etasqr.gen.2way

Computes generalized eta-square estimates in a two-factor design where one
or both factors are classification factors. If both factors are treatment
factors, then partial eta-square estimates are typically recommended.
The eta-squared estimates from this function can be used in the
etasqr.adj function to obtain bias adjusted estimates.
For more details, see Section 3.12 of Bonett (2021, Volume 1)

Implements confidence interval and sample size methods that are especially
useful in psychological research but are also useful in educational, social science,
business, and biological research. This package includes more than 100 confidence
interval functions and more than 80 sample size functions for 1-group, 2-group,
paired-samples, and multiple-group designs and for a variety of parameters including
means, medians, proportions, slopes, standardized mean differences, standardized
linear contrasts of means, and several measures of correlation and association. The
sample size functions can be used to approximate the sample size needed to estimate
a parameter or function of parameters with desired confidence interval precision or
to perform a variety of hypothesis tests (directional two-sided, equivalence,
superiority, noninferiority) with desired power. For details about these methods see:
Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.

Douglas G. Bonett

statpsych

Statistical Methods for Psychologists

Robert J. Calin-Jageman

etasqr.gen.2way function

<dl><dt>SSa</dt>
<dd>sum of squares for factor A</dd>
<dt>SSb</dt>
<dd>sum of squares for factor B</dd>
<dt>SSab</dt>
<dd>sum of squares for A x B interaction</dd>
<dt>SSe</dt>
<dd>error (within) sum of squares</dd></dl>

Arguments

Generalized eta-squared estimates in a two-factor design — etasqr.gen.2way

<dl>

<dt>SSa</dt>
<dd>sum of squares for factor A</dd>


<dt>SSb</dt>
<dd>sum of squares for factor B</dd>


<dt>SSab</dt>
<dd>sum of squares for A x B interaction</dd>


<dt>SSe</dt>
<dd>error (within) sum of squares</dd>

</dl>

etasqr.gen.2way: Generalized eta-squared estimates in a two-factor design

Description

Usage

Value

Arguments

References

Examples