stdmean2.from.t

This function computes Cohen's d for a 2-group design (which is a
standardized mean difference with a weighted variance standardizer) using
a pooled-variance independent-samples t statistic and the two sample sizes.
This function also computes the standard error for Cohen's d. The Cohen's d
estimate and standard error assume equality of population variances.

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

stdmean2.from.t function

<dl><dt>t</dt>
<dd>pooled-variance t statistic</dd>
<dt>n1</dt>
<dd>sample size for group 1</dd>
<dt>n2</dt>
<dd>sample size for group 2</dd></dl>

Arguments

Computes Cohen's d from pooled-variance t statistic — stdmean2.from.t

<dl>

<dt>t</dt>
<dd>pooled-variance t statistic</dd>


<dt>n1</dt>
<dd>sample size for group 1</dd>


<dt>n2</dt>
<dd>sample size for group 2</dd>

</dl>

stdmean2.from.t: Computes Cohen's d from pooled-variance t statistic

Description

Usage

Value

Arguments

Examples