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) tools:::Rd_expr_doi("10.1016/j.jclinepi.2015.12.005"); Austin and Steyerberg (2019) tools:::Rd_expr_doi("10.1002/sim.8281"); Austin et al. (2020) tools:::Rd_expr_doi("10.1002/sim.8570").
Maintainer: Stephen Rhodes steverho89@gmail.com [copyright holder]
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