run_boots

Wrapper to run bootstrap resamples using <code>parallel</code>

internal

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>.

Stephen Rhodes

pmcalibration

Calibration Curves for Clinical Prediction Models

run_boots function

<dl><dt>cal</dt>
<dd>an object created with one of the <code>_cal</code> functions</dd>
<dt>R</dt>
<dd>number of resamples (default = 1000)</dd>
<dt>cores</dt>
<dd>number of cores (for <code>parallel</code>)</dd></dl>

Arguments

Wrapper to run bootstrap resamples using parallel — run_boots

<dl>

<dt>cal</dt>
<dd>an object created with one of the <code>_cal</code> functions</dd>


<dt>R</dt>
<dd>number of resamples (default = 1000)</dd>


<dt>cores</dt>
<dd>number of cores (for <code>parallel</code>)</dd>

</dl>

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run_boots: Wrapper to run bootstrap resamples using `parallel`

Description

Usage

Value

Arguments