schwoebel

For the entire dataset and analysis scripts see:

datasets

Contrast analysis for factorial designs provides an
alternative to the traditional ANOVA approach, offering the distinct
advantage of testing targeted hypotheses. The foundation of this
package is primarily rooted in the works of Rosenthal, Rosnow, and
Rubin (2000, ISBN: 978-0521659802) as well as Sedlmeier and Renkewitz
(2018, ISBN: 978-3868943214).

Johannes Titz

cofad

Contrast Analyses for Factorial Designs

Markus Burkhardt

Mirka Henninger

Simone Malejka

schwoebel function

a data frame with 64 rows and 2 variables:<dl>
 <dt>condition</dt>
<dd>experimental condition (massed-same, massed-different,
 spaced-same, spaced-different)</dd> <dt>percent_recalled</dt>
<dd>dependent variable</dd>
</dl>

Format

Data from Schwoebel et al. (2018) — schwoebel

a data frame with 64 rows and 2 variables:<dl>
 <dt>condition</dt>
<dd>experimental condition (massed-same, massed-different,
 spaced-same, spaced-different)</dd>

 <dt>percent_recalled</dt>
<dd>dependent variable</dd>


</dl>

schwoebel: Data from Schwoebel et al. (2018)

Description

Usage

Arguments

Format