ci.random.anova

Computes estimates and confidence intervals for four parameters of the
one-way random effects ANOVA: 1) the superpopulation grand mean, 2) the
square-root within-group variance component, 3) the square-root
between-group variance component, and 4) the omega-squared coefficient.
This function assumes equal sample sizes.

Implements confidence interval and sample size methods that
are especially useful in psychological research. The methods can be
applied in 1-group, 2-group, paired-samples, and multiple-group designs
and to a variety of parameters including means, medians, proportions,
slopes, standardized mean differences, standardized linear contrasts
of means, plus several measures of correlation and association.
Confidence interval and sample size functions are given for single
parameters as well as differences, ratios, and linear contrasts of
parameters. 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 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

ci.random.anova function

<dl><dt>alpha</dt>
<dd>1 - alpha confidence</dd>
<dt>m</dt>
<dd>vector of estimated group means</dd>
<dt>sd</dt>
<dd>vector of estimated group standard deviations</dd>
<dt>n</dt>
<dd>common sample size in each group</dd></dl>

Arguments

Confidence intervals for parameters of one-way random effects ANOVA — ci.random.anova

<dl>

<dt>alpha</dt>
<dd>1 - alpha confidence</dd>


<dt>m</dt>
<dd>vector of estimated group means</dd>


<dt>sd</dt>
<dd>vector of estimated group standard deviations</dd>


<dt>n</dt>
<dd>common sample size in each group</dd>

</dl>

ci.random.anova: Confidence intervals for parameters of one-way random effects ANOVA

Description

Usage

Value

Arguments

Examples