Week 11

Question 1

What is one way to think about an ANCOVA?

Answer 1

A statistical control procedure.

Question 2

What are the two applications of ANCOVA?

Answer 2

1. elimination of experimental confounds

2. clarification of experimental findings

Question 3

What is the benefit of ANCOVA?

Answer 3

Allows a more sensitive test of treatment effects (as you are have higher control)

Question 4

What is a good way of adjusting peoples scores after the test to compare what they would be, if they had the same baseline?

Answer 4

ANCOVA

Question 5

How can we clarify experimental findings of MANOVA?

Answer 5

A step-down ANCOVA analysis, to determine which set of correlated DV’s was (most) responsible for a significant MANOVA.

Question 6

What is being measured in an ANCOVA?

Answer 6

• main effect of treatment
• ‘main effect’ of covariate
• interaction between the treatment and the CV

Question 7

Describe what we are testing when we test the main effect of treatment in an ANCOVA?

Answer 7

Tests whether the means of the groups are significantly different after controlling for the effect of the CV on the DV.

Question 8

If there is no significant main covariate effect in ANCOVA, what does tis tell us?

Answer 8

That there’s essentially is no point controlling for it. In other words, you don’t need to do a ANCOVA.

Question 9

If the linear regressions lines in ANCOVA are parallel (have the same slope) for each experimental group, then we can do what

Answer 9

Pick the mid point of the covariate and identify the size of the difference between groups on the DV.

Question 10

What is one assumption regarding linearity in ANCOVA?

Answer 10

The the lines are parallel/slopes are the same.

This is really important.

Question 11

if the covariate against the DV linear regression lines in ANCOVA are different for different grades, what does this mean?

Answer 11

That the size of the difference between the groups, is going to be not the same at different levels of the covariate.

Question 12

What do we do if the linear regression lines in ANCOVA are not parallel?

Answer 12

We have to come up with a really good reason as to why we you are comparing the groups at certain values of the covariates and not others.

Question 13

What is it called when you have parallel linear lines in an ANCOVA?

Answer 13

homogeneity

Question 14

What is an interaction between the IV and the CV actually telling us in ANCOVA?

Answer 14

Would tell us whether the slope of the DV-CV regression line is the same for each treatment group.
Non significant interaction tells us we have parallel lines.

Question 15

Does ANCOVA have an interaction analysis term?

Answer 15

No - it ASSUMES that the slope if the same for all groups (homogeneity)

Question 16

What is the main effect of the IV in ANCOVA telling us?

Answer 16

Are the intercepts for the regression lines for each group the same.

If not, then there is a significant difference between the groups on the DV when the CV = 0.

Question 17

What does it tell us if we have a significant interaction in and ANCOVA?

Answer 17

Tells us we do not have equal slopes in both groups (BAD)

Question 18

If the CV X IV interaction is non-significant:

Answer 18

then we have homogeneity of slopes for each group.

Question 19

If the CV X IV interaction is significant:

Answer 19

then the slope on the DV and CV is not the same for each group.

Question 20

What are the assumptions for ANOVA and ANCOHET?

Answer 20

1. linear relationships between CV and DV
2. Normal distribution of scores, homogeneity of variance and independence of residuals
3. homogeneity of regression

Question 21

Homogeneity of regression is assumed in ANCOVA, but is:

Answer 21

Explicitly testes in ANCOHET.

Question 22

In a perfect world, what relationship do we want between the CV and the IV?

Answer 22

No relationship.

Question 23

How can we determine the relationship between the CV and the IV?

Answer 23

Perform a one way ANOVA with CV as the DV, and the treatment as the IV. If significant, then the IV and CV are not independent.

Question 24

What happens if there is a significant relationship between the the IV and the CV?

Answer 24

Then if we were to remove the CV, it may remove some of the variance in the real treatment effect (leave a type 2 error).

Question 25

How can we use the different DV’s in MANOVA to do a step-down analysis?

Answer 25

We can turn one of the DV’s into a covariate and do an ANCOVA step-down analysis to see if IV is having an effect on one DV, or on both together.

Question 26

How do we go about doing an ANCOVA in a step-down analysis following a MANOVA?

Answer 26

The DV which is deemed to be the most important (based on theoretical considerations) is tested first in a univariate ANOVA. The remaining DV’s are then successively tested in univariate ANVOCA’s using the first DV as a covariate.

Question 27

What happens if our ANCOVA step-down analysis is not significant?

Answer 27

We can interpret that the DV does not add anything that has not already been accounted for by the most important DV.

Question 28

What happens if our ANCOVA step-down analysis is significant?

Answer 28

It means that the IV has an impact on the DV beyond the impact that it had on the most important DV (adds unique variance).

Question 29

What does ANCOVA do with DV score adjustment?

Answer 29

Adjusts individual scores on the DV to what it would be if everyone had the same score on the covariate.