What is a within-subjects design example?

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A within-subject design is a type of experimental design in which all participants are exposed to every treatment or condition. It is also known as a repeated measures design.

The term "treatment" is used to describe the different levels of the independent variable, the variable that's controlled by the experimenter. In other words, all of the subjects in the study are treated with the critical variable in question.

This article discusses what a within-subjects design is, how this type of experimental design works, and how it compares to a between-subjects design.

Let's imagine that you are doing an experiment on exercise and memory. For your independent variable, you decide to try two different types of exercise: yoga and jogging.

Instead of breaking participants up into two groups, you have all the participants try yoga before taking a memory test. Then, you have all the participants try jogging before taking a memory test. Next, you compare the test scores to determine which type of exercise had the greatest effect on performance on the memory tests.

This within-subjects design can be compared to what is known as a between-subjects design. In a between-subjects design, people are only assigned to a single treatment. So one group of participants would receive one treatment, while another group would receive a different treatment. The differences between the two groups would then be compared.

Consider the earlier example of the experiment looking at exercise and memory. In a between-subjects design, one group of participants would do yoga and then take a memory test. A different group of participants would jog and then take the memory test. Afterward, the results of the memory tests would be compared to see how the type of exercise influenced memory.

In a within-subjects design, all participants receive every treatment. In a between-subjects design, participants only receive one treatment.

Why exactly would researchers want to use a within-subject design? One of the most significant benefits of this type of experimental design is that it does not require a large pool of participants.

A similar experiment in a between-subject design, which is when two or more groups of participants are tested with different factors, would require twice as many participants as a within-subject design.

A within-subject design can also help reduce errors associated with individual differences. In a between-subject design where individuals are randomly assigned to the independent variable or treatment, there is still a possibility that there may be fundamental differences between the groups that could impact the experiment's results.

In a within-subject design, individuals are exposed to all levels of a treatment, so individual differences will not distort the results. Each participant serves as their own baseline.

This type of experimental design can be advantageous in some cases, but there are some potential drawbacks to consider. A major drawback of using a within-subject design is that the sheer act of having participants take part in one condition can impact the performance or behavior on all other conditions, a problem known as a carryover effect.

So for instance in our earlier example, having participants take part in yoga might have an impact on their later performance in jogging and may even affect their performance on later memory tests.

Fatigue is another potential drawback of using a within-subject design. Participants may become exhausted, bored, or less motivated after taking part in multiple treatments or tests.

Finally, performance on subsequent tests can also be affected by practice effects. Taking part in different levels of the treatment or taking the measurement tests several times might help the participants become more skilled.

This means they may be able to figure out how to game the results in order to do better on the experiment. This can skew the results and make it difficult to determine if any effect is due to the different levels of the treatment or simply a result of practice.

Frequently Asked Questions

• What is a 2x2 within subjects design?

  In a 2x2 design, researchers examine how two independent variables with two different levels impact a single dependent variable. For example, imagine a study where researchers wanted to see how the type and duration of therapy influence treatment outcomes. In a 2x2 design, they would examine two types of therapy (cognitive and psychoanalytic) as well as two levels of each treatment (short- and long-term).

• When would you use a within-subjects design?

  A within-subjects design can be a good option if participants or resources are limited. It can also be a good way to examine situations in real-world settings, such as to assess the effectiveness of educational programs.

• When should a within-subjects design not be used?

  If researchers are concerned about the potential interferences of practice effects, they may want to use a between-subjects design instead. Within-subjects designs can also take more time to administer in some cases, so it may be helpful to use a between-sessions design if many participants are available to quickly conduct data collection sessions.

By Julia Simkus, published Feb 15, 2022

A within-subjects design, or a within-groups design, is one way that researchers can assign test participants to different treatment groups. In a within-subjects design, each participant experiences every condition of the independent variable.

Researchers test the same participants repeatedly across all treatments to assess for differences between the variables. Within-subjects designs do not have a control group as all participants are tested both before and after they are exposed to treatment.

This study design is coined “within-subjects” because conditions are compared within the same group of participants. A between-subjects design, on the other hand, is the opposite of a within-subjects design where the differences in conditions occur between the groups of subjects.

