meta.lc.agree

Computes the estimate, standard error, and adjusted Wald confidence
interval for a linear contrast of G-index of agreement coefficients
from two or more studies. This function assumes that two raters each
provide a dichotomous rating for a sample of objects.

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.lc.agree function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>f11</dt>
<dd>vector of frequency counts in cell 1,1</dd>
<dt>f12</dt>
<dd>vector of frequency counts in cell 1,2</dd>
<dt>f21</dt>
<dd>vector of frequency counts in cell 2,1</dd>
<dt>f22</dt>
<dd>vector of frequency counts in cell 2,2</dd>
<dt>v</dt>
<dd>vector of contrast coefficients</dd></dl>

Arguments

Confidence interval for a linear contrast of G-index coefficients — meta.lc.agree

<dl>

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


<dt>f11</dt>
<dd>vector of frequency counts in cell 1,1</dd>


<dt>f12</dt>
<dd>vector of frequency counts in cell 1,2</dd>


<dt>f21</dt>
<dd>vector of frequency counts in cell 2,1</dd>


<dt>f22</dt>
<dd>vector of frequency counts in cell 2,2</dd>


<dt>v</dt>
<dd>vector of contrast coefficients</dd>

</dl>

meta.lc.agree: Confidence interval for a linear contrast of G-index coefficients

Description

Usage

Value

Arguments

References

Examples