meta.ave.var

Computes the estimate and confidence interval for an average variance
from two or more studies. The estimated average variance or the upper
confidence limit could be used as a variance planning value in sample
size planning. The confidence intervals assume normality, and this
function is not recommended if the variances have been estimated
from leptokurtic data.

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.ave.var function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>var</dt>
<dd>vector of sample variances</dd>
<dt>n</dt>
<dd>vector of sample sizes</dd>
<dt>bystudy</dt>
<dd>logical to also return each study estimate (TRUE) or not</dd></dl>

Arguments

Confidence interval for an average variance — meta.ave.var

<dl>

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


<dt>var</dt>
<dd>vector of sample variances</dd>


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


<dt>bystudy</dt>
<dd>logical to also return each study estimate (TRUE) or not</dd>

</dl>

meta.ave.var: Confidence interval for an average variance

Description

Usage

Value

Arguments

Examples