Chapter 11

Question 1

Adjusted mean

Answer 1

in the context of analysis of covariance this is the value of the group mean adjusted for the effect of the covariate.

Question 2

Analysis of covariance (ANCOVA)

Answer 2

a statistical procedure that uses the F-ratio to test the overall fit of a linear model controlling for the effect that one or more covariates have on the outcome variable. In experimental research this linear model tends to be defined in terms of group means and the resulting ANOVA is therefore an overall test of whether group means differ after the variance in the outcome variable explained by any covariates has been removed.

Question 3

Covariate

Answer 3

a variable that has a relationship with (in terms of covariance), or has the potential to be related to, the outcome variable we’ve measured.

Question 4

Homogeneity of regression slopes

Answer 4

an assumption of analysis of covariance. This is the assumption that the relationship between the covariate and outcome variable is constant across different treatment levels. So, if we had three treatment conditions, if there’s a positive relationship between the covariate and the outcome in one group, we assume that there is a similar-sized positive relationship between the covariate and outcome in the other two groups too.

Question 5

Partial eta squared (partial η2)

Answer 5

a version of eta squared that is the proportion of variance that a variable explains when excluding other variables in the analysis. Eta squared is the proportion of total variance explained by a variable, whereas partial eta squared is the proportion of variance that a variable explains that is not explained by other variables.

Question 6

Partial out

Answer 6

to partial out the effect of a variable is to remove the variance that the variable shares with other variables in the analysis before looking at their relationships (see partial correlation).

Question 7

Sidak correction

Answer 7

slightly less conservative variant of a Bonferroni correction.