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?
In a within-subjects experiment, subjects are
assigned to more than one treatment condition.
Introduction
Explain the statistical concept of power.
Power is an experiment’s ability to detect the
independent variable’s effect on the dependent
variable.
Introduction
Why is statistical power desirable?
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.
Introduction
Why is statistical power desirable?
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.
Introduction
Why do we call this approach a repeated-measures
design?
In a within-subjects experiment, researchers
measure subjects on the dependent variable
after each treatment.
Introduction
Summarize the basic principles of a within-subjects
design.
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.
A Within-Subjects Experiment
What is a within-subjects factorial design?
A within-subjects factorial design assigns
subjects to all levels of two or more independent
variables.
Within-Subjects Factorial Designs
What is a mixed design?
A mixed design is an experiment where there
is at least one between-subjects and one withinsubjects variable.
Mixed Designs
What are the advantages of within-subjects designs?
Advantages:
 use fewer subjects
 save time on training
 greater statistical power
 more complete record of subjects’ performance
Advantages of Within-Subjects Designs
What are the 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
Disadvantages of Within-Subjects Designs
When can’t we use a within-subjects design?
We can’t use a within-subjects design when one
treatment condition precludes another due to
interference.
Disadvantages of Within-Subjects Designs
What is an order effect?
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.
Controlling Within-Subjects Designs
How does counterbalancing control for order effects
in within-subjects designs?
Counterbalancing is a method of controlling
order effects by distributing progressive error
across different treatment conditions.
Controlling Within-Subjects Designs
How does counterbalancing control for order effects
in 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.
Controlling Within-Subjects Designs
What is a fatigue effect?
A fatigue effect is form of progressive error
where performance declines on the DV due to
tiredness, boredom, or irritation.
Controlling Within-Subjects Designs
What are practice effects?
Subject performance on the dependent variable
may improve across the conditions of a withinsubjects experiment and these positive changes
are called practice effects.
Controlling Within-Subjects Designs
What are practice effects?
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.
Controlling Within-Subjects Designs
Why can’t we eliminate or hold order effects
constant in a within-subjects experiment?
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.
Controlling Within-Subjects Designs
What is the strategy of subject-by-subject
counterbalancing?
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.
Controlling Within-Subjects Designs
How does reverse counterbalancing control
progressive error?
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.
Controlling Within-Subjects Designs
What is nonlinear progressive error?
Nonlinear progressive error, which can be
curvilinear (inverted-U) or nonomonotonic
(changes direction), cannot be graphed as a
straight line.
Controlling Within-Subjects Designs
Why can’t reverse counterbalancing control for this?
Reverse counterbalancing only controls for
linear progressive error.
When progressive error increases in a straight
line, this method actually confounds the
experiment
Controlling Within-Subjects Designs
What is block randomization?
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.
Controlling Within-Subjects Designs
What is a problem with subject-by-subject
counterbalancing?
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.
Controlling Within-Subjects Designs
What are our alternatives?
Across-subjects counterbalancing techniques
present each treatment once and controls
progressive error by distributing it across all
subjects.
Two techniques are complete and partial
counterbalancing.
Controlling Within-Subjects Designs
Explain complete counterbalancing.
Complete counterbalancing uses all possible
treatment sequences an equal number of times.
Researchers randomly assign each subject to
one of these sequences.
Controlling Within-Subjects Designs
Explain partial counterbalancing.
Partial counterbalancing is a form of acrosssubjects counterbalancing, where we present
only some of the possible (N!) orders.
Two partial counterbalancing techniques are
randomized partial and Latin square
counterbalancing.
Controlling Within-Subjects Designs
When is a within-subjects superior to a betweensubjects 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.
How Can You Choose a Design?