Chapter 10 Lab 10: Factorial ANOVA
Simplicity is complex. It’s never simple to keep things simple. Simple solutions require the most advanced thinking. —Richie Norton
10.1 Does standing up make you focus more?
This lab activity uses the data from “Stand by your Stroop: Standing up enhances selective attention and cognitive control” (Rosenbaum, Mama, Algom, 2017) to teach the analysis of a 2x2 design using ANOVA. Although the research design is a 2x2 repeated meaures design, we treat the design both as repeated measures, and as a between-subjects design to illustrate how to conduct either type of ANOVA in software.
10.1.1 STUDY DESCRIPTION
Do you pay more attention when you are sitting or standing? We analyse the data from “Stand by your Stroop: Standing up enhances selective attention and cognitive control” (Rosenbaum, Mama, Algom, 2017). This paper asked whether sitting versus standing would influence a measure of selective attention, the ability to ignore distracting information.
They used a classic test of selective attention, called the Stroop effect. In a typical Stroop experiment, subjects name the color of words as fast as they can. The trick is that sometimes the color of the word is the same as the name of the word, and sometimes it is not. Here are some examples:
Congruent trials occur when the color and word match. So, the correct answers for each of the congruent stimuli shown would be to say, red, green, blue and yello. Incongruent trials occur when the color and word mismatch. The correct answers for each of the incongruent stimuli would be: blue, yellow, red, green.
The Stroop effect is an example of a well-known phenomena. What happens is that people are faster to name the color of the congruent items compared to the color of the incongruent items. This difference (incongruent reaction time - congruent reaction time) is called the Stroop effect.
Many researchers argue that the Stroop effect measures something about selective attention, the ability to ignore distracting information. In this case, the target information that you need to pay attention to is the color, not the word. For each item, the word is potentially distracting, it is not information that you are supposed to respond to. However, it seems that most people can’t help but notice the word, and their performance in the color-naming task is subsequently influenced by the presence of the distracting word.
People who are good at ignoring the distracting words should have small Stroop effects. They will ignore the word, and it won’t influence them very much for either congruent or incongruent trials. As a result, the difference in performance (the Stroop effect) should be fairly small (if you have “good” selective attention in this task). People who are bad at ignoring the distracting words should have big Stroop effects. They will not ignore the words, causing them to be relatively fast when the word helps, and relatively slow when the word mismatches. As a result, they will show a difference in performance between the incongruent and congruent conditions.
If we take the size of the Stroop effect as a measure of selective attention, we can then start wondering what sorts of things improve selective attention (e.g., that make the Stroop effect smaller), and what kinds of things impair selective attention (e.g., make the Stroop effect bigger).
The research question of this study was to ask whether standing up improves selective attention compared to sitting down. They predicted smaller Stroop effects when people were standing up and doing the task, compared to when they were sitting down and doing the task.
10.1.2 Study Methods
The design of the study was a 2x2 repeated-measures design. The first IV was congruency (congruent vs incongruent). The second IV was posture (sitting vs. standing). The DV was reaction time to name the word. There were 50 participants in the study.
10.2 Lab Skills Learned
- Conducting a 2x2 between-subjects ANOVA
- Conducting a 2x2 repeated-measures ANOVA
10.3 Important Stuff
- citation: Rosenbaum, D., Mama, Y., & Algom, D. (2017). Stand by Your Stroop: Standing Up Enhances Selective Attention and Cognitive Control. Psychological science, 28(12), 1864-1867.
- Link to .pdf of article
- Data in .csv format
10.4 JAMOVI
In this lab, we will use jamovi to:
- Conduct a Between-Subjects Two-Factor Analysis of Variance (ANOVA)
- Conduct a Repeated Measures Two-Factor Analysis of Variance (ANOVA)
10.4.1 Experiment Background
The Rosenbaum, Mama, and Algom (2017) paper asked whether sitting versus standing would influence a measure of selective attention, the ability to ignore distracting information. Selective attention here is measured as performance on the Stroop task.
In a typical Stroop experiment, subjects name the color of words as fast as they can. The trick is that sometimes the color of the word is the same as the name of the word, and sometimes it is not.
The design of the study was a 2x2 design. The first IV was congruency (congruent vs incongruent). The second IV was posture (sitting vs. standing). The DV was reaction time (RT)to name the word.
10.4.2 Conduct a Between-Subjects Two-Factor Analysis of Variance (ANOVA)
Here is a link to our data file. It is named stroopsit.sav. Notice that in this file, there are 200 rows (corresponding to 200 subjects). Each subject is categorized according to 2 independent variables: posture (whether they were in the standing or sitting condition), and congruency (whether the stimuli they received were congruent or incongruent). In this application, we are treating the design as between-subjects. This means each participant only experienced one of the following four conditions:
- congruent stand
- incongruent stand
- congruent sit
- incongruent sit
To conduct a two-factor between-subjects ANOVA with post-hoc tests in jamovi, follow these steps, and you will see the rght side of the screen update with the chosen analyses and statistics:
You can see from this output that:
- There is no main effect of posture, F(1, 196)=2.449, p=NS
- There is a main effect of congruency, F(1, 196)=43.734, p<.05 where (from looking at the plot) incongruent stimuli were processed with a longer reaction time than congruent stimuli.
- There is no interaction between posture and congruency, F(1, 196)=.497, p=NS
10.4.3 Conduct a Repeated Measures Two-Factor Analysis of Variance (ANOVA)
ext, we will use this same data but treat it as a repeated measures (within-subjects) design (just as in the original experiment). This means each person in the study experienced ALL 4 conditions.
To start, we need a new data file. Here is link. This data file is called stroopsit_RM.sav. I have set it up so that the data is arranged for a repeated-measures design. Notice that each person is represented by a single row, and the columns correspond to the 4 conditions. To conduct a two-factor repeated-subjects ANOVA with post-hoc tests in jamovi, follow these steps, and you will see the rght side of the screen update with the chosen analyses and statistics:
According to this output: 1. There is a main effect of congruency, F(1, 49)=342.45, p<.05. 2. There is a main effect of posture, F(1, 49)=7.33, p<.05. 3. There is an interaction effect between congruency and posture, F(1, 49)=8.96, p<.05.
10.4.4 Practice Problems
Below is fictitious data representing the number of milliimeters a plant has grown under several water/sunlight combinations:
| Water & Sunlight | NoWater & Sunlight | Water & NoSunlight | NoWater & NoSunlight |
|---|---|---|---|
| 1.2 | 2.4 | 3.1 | 2.5 |
| 3.0 | 1.1 | 2.2 | 3.4 |
| 2.5 | 1.2 | 2.5 | 4.2 |
| 1.6 | 2.4 | 4.3 | 2.1 |
Enter this data into jamovi as appropriate for a Two-Factor Between-Subjects ANOVA (N=16). Perform the ANOVA and report all results in standard statistical reporting format (use alpha=.05).
Enter this data into jamovi as appropriate for a Two-Factor Repeated-Measures ANOVA (N=4). Perform the ANOVA and report all results in standard statistical reporting format (use alpha=.05).