es.d

This function takes as inputs a difference between two means and a standard deviation
and outputs the d effect size as defined by Cohen (1988),
also called the standardized mean difference.

Power and sample size calculations for a variety of study designs and
outcomes. Methods include t tests, ANOVA (including tests for interactions,
simple effects and contrasts), proportions, categorical data (chi-square tests
and proportional odds), linear, logistic and Poisson regression, alternative
and coprimary endpoints, power for confidence intervals, correlation
coefficient tests, cluster randomized trials, individually randomized group
treatment trials, multisite trials, treatment-by-covariate interaction effects
and nonparametric tests of location. Utilities are provided for
computing various effect sizes. Companion package to the book
"Power and Sample Size in R", Crespi (2025, ISBN:9781138591622).
Further resources available at <https://powerandsamplesize.org/>.

Catherine M. Crespi

powertools

Power and Sample Size Tools

Zichen Liu

Kristen M. McGreevy

es.d function

<dl><dt>delta</dt>
<dd>If one mean: muA (the true mean) - mu0 (the mean under the null). If two means: DeltaA (the true difference mu1 - mu2) - Delta0 (the difference under the null).</dd>
<dt>sd</dt>
<dd>The estimated standard deviation; defaults to 1.</dd></dl>

Arguments

Cohen d effect size calculation for one or two means — es.d

<dl>

<dt>delta</dt>
<dd>If one mean: muA (the true mean) - mu0 (the mean under the null). If two means: DeltaA (the true difference mu1 - mu2) - Delta0 (the difference under the null).</dd>


<dt>sd</dt>
<dd>The estimated standard deviation; defaults to 1.</dd>

</dl>

es.d: Cohen d effect size calculation for one or two means

Description

Usage

Value

Arguments

Details

Examples