Main Effects: Factorial Design
Main effect = separate effects of each independent variable regardless of the other independent variable
- A 2 X 2 factorial designs yields 2 main effects, one for each factor
- The row mean differences depict the main effect for one factor
- The column mean differences depict the main effect for the second factor
- When there is a difference in means between levels of a factor, then a main effect may be present. A statistical analysis (e.g., 2-way ANOVA) must be applied to verify whether a significant difference between mean scores/ratings exist.
|
|
Shampoo A |
Shampoo B |
|
|
Sunny |
1 |
3 |
Sunny (1+3)/2=2 |
|
Humid |
2 |
6 |
Humid (2+6)/2=4 |
|
|
Shampoo A (1+2)/2=1.5 |
Shampoo B (3+6/2) =4.5 |
|
There may be a main effect of shampoo because shampoo A mean score (1.5) differs from shampoo B mean score (4.5).
There may be a main effect of weather because sunny mean score (2) differs from humid mean score (4).
Use of statistical analyses would allow determination of whether significant differences in mean ratings between conditions exist.
