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pmcalibration

Calibration Curves for Clinical Prediction Models

Fit calibrations curves for clinical prediction models and calculate several associated metrics (Eavg, E50, E90, Emax). Ideally predicted probabilities from a prediction model should align with observed probabilities. Calibration curves relate predicted probabilities (or a transformation thereof) to observed outcomes via a flexible non-linear smoothing function. 'pmcalibration' allows users to choose between several smoothers (regression splines, generalized additive models/GAMs, lowess, loess). Both binary and time-to-event outcomes are supported. See Van Calster et al. (2016) <doi:10.1016/j.jclinepi.2015.12.005>; Austin and Steyerberg (2019) <doi:10.1002/sim.8281>; Austin et al. (2020) <doi:10.1002/sim.8570>.

Versions across snapshots

VersionRepositoryFileSize
0.2.0 rolling linux/jammy R-4.5 pmcalibration_0.2.0.tar.gz 369.3 KiB
0.2.0 rolling linux/noble R-4.5 pmcalibration_0.2.0.tar.gz 369.4 KiB
0.2.0 rolling source/ R- pmcalibration_0.2.0.tar.gz 291.4 KiB
0.2.0 latest linux/jammy R-4.5 pmcalibration_0.2.0.tar.gz 369.3 KiB
0.2.0 latest linux/noble R-4.5 pmcalibration_0.2.0.tar.gz 369.4 KiB
0.2.0 latest source/ R- pmcalibration_0.2.0.tar.gz 291.4 KiB
0.2.0 2026-04-26 source/ R- pmcalibration_0.2.0.tar.gz 291.4 KiB
0.2.0 2026-04-23 source/ R- pmcalibration_0.2.0.tar.gz 291.4 KiB
0.2.0 2026-04-09 windows/windows R-4.5 pmcalibration_0.2.0.zip 374.3 KiB
0.2.0 2025-04-20 source/ R- pmcalibration_0.2.0.tar.gz 291.4 KiB

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