.sv_jack

Computes jackknife estimate and standard error for skewness and kurtosis.

Generates prediction intervals and orchard plots for
meta-analytic and meta-regression models fitted with the 'metafor'
package. Orchard plots augment classic forest plots by displaying
individual effect sizes together with group means and their confidence
and prediction intervals, providing an enhanced visualization of
meta-analytic data for ecology, evolution, and beyond. Methods are
described in Nakagawa et al. (2023) <doi:10.1111/2041-210X.14152>.

Daniel Noble

orchaRd

Visualizing Meta-Analyses with Orchard Plots and Prediction
Intervals

Shinichi Nakagawa

.sv_jack function

<dl><dt>x</dt>
<dd>A numeric vector.</dd>
<dt>bias.correct</dt>
<dd>Logical, whether to apply bias correction. Default is TRUE.</dd>
<dt>return.replicates</dt>
<dd>Logical, whether to return jackknife replicates. Default is FALSE.</dd>
<dt>type</dt>
<dd>Character, either "skew" or "kurt" to specify the type of statistic.</dd></dl>

Arguments

Jackknife Estimation of Skewness and Kurtosis for computing sampling variances — .sv_jack

<dl>

<dt>x</dt>
<dd>A numeric vector.</dd>


<dt>bias.correct</dt>
<dd>Logical, whether to apply bias correction. Default is TRUE.</dd>


<dt>return.replicates</dt>
<dd>Logical, whether to return jackknife replicates. Default is FALSE.</dd>


<dt>type</dt>
<dd>Character, either "skew" or "kurt" to specify the type of statistic.</dd>

</dl>

.sv_jack: Jackknife Estimation of Skewness and Kurtosis for computing sampling variances

Description

Usage

Value

Arguments