Average Process
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Why does the single factor design form a minority in psychology?
- too simple to address complex questions
- can give a false impressio of importance of a factor
Why is it useful that in a factorial design, 2 or more factors are varied simultaneously?
- can address more complicated research questions
- can identify interactions between factors
How is a factorial design referenced?
- By the number of its factors
- Factors are referenced by name
- Levels of a factor are referenced by subscripts
How do you calculate the total number of treatments?
Multiplying the levels of each factor
What is a fully between-participants factorial design?
A design that contains factors that are all manipulated between-participants
What is a fully within-participants factorial design?
A design containing factors that are all manipulated within-participants
What is a mixed factorial design?
A design containing a mixture of factors that are manipulated between or within participants
Is there a limit on the number of levels in a factor?
No
What are the 3 possible outcomes in a factorial experiment?
- Main effects
- Simple main effects
- Interaction
Which is the simplest outcome?
Main effects
What are main effects?
They represent the overall difference in means of one factor, ignoring the others.
What are the 3 possible outcomes in terms of the main effects?
- No significant main effects
- One significant main effects
- Two significant main effects
What outcome is this in terms of main effects?
No significant main effects
What outcome do these show in terms of main effects?
One significant main effect
What outcome is this in terms of main effects?
Two significant main effects
What are simple main effects?
They break down main effects into their component parts
What are the simple main effects of this?
- Simple main effect of factor A at B2 and B1
- Simple main effect of factor B at A1 and A2
- The 2 simple effects for each factor were identical to overall main effect
What is an intraction?
The way one factor is related to the DV may depend on the level of the second factor.
If there is an interaction how do you interpret results?
- You can't interpret results in terms of the main effects
- You need to determine how the facyors are combining to influence the DV by looking at the simple main effects
Does this show an interaction?
Yes
How do you spot an interaction?
If a line plot has non-parallel lines it is indicative of the presence of an interaction
What are 3 examples of an interaction
=
What is the problem with a tightly compressed scale?
It can create an illusion of an interaction
Are simple main effects independent or dependent?
Independent- not all simple main effects have to be significant, some will some won't
Why factorial designs?
- The effect of a dactor in a single-factor desgin can be misleading and conceal a potential interaction
- It helps reach an appropriate conclusion
Why do you need an adequate sample size?
- To protect against type 2 errors
What is an adequate sample size per cell?
20
What does a factorial ANOVA produce?
An F ratio and p value for each main effect and interaction
In a two-factor desing what doe these values mean?
- F-ratio and p value for the main effect of factor A
- F ratio and p value for the main effect of factor B
- F ratio and p value for the A x B interaction