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pmcalibration  

Calibration Curves for Clinical Prediction Models
View on CRAN: Click here


Download and install pmcalibration package within the R console
Install from CRAN:
install.packages("pmcalibration")

Install from Github:
library("remotes")
install_github("cran/pmcalibration")

Install by package version:
library("remotes")
install_version("pmcalibration", "0.2.0")



Attach the package and use:
library("pmcalibration")
Maintained by
Stephen Rhodes
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-09-06
Latest Update: 2025-02-21
Description:
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) ; Austin and Steyerberg (2019) ; Austin et al. (2020) .
How to cite:
Stephen Rhodes (2023). pmcalibration: Calibration Curves for Clinical Prediction Models. R package version 0.2.0, https://cran.r-project.org/web/packages/pmcalibration. Accessed 27 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:42), 0.1.0 (2023-09-06 19:50)
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