Jasper van Egeraat [aut, cre], Nan van Geloven [aut, cph], Ruth Keogh [aut, cph], Leiden University Medical Center [fnd]