cohen_d_standardizers

Compute the standardizers for Cohen's d

Data Analysis using Bootstrap-Coupled ESTimation.
Estimation statistics is a simple framework that avoids the pitfalls of
significance testing. It uses familiar statistical concepts: means,
mean differences, and error bars. More importantly, it focuses on the
effect size of one's experiment/intervention, as opposed to a false
dichotomy engendered by P values.
An estimation plot has two key features:
1. It presents all datapoints as a swarmplot, which orders each point to
display the underlying distribution.
2. It presents the effect size as a bootstrap 95% confidence interval on a
separate but aligned axes.
Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105.
<doi:10.1038/s41592-019-0470-3>.
The free-to-view PDF is located at <https://rdcu.be/bHhJ4>.

Joses W. Ho

dabestr

Data Analysis using Bootstrap-Coupled Estimation

Tayfun Tumkaya

cohen_d_standardizers function

<dl><dt>x1</dt>
<dd>A vector of values.</dd>
<dt>x2</dt>
<dd>Another vector of values.</dd></dl>

Arguments

Compute the standardizers for Cohen's d — cohen_d_standardizers

<dl>

<dt>x1</dt>
<dd>A vector of values.</dd>


<dt>x2</dt>
<dd>Another vector of values.</dd>

</dl>

cohen_d_standardizers: Compute the standardizers for Cohen's d

Description

Usage

Value

Arguments