rm2_data

Example data for a mixed repeated-measures two-way ANOVA examining the
effect of instruction type and forward/backward strength in word
associations. Designed for use with <code>omega.partial.SS.rm</code>
and other repeated measures ANOVA designs.
The dataset contains a between-subjects variable for instruction type,
a subject identifier, and four repeated-measures conditions:
- FSG (forward strength): e.g., "cheddar" → "cheese"
- BSG (backward strength): e.g., "cheese" → "cheddar"
Forward and backward strength were manipulated to measure overestimation of
association strength.

datasets

Measure of the Effect ('MOTE') is an effect size calculator, including a
wide variety of effect sizes in the mean differences family (all versions of d) and
the variance overlap family (eta, omega, epsilon, r). 'MOTE' provides non-central
confidence intervals for each effect size, relevant test statistics, and output
for reporting in APA Style (American Psychological Association, 2010,
<ISBN:1433805618>) with 'LaTeX'. In research, an over-reliance on p-values
may conceal the fact that a study is under-powered (Halsey, Curran-Everett,
Vowler, & Drummond, 2015 <doi:10.1038/nmeth.3288>). A test may be statistically
significant, yet practically inconsequential (Fritz, Scherndl, & Kühberger, 2012
<doi:10.1177/0959354312436870>). Although the American Psychological Association
has long advocated for the inclusion of effect sizes (Wilkinson & American
Psychological Association Task Force on Statistical Inference, 1999
<doi:10.1037/0003-066X.54.8.594>), the vast majority of peer-reviewed,
published academic studies stop short of reporting effect sizes and confidence
intervals (Cumming, 2013, <doi:10.1177/0956797613504966>). 'MOTE' simplifies
the use and interpretation of effect sizes and confidence intervals.

Erin M. Buchanan

MOTE

Effect Size and Confidence Interval Calculator

Amber M Gillenwaters

John E. Scofield

K. D. Valentine

rm2_data function

A data frame with 6 variables:<dl>
 <dt>group</dt>
<dd>Factor. Between-subjects variable indicating the
type of instructions given.</dd> <dt>subject</dt>
<dd>Integer or factor. Subject identifier.</dd> <dt>fsglobsglo</dt>
<dd>Numeric. Low FSG, low BSG condition.</dd> <dt>fsghibsglo</dt>
<dd>Numeric. High FSG, low BSG condition.</dd> <dt>fsglobsghi</dt>
<dd>Numeric. Low FSG, high BSG condition.</dd> <dt>fsghibsghi</dt>
<dd>Numeric. High FSG, high BSG condition.</dd>
</dl>

Format

Repeated Measures Two-Way ANOVA Example Data — rm2_data

A data frame with 6 variables:<dl>
 <dt>group</dt>
<dd>Factor. Between-subjects variable indicating the
type of instructions given.</dd>

 <dt>subject</dt>
<dd>Integer or factor. Subject identifier.</dd>

 <dt>fsglobsglo</dt>
<dd>Numeric. Low FSG, low BSG condition.</dd>

 <dt>fsghibsglo</dt>
<dd>Numeric. High FSG, low BSG condition.</dd>

 <dt>fsglobsghi</dt>
<dd>Numeric. Low FSG, high BSG condition.</dd>

 <dt>fsghibsghi</dt>
<dd>Numeric. High FSG, high BSG condition.</dd>


</dl>

rm2_data: Repeated Measures Two-Way ANOVA Example Data

Description

Usage

Arguments

Format