se.spear

Computes the Bonett-Wright standard error of a Spearman correlation using
the estimated correlation and sample size. The standard error from this
function can be used as input in the meta.ave.cor.gen
function in applications where a combination of different types of
compatible correlations are used in the meta-analysis.

Implements functions for varying coefficient meta-analysis methods.
These methods do not assume effect size homogeneity. Subgroup effect size
comparisons, general linear effect size contrasts, and linear models of
effect sizes based on varying coefficient methods can be used to describe
effect size heterogeneity. Varying coefficient meta-analysis methods do not
require the unrealistic assumptions of the traditional fixed-effect and
random-effects meta-analysis methods. For details see:
Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.

Douglas G. Bonett

vcmeta

Varying Coefficient Meta-Analysis

Robert J. Calin-Jageman

se.spear function

<dl><dt>cor</dt>
<dd>estimated Spearman correlation</dd>
<dt>n</dt>
<dd>sample size</dd></dl>

Arguments

Computes the standard error for a Spearman correlation — se.spear

<dl>

<dt>cor</dt>
<dd>estimated Spearman correlation</dd>


<dt>n</dt>
<dd>sample size</dd>

</dl>

se.spear: Computes the standard error for a Spearman correlation

Description

Usage

Value

Arguments

References

Examples