Chapter IX: Experimental Designs Within Subjects Design
9.1 Research Strategies
The defining characteristic of a between-subjects experiment is that it requires separate but
equivalent groups of participants for the different treatment conditions compared.
Alternative research procedure: the within subjects design
The defining characteristic of a within-subjects design is that it uses a single group of
participants, and tests or observes each individual in all of the different treatments being
The sample is not separated into several groups but rather exists as a single group that
participated in every treatment condition
In a within-subjects design the same group of individuals participated in every level of the
independent variable so that each participant experiences all of the different levels of the
In one sense, a within-subjects study is the ultimate in equivalent groups because the
group in one treatment condition is absolutely identical to the group in every other
condition. In the context of statistical analysis, a within-subjects design is often called a
repeated-measures design because the research study repeats measurements of the
same individuals under different conditions.
Within-subjects design may be used in investigations of changes over time.
Figure 9.1 [The Structure of a Within-Subjects Design] The same sample of individuals
participates in all of the treatment conditions. Because each participant is measured in
each treatment, this design is sometimes called a repeated-measures design. Note: all
participants go through the entire series of treatments but not necessarily in the same
A within-subjects experimental design, also known as a repeated measures experimental
design, compares two or more different treatment conditions (or compares treatment and
control) by observing or measuring the same group of individuals in all of the treatment
conditions being compared. Thus, a within-subjects design looks for differences between
treatment conditions within the same group of participants. To qualify as an experiment, the
design must satisfy all other requirements of the experimental research strategy such as
manipulation of an independent variable and control of extraneous variables.
One advantage of a within-subjects design is that it requires relatively few participants in
comparison to between subjects designs.
The primary advantage of a within-subjects design, however, is that it essentially eliminates
all of the problems based on individual differences that are the primary concern of a
There are no individual differences to confound the study.
Each participant appears in every treatment condition, each individual serves as his own
control or baseline.
In a within-subjects design, it is possible to measure the differences between treatments
without involving any individual differences.
Because the same participants are in every treatment condition, the treatment effects and
the individual differences are not linked.
In a within-subjects design, it is possible to measure the differences between individuals.
When the individual differences are consistent across treatments, they can be measured
and removed from the rest of the variance in the data.
By measuring and removing individual differences, the within-subjects design reduces
variance and reveals treatment effects that might not be apparent in a between-subjects
A within-subjects design is more likely to detect a treatment effect than a between-subjects
The primary disadvantage comes from the fact that each participant goes through a series
of treatment conditions with each treatment administered at a different time.
Errors introduced based on time-related factors, such as fatigue or the weather Another potential problem for the within-subjects design is participant attrition people who
start the research study may be gone before the study is completed
To note, because a within-subjects design requires repeated measurements under different
conditions for each individual, some participants may be lost between the first
measurement and the final measurement
Participants may forget appointments, lose interest, quit, move away, or even die.
The attrition problem may exaggerate volunteer bias 9i.e. dedicated volunteer) may
threaten external validity
9.2 Threats To Internal Validity For Within-Subjects Designs
Confounding from environmental variables. Environmental variables are characteristics
of the environment that may change from one treatment condition to another.
Examples: [morning, afternoon, night] or [room 1 and room 2]
Confounding from time-related factors. A serious concern of within-subjects designs
comes from the fact that the design requires a series of measurements made over time.
History. Scores may be affected by changing events outside the study.
Maturation. Scores may be affected by physiological or psychological changes in
Instrumentation. Scores may be affected by changes in the measuring
Testing effects. Scores may be affected by experience in prior treatment
Regression. Extreme scores may become less extreme due to statistical
Testing effects are directly related to experience obtained by participating and being
measured in previous treatment conditions
Testing effects are often called order effects. Those are in place to emphasize that the
participants go through a series of treatments in order, and that performance in any