experimental condition that is systematically varied across participants

characteristic that varies across participants but is not manipulated by the experimenters

main effect:The overall effect of a single factor

on the dependent variable, ignoring the effects of or averaging over the levels of all other factors.

Interaction: A situation,that arises when the effect of one factor (independent variable)

on the dependent variable is contingent on the levels of at least one other factor.

An interaction refers to the joint effect

of multiple independent variables considered in combination, or in tandem

the effect of the factors that interact is more than a simple

cumulative effect of those factors (the interaction)

For example, a particular style of therapy might

work better for one type of client than for another.

Examining only main effects might miss

the important way in which factors operate jointly

diagram that represents different combinations of the presence or absence of main and interaction effects.

Between-subjects Factorial Design Example

type of memory task and age/expertise, such that the memory task that evoked expertise (the chessboard) was enhanced more by the presence of expert knowledge

Within-subjects Factorial Design

involves conditions where the groups for each level of a factor are not independent of each other, but rather each group is exposed to each level of the factor

The term “repeated measures" reflects the idea that groups are

repeatedly exposed to the different levels of the factor(s)

Mixed factorial design (or mixed design)

A design that includes both within and between-subjects factors

Example of a Mixed Factorial Design (a 2 x 2)

After the pretest, randomly assign to one of two groups: the exposure or supportive psychotherapy. Finaly posttest.

Higher-order Factorial Designs

includes more than two independent variables.

Higher-order Factorial Designs: For example, a 2 x 2 x 2 design,

with three factors, two levels for each factor, and eight cells or conditions.

2 (strategy) x 2(gender) x 3(age) design

one IV ( rote rehearsal or imagery) two participant variables, gender (male or female) and age (high school, college, middle age)

A higher-level factorial design is

best suited to capture the complexity of the world that we live in

Higher-order factorial designs may be used to

increase the external validity of your study.

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Experimental Independent Variables versus Participant Variables

Term	Definition
independent variable	experimental condition that is systematically varied across participants
participant variable	characteristic that varies across participants but is not manipulated by the experimenters
main effect:The overall effect of a single factor	on the dependent variable, ignoring the effects of or averaging over the levels of all other factors.
Interaction: A situation,that arises when the effect of one factor (independent variable)	on the dependent variable is contingent on the levels of at least one other factor.
Interaction is the reason	for factorial methodology
An interaction refers to the joint effect	of multiple independent variables considered in combination, or in tandem
the effect of the factors that interact is more than a simple	cumulative effect of those factors (the interaction)
For example, a particular style of therapy might	work better for one type of client than for another.
Examining only main effects might miss	the important way in which factors operate jointly
Interaction chart	diagram that represents different combinations of the presence or absence of main and interaction effects.
Between-subjects Factorial Design Example	type of memory task and age/expertise, such that the memory task that evoked expertise (the chessboard) was enhanced more by the presence of expert knowledge
Within-subjects Factorial Design	involves conditions where the groups for each level of a factor are not independent of each other, but rather each group is exposed to each level of the factor
The term “repeated measures" reflects the idea that groups are	repeatedly exposed to the different levels of the factor(s)
Mixed factorial design (or mixed design)	A design that includes both within and between-subjects factors
Example of a Mixed Factorial Design (a 2 x 2)	After the pretest, randomly assign to one of two groups: the exposure or supportive psychotherapy. Finaly posttest.
Higher-order Factorial Designs	includes more than two independent variables.
Higher-order Factorial Designs: For example, a 2 x 2 x 2 design,	with three factors, two levels for each factor, and eight cells or conditions.
2 (strategy) x 2(gender) x 3(age) design	one IV ( rote rehearsal or imagery) two participant variables, gender (male or female) and age (high school, college, middle age)
A higher-level factorial design is	best suited to capture the complexity of the world that we live in
Higher-order factorial designs may be used to	increase the external validity of your study.

Created by: james22222222

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