8. Factorial ANOVA

Question 1

When would you use a factorial ANOVA?

Answer 1

When you have more than 1 categorical IV and one numerical DV

Question 2

What are the 3 types of factorial designs?

Answer 2

Between subjects
Within subjects (repeated measures)
Mixed model (both)

Question 3

What are the 2 types of factors?

Answer 3

Fixed (sex)

Random

Question 4

What can’t you do with a fixed factor model?

Answer 4

Generalise results to other levels (e.g. can only speak about the types of rivals you used)

Question 5

What is an example of a random factor?

Answer 5

Randomly selecting different class times from a set of possibilities

Question 6

How are factorial designs labelled?

Answer 6

Number of factors by number of levels
e.g. sex (2) and rival (4)
= 2 x 4 design

Question 7

What are the 3 effects that can be examined in a factorial design?

Answer 7

Main
Interaction
Simple

Question 8

What is the main effect?

Answer 8

The separate effect of each independent variable

Question 9

What is an interaction effect?

Answer 9

When the effects of one independent variable are dependent on the levels of another independent variable = moderated

Question 10

How is an interaction effect represented in a line graph?

Answer 10

Straight lines that are NOT parallel

Question 11

If the line graph has the two lines intersect each other in a perfect cross what does this mean?

Answer 11

No main effects - all interaction effects

Question 12

When are simple effects examined in an ANOVA?

Answer 12

When there’s a statistically sig. interaction effect

Question 13

How do you compute simple effects?

Answer 13

Using a syntax with 2 families of simple effects:
IV1 e.g. 4 x rival type: m v. f
IV2 e.g. 12x male with each pairwise of rivals and female with each

Question 14

In a two-way independent groups ANOVA ho many parts make up SSB?

Answer 14

SS1 = Main effect IV1
SS2 = Main effect IV2 
SS1*2 = Interaction

Question 15

Total variance in the SPSS output is given as?

Answer 15

Corrected Total’s Type II Sum of Squares

in between subjects box

Question 16

When we don’t have equal sample sizes in the groups during a factorial ANOVA what does the Model Variance account for?

Answer 16

The 3 effects (2 x main effect and 1 x interaction effect) simultaneously

(if equal size = sum of 3 effects)

Question 17

When the F value is not sig. on one of the variables in an ANOVA, what does this mean?

Answer 17

There is no difference between the groups/ levels of that variable on the DV

e.g. IV: SEX = no difference between males and females on their ratings of jealousy

Question 18

What is reported from a factorial ANOVA for effect size?

Answer 18

R Sq Adj or Partial Eta Sq

Converted to a %

Question 19

What is observed power?

Answer 19

The likelihood of finding a sig. difference between groups in that sample size

Question 20

Why would you look at observed power?

Answer 20

If non sig. F = gives explanation

Question 21

What do you report when writing our ANOVA results?

Answer 21

Sig./Non Sig. effect for IV, F(x,x) = x, p = x (tailed),
eta sq = x (effect size),
obs. power = x

Question 22

What do you do if you get a sig. main effect vs. a sig. interaction effect (on a variable with more than 2 levels)?

Answer 22

Sig. Main Effect = Contrasts or Pairwise Comparisons

Sig. Interaction = Simple Effects

Question 23

How do you obtain the effect size for simple effects?

Answer 23

Syntax

Question 24

What is the only assumption common to all three factorial designs (independent groups, repeated measures and mixed model)?

Answer 24

Scores on the dependent variable must be distributed normally within groups

Question 25

What are the assumptions for an Independent groups factorial ANOVA?

Answer 25

Normality
Homogeneity of Variance
Independence
Proportionality

Question 26

How is Independence tested in an Independent Groups Factorial ANOVA?

Answer 26

Chi Square test on IV’s

should be non sig.

Question 27

What is proportionality?

Answer 27

All cell sizes equal or proportional

Question 28

How is proportionality tested?

Answer 28

By checking the number of participants in each cell.

Ratio of males to females must be the same in each rival

Question 29

How many times do you need to check normality in a factorial ANOVA?

Answer 29

Once for each cell

Question 30

What two conditions need to be met to achieve Independence?

Answer 30

Participants not in more than 1 group

The IVs must be unrelated (Chi Squared non sig.)

Question 31

How can the strength of the association between the IVs be tested (other than Chi Squared)?

Answer 31

Phi co-efficient (2 x 2 design)

Contingency co-efficient Cramer’s V

Question 32

How many Chi Squares must be run to check for Independence?

Answer 32

Once for each pair of variables

Question 33

If the assumption of proportionality is not met, what should you use?

Answer 33

Type II SS in SPSS

Question 34

If normality is violated in a factorial ANOVA?

Answer 34

Transformation

Bootstrap

Question 35

When is the violation of the assumption of the homogeneity of variance a problem in a factorial ANOVA?

Answer 35

When the largest group variance is more than 4 x the smallest
Different Groups skewed in different directions on the DV

Question 36

What should you do if the assumption of Independence is violated?

Answer 36

Don’t use an ANOVA

Dummy code variables and use in a regression

Question 37

When is the harmonic mean used?

Answer 37

When proportionality is violated to calculate equally weighted means

Question 38

When would you use SS Type I?

Answer 38

Non-experimental research (sample sizes reflect importance of cells).
Effects have unequal priority.

Question 39

When would you use SS Type II?

Answer 39

Non-experimental research (sample sizes reflect importance of cells).
Main effects have equal priority.

Question 40

When would you use SS Type III?

Answer 40

Experiments designed to be equal

All cells equally important.

Question 41

When would you use SS Type IV?

Answer 41

Experiments designed to be equal

Missing cells in the design.