A Within-Subjects Experiment: Homophone Priming of Proper Names

Within-Subjects Factorial Designs

Mixed Designs

Advantages of Within-Subjects Designs

Disadvantages of Within-Subjects Designs

Controlling Within-Subjects Designs

How Can You Choose a Design?

What is a within-subjects design?

Introduction

In a within-subjects experiment, subjects are assigned to more than one treatment condition.

Explain the statistical concept of power.

Introduction

Power is an experiment’s ability to detect the independent variable’s effect on the dependent variable.

Why is statistical power desirable?

Introduction

Statistical power is desirable when it allows us to detect practically significant differences between the experimental conditions.

Theoretically, there is a point of diminishing returns where excessive power detects meaningless differences between treatment conditions.

Why is statistical power desirable?

Introduction

For example, in a study of treatments to lower blood pressure, a difference of 0.1 mm Hg—while statistically significant—would not affect patient health or life expectancy.

Why do we call this approach a repeated-measures design?

Introduction

In a within-subjects experiment, researchers measure subjects on the dependent variable after each treatment.

Summarize the basic principles of a within-subjects design.

A Within-Subjects Experiment

Subjects participate in more than one treatment condition and serve as their own control.

We compare their performance on the dependent variable across conditions to determine whether there is a treatment effect.

What is a within-subjects factorial design?

Within-Subjects Factorial Designs

A within-subjects factorial design assigns subjects to all levels of two or more independent variables.

What is a mixed design?

Mixed Designs

A mixed design is an experiment where there is at least one between-subjects and one within-subjects variable.

What are the advantages of within-subjects designs?

Advantages of Within-Subjects Designs

Advantages: use fewer subjects save time on training greater statistical power more complete record of subjects’ performance

What are the disadvantages of within-subjects designs?

Disadvantages of Within-Subjects Designs

Disadvantages: subjects participate longer resetting equipment may consume time treatment conditions may interfere with each other treatment order may confound results

When can’t we use a within-subjects design?

Disadvantages of Within-Subjects Designs

We can’t use a within-subjects design when one treatment condition precludes another due to interference.

What is an order effect?

Controlling Within-Subjects Designs

Order effects are positive (practice) and negative (fatigue) performance changes due to a condition’s position in a series of treatments.

The term, progressive error, encompasses both positive and negative order effects.

How does counterbalancing control for order effects in within-subjects designs?

Controlling Within-Subjects Designs

Counterbalancing is a method of controlling order effects by distributing progressive error across different treatment conditions.

How does counterbalancing control for order effects in within-subjects designs?

Controlling Within-Subjects Designs

Two major counterbalancing strategies are subject-by-subject counterbalancing, which controls progressive error for each subject, and across-subjects counterbalancing, which distributes progressive error across all subjects.

What is a fatigue effect?

Controlling Within-Subjects Designs

A fatigue effect is form of progressive error where performance declines on the DV due to tiredness, boredom, or irritation.

What are practice effects?

Controlling Within-Subjects Designs

Subject performance on the dependent variable may improve across the conditions of a within-subjects experiment and these positive changes are called practice effects.

What are practice effects?

Controlling Within-Subjects Designs

Practice effects may be due to relaxation, increased familiarity with the equipment or task, development of problem-solving strategies, or discovery of the purpose of the experiment.

Why can’t we eliminate or hold order effects constant in a within-subjects experiment?

Controlling Within-Subjects Designs

We can’t eliminate order effects because there is an order as soon as we present two or more treatments.

Holding order constant—always assigning subjects to the sequence ABC—would confound the experiment.

What is the strategy of subject-by-subject counterbalancing?

Controlling Within-Subjects Designs

Subject-by-subject counterbalancing controls progressive error for each subject by presenting all treatment conditions more than once.

Two subject-by-subject counterbalancing techniques are reverse counterbalancing and block randomization.

How does reverse counterbalancing control progressive error?

Controlling Within-Subjects Designs

In reverse counterbalancing, we administer treatments twice in a mirror-image sequence, for example, ABBA.

When progressive error is linear, it progressively changes across the experiment so that A and B have the same amount of progressive error.

What is nonlinear progressive error?

Controlling Within-Subjects Designs

Nonlinear progressive error, which can be curvilinear (inverted-U) or nonomonotonic (changes direction), cannot be graphed as a straight line.

Why can’t reverse counterbalancing control for this?

Controlling Within-Subjects Designs

Reverse counterbalancing only controls for linear progressive error.

When progressive error increases in a straight line, this method actually confounds the experiment

What is block randomization?

Controlling Within-Subjects Designs

Block randomization is a subject-by-subject counterbalancing technique where researchers assign each subject to several complete blocks of treatments.

A block consists of a random sequence of all treatments, so that each block presents the treatments in a different order.

What is a problem with subject-by-subject counterbalancing?

Controlling Within-Subjects Designs

Since subject-by-subject counterbalancing presents each treatment several times, this can result in long-duration, expensive, or boring procedures. This problem is compounded as the experimenter increases the number of treatments.

What are our alternatives?

Controlling Within-Subjects Designs

Across-subjects counterbalancing techniques present each treatment once and controls progressive error by distributing it across allsubjects.

Two techniques are complete and partial counterbalancing.

Explain complete counterbalancing.

Controlling Within-Subjects Designs

Complete counterbalancing uses all possible treatment sequences an equal number of times. Researchers randomly assign each subject to one of these sequences.

Explain partial counterbalancing.

Controlling Within-Subjects Designs

Partial counterbalancing is a form of across-subjects counterbalancing, where we present only some of the possible (N!) orders.

Two partial counterbalancing techniques are randomized partial and Latin square counterbalancing.

When is a within-subjects superior to a between-subjects design?

How Can You Choose a Design?

A within-subjects design is usually preferable when you need to control large individual differences or have a small number of subjects.

However, it may not be feasible if the experiment is long or there is a risk of asymmetrical carryover.