Research Methods: Ch. 12

In a 2 x 2 x 2 design, what is the number of main effects and interactions?

3 main effects and 2 interactions

4

4

8

8

Describe an interaction as a "difference in differences."

In a factorial design with two independent variables, the first two results obtained are the main effects for each independent variable. The third results is the interaction effect. Wheres the main effects are simple differences, the interaction effect is the difference in differences.

​Describe interactions in terms of "it depends."

Journalists might gloss over the details of a factorial design, but sometimes they will use the phrase "it depends" to highlight an interaction in a report of factorial design.

Explain how factorial designs can be used to test theories.

Sometimes theories make explicit claims about when an effect occurs or what causes it. Factorial designs can test such theories. Example: context dependent memory theory. Predicts that people associate items they are trying to learn with the context of the environment in which they learn them.

Explain the basic logic of three-way factorial designs.

When a factorial design has three independent variables, the number of differences to be investigated increases dramatically. In a three way design you are concerned with three main effects (one for each independent variable) plus three separate two way interactions and a three way interaction.

​Given a factorial notation (e.g., 2 x 2), identify the number of independent variables, the number of levels of each variable, the number of cells in the design, and the number of main effects and interactions that will be relevant.

● 2 x 2 x 3 ○ 3 IVs ○ 3 main effects ○ 2 levels to first IV, 2 levels to second IV, and 3 levels to third IV ○ 12 cells total ○ 2 interactions

Describe how the same 2 x 2 design might be conducted as an independent-groups factorial, a within-groups factorial, or a mixed factorial design.

● In a 2 x 2 independent-groups factorial, there will be 4 different groups of participants (different participants in each cell). ● In a 2 x 2 within-groups factorial, there will be only one group of participants. This one group participates in all 4 of the cells of the design. ● In a 2 x 2 mixed factorial design, one variable is manipulated as independent-groups and the other is manipulated as within-groups.

Be able to determine whether it is likely that there are main effects and/or an interaction effect of two independent variables from a line graph and from cell means.

● In factorial designs researchers test each independent variable to look for a main effect. A main effect is the overall effect of one independent variable on the dependent variable, averaging over the levels of the other independent variable. In other words, a main effect is a simple difference. In a factorial design with two independent variables, there are two main effects. ● Look at graphs in book

Be able to distinguish between the various types of factorial designs (independent-groups, within-groups, and mixed factorial designs).

● Independent groups: Also known as between subjects factorial, both independent variables are studied as independent groups. Therefore if the design is 2 x 2 there are four different groups of participants in the experiment ● Within groups: also called repeated measures factorial, both independent variables are manipulated as within groups. Therefore if the design is 2 x 2 there is only one group of participants, but they participate in all four combinations or cells of the design. ● Mixed factorial: one independent variable is manipulated as independent groups and the other is manipulated as within groups.

Explain two reasons to conduct a factorial study.

● One reason researchers conduct studies with factorial designs is to test whether an independent variable affects different kinds of people, or people in different situations in the same way ● Another reason is Factorial designs can test theories: Researchers can use interactions to test theories

What does the notation (e.g., 2 x 2, 3 x 4, 2 x 2 x 3) indicate about the number of independent variables in a study? How does it convey the number of cells?

● The quantity of numbers indicates the number of independent variables. The value of each number indicates how many levels there are for each IV. When the two numbers are multiplied together, you get the total number of cells in the design. ● example) 3 x 4 factorial design ○ 2 IVs → 2 main effects w/ one interaction ○ One IV has 3 levels, the other IV has 4 levels ○ 12 cells total

Articulate how a factorial design works.

● When researchers want to test for interactions, they do so with factorial designs. This when there are two or more independent variables (also referred to as factors) In the most common factorial design, researchers across the two independent variables, they study each possible combination of the independent variables.

Explain how different designs change the number of participants required: Which design requires the most? Which requires the fewest?

● Within Subjects require the fewest because the same participants are being exposed to the different conditions. ● Between subjects require more participants because different participants are used for the different conditions.