acplot.mcmc.list

Function to display autocorrelation of a fitted Bayesian meta-analysis model.

autocorrelation

Meta-analysis

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

acplot.mcmc.list function

<dl><dt>x</dt>
<dd>An object of class <code>"mcmc.list"</code></dd>
<dt>P</dt>
<dd>Optional dataframe describing the parameters to plot and their respective names</dd>
<dt>nLags</dt>
<dd>Integer indicating the number of lags of the autocorrelation plot.</dd>
<dt>greek</dt>
<dd>Logical value indicating whether parameter labels have to be parsed to get Greek letters. Defaults to FALSE.</dd>
<dt>...</dt>
<dd>Additional arguments which are passed to ggs_autocorrelation</dd></dl>

Arguments

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

Author

Plot the autocorrelation of a Bayesian meta-analysis model — acplot.mcmc.list

<dl>

<dt>x</dt>
<dd>An object of class <code>"mcmc.list"</code></dd>


<dt>P</dt>
<dd>Optional dataframe describing the parameters to plot and their respective names</dd>


<dt>nLags</dt>
<dd>Integer indicating the number of lags of the autocorrelation plot.</dd>


<dt>greek</dt>
<dd>Logical value indicating whether parameter labels have to be parsed to get Greek letters. Defaults to FALSE.</dd>


<dt>...</dt>
<dd>Additional arguments which are passed to ggs_autocorrelation</dd>

</dl>

acplot.mcmc.list: Plot the autocorrelation of a Bayesian meta-analysis model

Description

Usage

Value

Arguments

Author