Flashcards in 8. Factorial ANOVA Deck (41):

1

## When would you use a factorial ANOVA?

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

2

## What are the 3 types of factorial designs?

###
Between subjects

Within subjects (repeated measures)

Mixed model (both)

3

## What are the 2 types of factors?

###
Fixed (sex)

Random

4

## What can't you do with a fixed factor model?

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

5

## What is an example of a random factor?

### Randomly selecting different class times from a set of possibilities

6

## How are factorial designs labelled?

###
Number of factors by number of levels

e.g. sex (2) and rival (4)

= 2 x 4 design

7

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

###
Main

Interaction

Simple

8

## What is the main effect?

### The separate effect of each independent variable

9

## What is an interaction effect?

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

10

## How is an interaction effect represented in a line graph?

### Straight lines that are NOT parallel

11

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

### No main effects - all interaction effects

12

## When are simple effects examined in an ANOVA?

### When there's a statistically sig. interaction effect

13

## How do you compute simple effects?

###
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

14

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

###
SS1 = Main effect IV1

SS2 = Main effect IV2

SS1*2 = Interaction

15

## Total variance in the SPSS output is given as?

###
Corrected Total's Type II Sum of Squares

(in between subjects box)

16

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

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

(if equal size = sum of 3 effects)

17

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

###
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

18

## What is reported from a factorial ANOVA for effect size?

###
R Sq Adj or Partial Eta Sq

Converted to a %

19

## What is observed power?

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

20

## Why would you look at observed power?

###
If non sig. F = gives explanation

21

## What do you report when writing our ANOVA results?

###
Sig./Non Sig. effect for IV, F(x,x) = x, p = x (tailed),

eta sq = x (effect size),

obs. power = x

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)?

###
Sig. Main Effect = Contrasts or Pairwise Comparisons

Sig. Interaction = Simple Effects

23

## How do you obtain the effect size for simple effects?

### Syntax

24

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

### Scores on the dependent variable must be distributed normally within groups

25

## What are the assumptions for an Independent groups factorial ANOVA?

###
Normality

Homogeneity of Variance

Independence

Proportionality

26

## How is Independence tested in an Independent Groups Factorial ANOVA?

###
Chi Square test on IV's

(should be non sig.)

27

## What is proportionality?

### All cell sizes equal or proportional

28

## How is proportionality tested?

###
By checking the number of participants in each cell.

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

29

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

###
Once for each cell

30

## What two conditions need to be met to achieve Independence?

###
Participants not in more than 1 group

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

31

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

###
Phi co-efficient (2 x 2 design)

Contingency co-efficient Cramer's V

32

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

### Once for each pair of variables

33

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

### Type II SS in SPSS

34

## If normality is violated in a factorial ANOVA?

###
Transformation

Bootstrap

35

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

###
When the largest group variance is more than 4 x the smallest

Different Groups skewed in different directions on the DV

36

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

###
Don't use an ANOVA

Dummy code variables and use in a regression

37

## When is the harmonic mean used?

### When proportionality is violated to calculate equally weighted means

38

## When would you use SS Type I?

###
Non-experimental research (sample sizes reflect importance of cells).

Effects have unequal priority.

39

## When would you use SS Type II?

###
Non-experimental research (sample sizes reflect importance of cells).

Main effects have equal priority.

40

## When would you use SS Type III?

###
Experiments designed to be equal

All cells equally important.

41