gelmanplot.uvmeta

This plot shows the evolution of Gelman and Rubin's shrink factor as the number of iterations increases. The code is adapted from
the R package coda.

Facilitate frequentist and Bayesian meta-analysis of diagnosis and prognosis research studies. It includes functions to summarize multiple estimates of prediction model discrimination and calibration performance (Debray et al., 2019) <doi:10.1177/0962280218785504>. It also includes functions to evaluate funnel plot asymmetry (Debray et al., 2018) <doi:10.1002/jrsm.1266>. Finally, the package provides functions for developing multivariable prediction models from datasets with clustering (de Jong et al., 2021) <doi:10.1002/sim.8981>.

Thomas Debray

metamisc

Meta-Analysis of Diagnosis and Prognosis Research Studies

Valentijn de Jong

gelmanplot.uvmeta function

<dl><dt>x</dt>
<dd>An mcmc object</dd>
<dt>confidence</dt>
<dd>The coverage probability of the confidence interval for the potential scale reduction factor</dd>
<dt>...</dt>
<dd>Additional arguments which are currently not used</dd></dl>

Arguments

Thomas Debray &lt;thomas.debray@gmail.com&gt;

Author

Gelman-Rubin-Brooks plot — gelmanplot.uvmeta

<dl>

<dt>x</dt>
<dd>An mcmc object</dd>


<dt>confidence</dt>
<dd>The coverage probability of the confidence interval for the potential scale reduction factor</dd>


<dt>...</dt>
<dd>Additional arguments which are currently not used</dd>

</dl>

gelmanplot.uvmeta: Gelman-Rubin-Brooks plot

Description

Usage

Value

Arguments

Author