Using a within-subjects design

Within-subjects studies are typically used for longitudinal studies as researchers can assess changes within the same group of subjects over an extended period of time.

For example, assume a psychiatrist is looking for new medication to treat patients with Obsessive-Compulsive Disorder (OCD). She has four potential options of medications to help the patients with their OCD.

In order to determine which medication is going to be the most beneficial for her patients, she measures each child's performance four times, once after being on each of four drug doses for a week. Each subject’s performance is thus measured at each of the four levels of the factor, or dose.

Advantages

Does not require large subject pool

Within-subjects designs require smaller sample sizes as each participant provides repeated measures for each treatment condition. This also reduces the cost and resources necessary to conduct these studies.

A between subjects study, on the other hand, would require at least twice as many participants as a within-subject design. This also means twice the cost and resources.

No variation in individual differences

Since the same individuals participate in all conditions, there will be no effects from variations in individual differences between conditions.

Because individual variation is removed, this study design has little room for error, and researchers can easily detect any differences that exist among treatments.

Limitations

Time

Data collection can take a long time since each participant is given multiple treatments. In addition, it can be challenging to control the effects of time on the outcomes of the study. Between-subjects studies tend to have shorter sessions than within-subject ones.

Carryover effects

In within-subject designs, participants are exposed to several levels of the same independent variable. This prior exposure to a treatment condition could alter the outcomes of later treatment conditions.

For example, exposure to a reaction time test could make participants’ reactions times faster in a subsequent treatment due to familiarity with the study. Randomization and counterbalancing can help reduce these carryover effects.

Examples

• Course of Cognitive Decline in Hematopoietic Stem Cell Transplantation: A Within-subjects Design (Friedman et al., 2009).
• Beliefs, attitudes, and intentions toward nuclear energy before and after Chernobyl in a longitudinal within-subjects design (Verplanken, 1989).
• A comparison of paper and online tests using a within-subjects design and propensity score matching study (Lottridge, Nicewander, & Mitzel, 2011).
• A test of exercise analgesia using signal detection theory and a within-subjects design (Fuller and Robinson, 1993).
• Reported jealousy differs as a function of menstrual cycle stage and contraceptive pill use: A within-subjects investigation (Cobey et al., 2012).
• Behavioral effects of haloperidol in young autistic children: An objective analysis using a within-subjects reversal design (Cohen et al., 1980).
• Tipping and service quality: A within-subjects analysis (Lynn and Sturman, 2010).

Frequently asked questions about within-subjects design

1. What's the difference between a Between-subjects versus within-subjects design?

Between-subjects and within-subjects designs are two different methods for researchers to assign test participants to different treatments.

In a between-subjects design, researchers will assign each subject to only one treatment condition; whereas in a within-subjects design, researchers will test the same participants repeatedly across all conditions.

Between-subjects and within-subjects designs can be used in place of each other, or in conjunction with each other.

Each of these types of experimental design has its own advantages and disadvantages, and it is usually up to the researchers to determine which method will be more beneficial for their study.

2. Can you use a between-subjects and within-subjects design in the same study?

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design).

Factorial designs are a type of experiment where multiple independent variables are tested. Each level of one independent variable (a factor) is combined with each level of every other independent variable to produce different conditions.

Each combination becomes a condition in the experiment. In a factorial experiment, the researcher has to decide for each independent variable whether to use a between-subjects design or a within-subjects design.

In a mixed factorial design, researchers will manipulate one independent variable between subjects and another within subjects.

Julia Simkus is an undergraduate student at Princeton University, majoring in Psychology. She plans to pursue a PhD in Clinical Psychology upon graduation from Princeton in 2023. Julia has co-authored two journal articles, one titled “Substance Use Disorders and Behavioral Addictions During the COVID-19 Pandemic and COVID-19-Related Restrictions," which was published in Frontiers in Psychiatry in April 2021 and the other titled “Food Addiction: Latest Insights on the Clinical Implications," to be published in Handbook of Substance Misuse and Addictions: From Biology to Public Health in early 2022.

How to reference this article:

Simkus, J. (2022, Feb 15). Within-Subjects Design: Examples, Pros & Cons. Simply Psychology. www.simplypsychology.org/within-subjects-design.html

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