explain

'explain()' provides a human-readable, exhaustive, description of
the results. It also provides references to the key results.

Analyses of Proportions can be performed on the Anscombe (arcsine-related) transformed
data. The 'ANOPA' package can analyze proportions obtained from up to
four factors. The factors can be within-subject or between-subject or a mix
of within- and between-subject. The main, omnibus analysis can be followed by
additive decompositions into interaction effects, main effects, simple
effects, contrast effects, etc., mimicking precisely the logic of ANOVA. For
that reason, we call this set of tools 'ANOPA' (Analysis of Proportion
using Anscombe transform) to highlight its similarities with ANOVA.
The 'ANOPA' framework also allows plots of proportions easy to obtain
along with confidence intervals. Finally, effect sizes and planning statistical
power are easily done under this framework. Only particularity, the 'ANOPA' computes
F statistics which have an infinite degree of freedom on the denominator.
See Laurencelle and Cousineau (2023) <doi:10.3389/fpsyg.2022.1045436>.

Denis Cousineau

ANOPA

Analyses of Proportions using Anscombe Transform

Louis Laurencelle

explain function

<dl><dt>object</dt>
<dd>an object to explain</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

explain — explain

<dl>

<dt>object</dt>
<dd>an object to explain</dd>


<dt>...</dt>
<dd>ignored</dd>

</dl>

explain: explain

Description

Usage

Value

Arguments