anofaES

The function <code>anofaES()</code> compute effect size from observed frequencies
according to the ANOFA framework. See lc23b;textualANOFA for more.

Analyses of frequencies can be performed using an alternative test based
on the G statistic. The test has similar type-I error rates and power as
the chi-square test. However, it is based on a total statistic that can be
decomposed in an additive fashion into interaction effects, main effects, simple
effects, contrast effects, etc., mimicking precisely the logic of ANOVA. We call
this set of tools 'ANOFA' (Analysis of Frequency data) to highlight its
similarities with ANOVA. This framework also renders plots of frequencies
along with confidence intervals. Finally, effect sizes and planning statistical
power are easily done under this framework. The ANOFA is a tool that assesses
the significance of effects instead of the significance of parameters; as such,
it is more intuitive to most researchers than alternative approaches based on
generalized linear models.
See Laurencelle and Cousineau (2023) <doi:10.20982/tqmp.19.2.p173>.

Denis Cousineau

ANOFA

Analyses of Frequency Data

Louis Laurencelle

Pier-Olivier Caron

anofaES function

<dl><dt>props</dt>
<dd>the expected proportions;</dd></dl>

Arguments

Computing effect size within the ANOFA. — anofaES

<dl>

<dt>props</dt>
<dd>the expected proportions;</dd>

</dl>

anofaES: Computing effect size within the ANOFA.

Description

Usage

Value

Arguments

Details

References

Examples