ANCOVA

Question 1

What does ANCOVA stand for?

Answer 1

Analysis of covariance

Question 2

What does the ANCOVA test for?

Answer 2

whether there is a difference between groups while controlling for the effects of other continuous variables that are not of primary interest but could influence the results.

Question 3

What are these continuous variables known as?

Answer 3

Covariates

Question 4

What is the effect if adding a covariate?

Answer 4

Reduces error in the model

Question 5

How do the assumptions for the ANCOVA compare to the ANOVA?

Answer 5

The same but two additional assumptions:

1. Independence of covariate and treatment conditions - the covariate is independent of the effect of the independent variable
2. Homogeneity of regression slopes- The assumption that the relationship between the covariate and the dependent variable holds for all levels of the independent variable.

Question 6

What does it mean if the independence of covariate and treatment conditions assumption is not met? What effect does this have on the f statistic?

Answer 6

A part of the experimental effect will be explained by the covariate, while it should explain part of the error variance. This will reduce the F statistic

Question 7

How can the independence of covariate and treatment conditions assumption be controlled for?

Answer 7

Randomizing participants to experimental groups or by matching groups to the covariate

Question 8

How can the assumption of homogeneity of regression slope be tested for?

Answer 8

using a scatterplot of the interaction effect or on SPSS by building terms and checking the interaction effect between the independent variable and the covariate.

Question 9

What is the partial eta squared?

Answer 9

the effect size which takes the covariates into account. It uses the proportion of variance that a variable explains that is not explained by other variables in the analysis.

SSmodel / SSmodel+SSerror