pmcalibration-package {pmcalibration}R Documentation

pmcalibration: Calibration Curves for Clinical Prediction Models

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) 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.

Author(s)

Maintainer: Stephen Rhodes steverho89@gmail.com [copyright holder]

See Also

Useful links:


[Package pmcalibration version 0.2.0 Index]