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>.
Package details |
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Author | Stephen Rhodes [aut, cre, cph] |
Maintainer | Stephen Rhodes <steverho89@gmail.com> |
License | GPL-3 |
Version | 0.1.0 |
URL | https://github.com/stephenrho/pmcalibration |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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