rosenthal_chap5_q2

Exercise 2 from Chapter 5 (table on p. 147) in Rosenthal and Rosnow (2000)

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

rosenthal_chap5_q2 function

a data frame with 12 rows and 4 columns<dl>
 <dt>dv</dt>
<dd>dependent variable: rating of degree of complexity of social
 interaction from a series of clips</dd> <dt>id</dt>
<dd>unique identifier of participant</dd> <dt>within</dt>
<dd>within variable: complexity of interaction (low, medium
 high)</dd> <dt>between</dt>
<dd>between variable: cognitive complexity of participant (high
 or low)</dd>
</dl>

Format

Complexity data set by Rosenthal and Rosnow (2000) — rosenthal_chap5_q2

a data frame with 12 rows and 4 columns<dl>
 <dt>dv</dt>
<dd>dependent variable: rating of degree of complexity of social
 interaction from a series of clips</dd>

 <dt>id</dt>
<dd>unique identifier of participant</dd>

 <dt>within</dt>
<dd>within variable: complexity of interaction (low, medium
 high)</dd>

 <dt>between</dt>
<dd>between variable: cognitive complexity of participant (high
 or low)</dd>


</dl>

rosenthal_chap5_q2: Complexity data set by Rosenthal and Rosnow (2000)

Description

Usage

Arguments

Format