wellbeing_ind

<p>This is a synthetic dataset from Geoff Cumming. 20 students were randomly
assigned to spend the afternoon reading in the library—the Control condition
—or reading in the local botanical gardens—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