meta.sub.cor

Computes the estimate, standard error, and confidence interval for a
difference in average Pearson or partial correlations for two mutually
exclusive subgroups of studies. Each subgroup can have one or more
studies. All of the correlations must be either Pearson correlations
or partial correlations.

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

meta.sub.cor function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>n</dt>
<dd>vector of sample sizes</dd>
<dt>cor</dt>
<dd>vector of estimated correlations</dd>
<dt>s</dt>
<dd>number of control variables (set to 0 for Pearson)</dd>
<dt>group</dt>
<dd>vector of group indicators:<ul>
<li>1 for set A</li>
<li>2 for set B</li>
<li>0 to ignore</li>
</ul></dd></dl>

Arguments

Confidence interval for a subgroup difference in average Pearson
or partial correlations — meta.sub.cor

<dl>

<dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>


<dt>n</dt>
<dd>vector of sample sizes</dd>


<dt>cor</dt>
<dd>vector of estimated correlations</dd>


<dt>s</dt>
<dd>number of control variables (set to 0 for Pearson)</dd>


<dt>group</dt>
<dd>vector of group indicators:<ul>
<li>1 for set A</li>
<li>2 for set B</li>
<li>0 to ignore</li>
</ul></dd>

</dl>

meta.sub.cor: Confidence interval for a subgroup difference in average Pearson or partial correlations

Description

Usage

Value

Arguments

References

Examples