Week 14: Mixed Factorial ANOVA

Question 1

• What is a mixed factorial ANOVA? What is the purpose of this method?

Answer 1

Mixed = you have IVs that are between-subjects and within-subjects

Factorial = also called factors – another word to mean independent variables

Purpose: To examine mean differences based on both between-subjects and within-subjects variables in an analysis

*Remember
Between-subjects – a person only participates in one level

Within-subjects – a person participates in ALL levels

Question 2

• IVs and DV: categorical or continuous?

Answer 2

Between-subjects IV = categorical
Example: male vs. female

Within-subjects IV = categorical
Example: taking both test 1 and test 2

DV = continuous
Example: test scores

Question 3

• What are the assumptions of a mixed factorial ANOVA?

Answer 3

Normality of your DV – no outliers, skewness, or kurtosis

Homogeneity of variance for your between-subjects variable

Sphericity (similar to homogeneity of variance) for your within-subjects variable

Remember, you want the variances of your groups / conditions to be similar to prevent any bias

Although you can violate homogeneity of variance, ANOVAs tend to be robust if sample size is equal

Robust means that your conclusion of a significant difference can still be considered a correct interpretation