Week 4: 2-way ANOVA

Question 1

What is a 2-factor ANOVA?

Answer 1

Factor = IV

Has 2 IVs that have 2+ levels

Question 2

What is the purpose of a 2-factor ANOVA?

Answer 2

To see how the two variables interact to affect the DV

Question 3

How is the ANOVA labeled?

Answer 3

a x b

a and b represent the number of levels in the 2 IVs

Question 4

What results from a 2-factor ANOVA?

Answer 4

Results in 2 main effects and an interaction effect to be reported

Question 5

What is the null for the main effects and the interaction effect?

Answer 5

Main effects: means are all equal for all levels of IV

Interaction: no difference in the effect of IVa at all levels of IVb (the affect of A is the same at all levels of B)

Question 6

What do you do with a significant main effect?

Answer 6

If only 2 levels: no further tests are required as it is obvious where the differences lie
2+ levels: follow up tests required (tukey or bonferonni–adjusted t tests)

Question 7

What do you do with a significant interaction?

Answer 7

You don’t report main effects in depth as this overrides them.

Need to do tests of simple main effects to clarify the interaction
- Bonferonni adjustment

Question 8

How would you set out a 2 factor ANOVA in jamovi (between)?

Answer 8

1x column for each IV and the DV

1x row per participant

Question 9

What do you do if the main effects and the interaction effect are not significant?

Answer 9

Just report - no further tests

Question 10

How do you do the analysis in Jamovi for a 2 factor ANOVA?

Answer 10

Linear models - general linear models

DV - DV box
IVs - factors box
Partial eta squared

Homogeneity tests
Descriptives - through explore tab or estimated marginal means

Question 11

If simple main effects on the interaction are significant, what do you do next?

Answer 11

If 2+ levels

Run separate one-way ANOVAs by filtering the data to one level of an IV