wellbeing_ind

<p>This is a synthetic dataset from Geoff Cumming. 20 students were randomly
assigned to spend the afternoon reading in the library&lt;U+2014&gt;the Control condition
&lt;U+2014&gt;or reading in the local botanical gardens&lt;U+2014&gt;the Test condition. At the end of
the session, each student completed a measure of his or her perceived
well-being.</p>

datasets

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

wellbeing_ind function

<p>A list with two elements: <code>control</code> and <code>test</code>.</p>

wellbeing_ind: Wellbeing Scores (2 independent groups).

Description

Usage

Arguments

Format

Details