etasqr.adj

Computes an approximate bias adjustment for eta-squared. This adjustment
can be applied to eta-squared, partial-eta squared, and generalized
eta-squared estimates.
For more details, see Section 3.7 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.adj function

<dl><dt>etasqr</dt>
<dd>unadjusted eta-square estimate</dd>
<dt>dfeffect</dt>
<dd>degrees of freedom for the effect</dd>
<dt>dferror</dt>
<dd>error degrees of freedom</dd></dl>

Arguments

Bias adjustment for an eta-squared estimate — etasqr.adj

<dl>

<dt>etasqr</dt>
<dd>unadjusted eta-square estimate</dd>


<dt>dfeffect</dt>
<dd>degrees of freedom for the effect</dd>


<dt>dferror</dt>
<dd>error degrees of freedom</dd>

</dl>

etasqr.adj: Bias adjustment for an eta-squared estimate

Description

Usage

Value

Arguments

References

Examples