factorial ANOVA (independent design)

Question 1

what are factorial ANOVAs used to test

Answer 1

used to test for differences when we have more than one IV

including more than one IV, we can explore the effects of each IV and interactions between IVs

each IV will have 2 or more levels

Question 2

what are the three broad factorial ANOVA designs

Answer 2

all IVs are between-subjects (independent)

all IVs are within subjects (repeated measures)

a mixture of between subjects and within subjects (mixed)

Question 3

terminology factorial ANOVAs

Answer 3

• The terms IV and Factor are interchangeable
• Factorial ANOVAs can include:
  2-way independent ANOVA
  4-way independent ANOVA
  3-way repeated measures ANOVA
  2-way mixed ANOVA
  etc…
• IVs always have at least 2 levels
  22 ANOVA: 2 IVs, each with 2 levels
  24 ANOVA: 2 IVs, one with 2 levels and one with 4 levels
• 422 ANOVA: 3 IVs, one with 4 levels and two with two levels

Question 4

what does a factorial ANOVA tell us about and control for

Answer 4

tells us about interaction effects and tells us about interactions

Question 5

hypothesis testing independent factorial ANOVA

Answer 5

Calculate F for each effect (the two main effects and the hypothesis

Create a null hypothesis for the effect of X on Y, the effect of Z on Y and the interaction of X and Z

X has no effect on Z (no mean difference between populations)
-ignore Y
Y has no effect on Z (no mean difference between populations)
-ignore X
There is no interaction between X and Y

Question 6

variance between IV levels is a sum of (2 way independent factorial ANOVA)

Answer 6

IV1, IV2 and interaction (IV1*IV2)

Question 7

partitioning the variance: 3 way independent ANOVA

Answer 7

IV1
IV2
IV3
IV1IV2
IV1IV3
IV2IV3
IV1IV2*IV3
error

Question 8

interaction effects

Answer 8

combined effect of multiple factors on the DV

a significant interaction indicates that the effect of manipulating one IV depends on the level of another

Question 9

for a main effect to be genuine and meaningful…

Answer 9

it would influence measurement of the DV across all conditions

Question 10

assumptions independent factorial ANOVA

Answer 10

Normality

Homogeneity of variance:
-SPSS check with Levene’s test
-no correction!

Equivalent sample size

Independence of observations

Question 11

which post hoc test to use for independent factorial ANOVA

Answer 11

tukey hsd

Question 12

what does the presence of an interaction suggest

Answer 12

The presence of an interaction suggest we need to consider differences at the level of cell means (simple effects)
-the effect of the main IV at different levels of the secondary IV

Question 13

simple effect

Answer 13

the effect of an IV at a single level of another IV

comparison of cell means (conditions)