Week 8 (ANCOVA)

Question 1

What does ANCOVA stand for

Answer 1

Analysis of Covariance

Question 2

What is an ANCOVA

Answer 2

-Type of linear model that combines the best abilities of linear regression with the best of ANOVA
-Includes one or more continuous variable (covariates) within the ANOVA
-Allows you to test differences in group means and interactions, just like ANOVA

Question 3

What is a covariate

Answer 3

-Other variables that might also influence the result
-These variables might also influence the DV are referred to as covariates in ANCOVA
-We include the covariates in the model to adjust for the influence they have on the DV

Question 4

How do covariates influence ANOVA results

Answer 4

-The error variance (F value equation) includes uncontrolled sources of variability
-Some of error variance may be caused by covariates

Question 5

F ratio equation

Answer 5

(Variance between conditions) divided by (Variance within conditions)

Question 6

Including variates to reduce error variance

Answer 6

-WITHOUT the covariate included in the analysis, it is part of the error variance (which is used to calculate F ratio)
-WITH the covariate included, error variance is reduced as variance due to the covariate is removed –> F ratio?

Question 7

Methods for controlling for covariation

Answer 7

-Random allocation: Of participants to conditions to minimise the influence
-Match participants: In different conditions to minimise the influence of covariates
-Statistically: Analysis of Covariance

Question 8

Reasons to include covariates in ANOVA

Answer 8

1. Reduces within group ‘error’ variance (the bottom half of the ratio/ unexplained variance)
2. Controls for the influence of the covariates on the DV (in other words, eliminating confounding effects from the covariates)

Question 9

Not everything can be a co-variate

Answer 9

1. Covariates should be continuous (e.g., not categorical)
2. There should be a theoretical reason for including a covariate (e.g., based on theories or previous literature)

Question 10

ANCOVA Assumptions

Answer 10

1. Linear relationship between the covariate and the DV at each level of the IV
2. Homogeneity of Regression Slopes
3. Independence of the covariate and experiment effect

Question 11

How can we test the assumption of a linear relationship between the covariate and the DV at each level of the IV

Answer 11

-Relationship can be positive or negative
-Check this by drawing scatterplots to show the relationships between the covariate and DV

Question 12

How can we test the assumption of Homogeneity of Regression Slopes