10 Experimental Research: One-Way Designs

• What types of evidence allow us to conclude that one variable causes another variable?• How do experimental research designs allow the demonstration of causal relationships between independent and dependent variables?• How is equivalence among the level of the independent variable created in experiments?• How does the ANOVA test hypotheses about differences between the experimental conditions?• What are repeated-measures experimental designs?• How are the results of experimental research designs presented in the research report?• What are the advantages and disadvantages of experimental designs versus correlational research?

Demonstration of Causality

Association

Temporal Priority

Control of Common-causal Variable

If there is a causal relationship between IV and DV, there must bea strong correlation between them.

IV must be an antecedent of the DV.

The influence of common-causal variables that may have produced spurious relationships between IV and DV should be ruled out.

One-Way Experimental DesignExample: Violent cartoons increase children’s aggressive behaviors.

1) Define a independent variable and its levels (experimental condition)2) Create equivalence either through use of different participants (between-participant designs) or through use of thesame participants in each of experimental conditions (repeated-measure designs = within-participant designs)3) Assign participants to each level randomly.4) Select a dependent variable

Analysis of Variance (ANOVA)

A statistical procedure that is specially designed to compare themeans of the dependent variables across the levels of an experimental research design (the independent variable).

Example: Violent cartoons increase children’s aggressive behaviors.

IV: Violent Cartoons vs. Nonviolent Cartoons

DV: Children’s aggressive behaviors

Hypothesis Testing in Experimental Design

Null Hypothesis H0:

MeanViolent cartoons = MeanNonviolent Cartoons

Research Hypothesis H1:

MeanViolent cartoons > MeanNonviolent Cartoons

There is a specific difference among the conditions so that Mean(violent) is greater than M(nonviolent).

Between-Groups and Within-Groups Variance Estimates

Variance A measure of dispersion of the scores on a variable.

The ANOVA compares the variance of the means of the dependent variable between the different levels to the varianceof individuals on the dependent variable within each of theconditions

Between-Group Variance

Within-Group Variance

The variance among the condition means

The variance within the conditions

Data

Violent Nonviolent5 23 14 33 24 15 3

Total mean = 3

Mean(violent)= 4

Mean(violent)= 2

Within-Groups Variance

Between Group Variance

F value

F =Between-groups variance

Within-groups variance

As the Between-groups variance increasesin comparison to the Within-groups variance

F increases

P value will be less than alpha

ANOVA Summary Table

Source Sum of df Mean F p-value Squares Square

DV:AggressivePlay

Between 14.40 1 14.40 10.98 .002Within 49.78 38 1.31 Total 64.18

Presentation of Experiment Results

There were significant differences on rated aggression acrossthe levels of the cartoon condition, F (1, 38) = 10.98, p < .01.Children who viewed the violent cartoons (M = 2.89) were ratedas playing more aggressively than children who had viewed thenonviolent cartoons (M = 1.52)

F valuep value

Degree of freedom (# of Between-Groups - 1)

Degree of freedom (# of Within-Groups - 1)

The mean value of the violent conditionThe mean value of the nonviolent condition

Between-Participants Designs and Repeated-Measure Designs

B-P Design R-M Design

Violent Cartoons

NonviolentCartoons

Aggressive Play

Aggressive Play

PsPs

Violent Cartoons

Violent Cartoons

NonviolentCartoons

NonviolentCartoons

Aggressive Play Aggressive Play

Aggressive Play Aggressive Play

Advantages and Disadvantages of Repeated-Measure Designs

1) Increase Statistical Power2) Economize Participants

X 1) The first measure will influence the second measure. (carryover)2) Participants might become fatigued in the second measure.3) Participants performance might improve on the task over time through practice.

Counterbalancing

Arranging the order in which the conditions of a repeated-measuresdesign are experienced.

Latin Square Designs

A method of counterbalancing the order of conditions so that each condition appears in each order but also follows equally often after each of the order conditions.

P1 P2 P3

S1

S2

S3

A B C

B C A

C A B

Advantages and Disadvantages of Experiments

The experiment design can not manipulate a person’s sex, race, intelligence, family variables, and religious background.X

X

X The experiment design will not observe participant’s reactionexactly as they would behave if observed outside of the lab

The experiment design necessarily oversimplify things.

The experiment design allow us to draw conclusions aboutcausal relationships between the independent and dependentvariables.