CH 12: Factorial Experimental Designs

Complete Factorial Design

a factorial design in which each level of one factor is combined or crossed with each level of the other factor, with participants observed in each cell or combination of levels

Participant Variable

a quasi-independent or preexisting variable that is related to or characteristic of the personal attributes of a participant

Mixed Factor Design

a research design in which different participants are observed at each level of a between-subjects factor and also repeatedly observed across the levels of the within-subjects factor

Factorial Experimental Design

a research design in which groups are created by manipulating the levels of two or more factors, then the same or different participants are observed in each group using experimental procedures or randomization (for a between-subjects factor) and using control for timing and order effects (for a within-subjects factor)

Two-Way Factorial Desgin

a research design in which participants are observed in groups created by combining or crossing the levels of two factors

Higher-Order Factorial Design

a research design in which the levels of more than two factors are combined or crossed to create groups

Between-Subjects Factorial Design

a research design in which the levels of two or more between-subjects factors are combined to create groups, meaning that different participants are observed in each group

Within-Subjects Factorial Design

a research design in which the levels of two or more within-subjects factors are combined to create groups, meaning that the same participants are observed in each group

Interaction

a source of variation associated with how the effects of one factor are influenced by, or depend on, the levels of a second factor in a table summary, an interaction is a measure of how cell means at each level of one factor change across the levels of a second factor

Within-Subjects Factorial Design

In which kind of design do we combing the levels of two or more within-subjects factors?

Mixed Factorial Desingn

In which type design do we combine the levels of at least one between-subjects factor and one within-subjects factor?

levels; two or more independent variables

A factorial experimental design is used when we manipulate the ____________________ of __________________ to create groups.

1. Manipulate the levels of each factor 2. Cross the levels of the two factors to create the groups 3. Randomly assign different participants to each level of the between-subjects factor 4. Control for order effects due to observing the same participants at each level of the within-subjects factor (attentional demand required during the task). Then compare group differences in the dependent variable (memory cell).

For the mixed factorial design to be an experiment, the researchers must have done which four things?

1. Manipulate the levels of each factor 2. Cross the levels of the two factors to create groups 3. Control for order effects due to observing the same subjects in each group. Then compare group differences in the dependent variable (activity levels)

For the within-subjects factorial design to be an experiment, the researcher must have done which three things?

manipulated; experimental

In a factorial experimental design, the levels of both factors must be ___________________, and ____________________ procedures must be used to assign or observe participants in each group.

Between-Subjects Factorial Design

In what kind of design do we combine the levels of two or more between-subjects factors?

- the larger the number of levels combined to create the groups, the greater demands on the participants - the greater demands in each group, the greater the burden on participants

What are two concerns for a factorial design?

Factorial Design

a research design in which participants are observed across the combination of levels of two or more factors

Main Effect

a source of variation associated with mean differences across the levels of a single factor in a table summary, a main effect is a measure of how the row and column means differ across the levels of a single factor

Two-Way ANOVA

a statistical procedure used to analyze the variance in a dependent variable between groups created by combining the levels of two factors

Higher-Order Interaction

an interaction for the combination of levels of three or more factors in a factorial design

Completely Crossed Design

another name for "complete factorial design"