Published on 11 April 2022 by Pritha Bhandari.
In experiments, a different independent variable treatment or manipulation is used in each condition to assess whether there is a cause-and-effect relationship with a dependent variable.
In a within-subjects design, or a within-groups design, all participants take part in every condition. It’s the opposite of a between-subjects design, where each participant experiences only one condition.
A within-subjects design is also called a dependent groups or repeated measures design because researchers compare related measures from the same participants between different conditions.
All longitudinal studies use within-subjects designs to assess changes within the same individuals over time.
Table of contents
- Using a within-subjects design
- Within-subjects vs between-subjects design
- Pros and cons of a within-subjects design
- Frequently asked questions about within-subjects designs
Using a within-subjects design
In a within-subjects design, all participants in the sample are exposed to the same treatments. The goal is to measure changes over time or changes resulting from different treatments for outcomes such as attitudes, learning, or performance.
Other unrelated questions are also asked to make sure participants don’t guess the aim of the study. To test the effects of messaging styles on generosity, you compare the willingness to donate across conditions within subjects.
When comparing different treatments within subjects, you should randomise or counterbalance the order in which every condition is presented across the group of participants. This prevents the effects of earlier treatments from spilling over onto later ones.
Randomisation means using many different possible sequences for treatments, while counterbalancing means using a limited number of sequences across the group.
Counterbalancing is sometimes more convenient for researchers because an even portion of the sample undergoes each sequence of conditions selected by researchers. Each treatment ideally appears equally often in each position (e.g., third) of the sequence. This helps balance out the effects of treatment sequence on the outcomes.
To randomise treatment order, the order of the short stories is completely randomised between participants using a computer program. Every possible sequence can be presented to participants across the group, but in complete randomisation, you can’t control how often each sequence is used in the participant group.
In longitudinal studies, time is an independent variable. Because researchers can’t prevent the effects of time, longitudinal studies usually study correlations between time and other (dependent) variables.
To assess changes in perception, you compare differences in survey responses over time within subjects.
Within-subjects vs between-subjects design
The opposite of a within-subjects design is a between-subjects design, where each participant only experiences one condition, and different treatment groups are compared.
Between-subjects designs usually have a control group (e.g., no treatment) and an experimental group, or multiple groups that differ on a variable (e.g., gender, ethnicity, test score etc). Researchers compare the outcomes of different groups with each other.
In within-subjects designs, participants serve as their own control by providing baseline scores across different conditions.
The word ‘within’ means you’re comparing different conditions within the same group or individual, while the word ‘between’ means that you’re comparing different conditions between groups.
- a control group that takes a college course on campus,
- an experimental group that takes the same college course online.
You would administer the same test to all participants and compare test scores between the groups.
If you use a within-subjects design, everyone in your sample would take part in every condition:
- Half of the college course is administered on campus before a test.
- Half of the college course is given online before a comparable test.
You would randomise the order of the learning environment across the participants: some participants would first take the course on campus before switching to online learning, while the others would take the course online first before taking it in person. Then, you compare test scores within subjects between the two conditions.
In factorial designs, two or more independent variables are tested at the same time. Every level of one independent variable is combined with each level of every other independent variable to create different conditions.
In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.
Some longitudinal studies can be experimental when they use a mixed design to study two or more independent variables. If you can directly manipulate one of the independent variables, and participant assignment to conditions, you’re using an experimental approach.
Each participant is randomly assigned to one of two groups:
- A control group that receives standard teaching methods,
- Another group that receives experimental teaching methods.
All participants are tested before, midway and after taking the course, and their scores are statistically tested for differences across time and between groups.
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Pros and cons of a within-subjects design
Smaller sample
Within-subjects designs help you detect causal or correlational relationships between variables with relatively small samples. It’s easier to recruit a sample for a within-subjects design than a between-subjects design because you need fewer participants. Every participant provides repeated measures, making the study more cost effective.
Removes effects of individual differences between conditions
In a between-subjects design, different participants take part in each condition, so participant characteristics (e.g., intelligence or memory capacity) often vary between groups. This means it’s hard to say whether the outcomes are truly the result of the independent variable or individual differences between groups.
In contrast, there are no variations in individual differences between conditions in a within-subjects design because the same individuals participate in all conditions. Participant characteristics are controlled for.
Statistically powerful
A within-subjects design is more statistically powerful than a between-subjects design, because individual variation is removed. To achieve the same level of power, a between-subjects design often requires double the number of participants (or more) that a within-subjects design does.
Time-related effects
There are many time-related threats to internal validity that only apply to within-subjects design because it’s hard to control the effects of time on the outcomes of the study.
Some examples:
- History: an unrelated event (e.g., a lockdown) may influence the outcomes.
- Maturation: the natural physical or psychological changes (e.g., growth or aging) in the participants over time may cause the outcomes.
- Subject attrition: more participants drop out at every subsequent step of the study, leaving you with a potentially biased sample at the end because only participants with strong motivations stay in the study.
Carryover effects
Carryover effects are a broad category of internal validity threats that occur when an earlier treatment alters the outcomes of a later treatment.
Some examples:
- Practice effects (learning): familiarity with the study based on earlier conditions leads to better performance in later conditions.
- Order effects: the placement of a condition in a number of conditions changes the outcomes – for example, participants pay less attention in the last condition because of boredom and fatigue.
- Sequence effects: the interaction between conditions (based on their sequence) affects the outcomes; for instance, participants in an ad rating survey may compare later ads to earlier ones and base their decisions on the sequence of items.
Randomisation and counterbalancing of the order of conditions can help reduce carryover effects.
Frequently asked questions about within-subjects designs
- What’s the difference between within-subjects and between-subjects designs?
-
In a between-subjects design, every participant experiences only one condition, and researchers assess group differences between participants in various conditions.
In a within-subjects design, each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.
The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.
- What are the pros and cons of a within-subjects design?
-
Within-subjects designs have many potential threats to internal validity, but they are also very statistically powerful.
Advantages:
- Only requires small samples
- Statistically powerful
- Removes the effects of individual differences on the outcomes
Disadvantages:
- Internal validity threats reduce the likelihood of establishing a direct relationship between variables
- Time-related effects, such as growth, can influence the outcomes
- Carryover effects mean that the specific order of different treatments affect the outcomes
- Can I use a within- and between-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). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.
- What is a factorial design?
-
In a factorial design, multiple independent variables are tested.
If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.
(Video) Experimental Study Designs - Between & Within Subjects Design (and their Advantages & Disadvantages)
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Pritha Bhandari
Pritha has an academic background in English, psychology and cognitive neuroscience. As an interdisciplinary researcher, she enjoys writing articles explaining tricky research concepts for students and academics.
FAQs
What are examples of within subjects design? ›
Another common example of a within-subjects design is medical testing, where researchers try to establish whether a drug is effective or whether a placebo effect is in order. The researchers, in the crudest form of the test, will give all of the participants the placebo, for a time, and monitor the results.
What is an example of a within subject factorial design? ›This is called a mixed factorial design . For example, a researcher might choose to treat cell phone use as a within-subjects factor by testing the same participants both while using a cell phone and while not using a cell phone (while counterbalancing the order of these two conditions).
What is the major strength of the within subjects design Group of answer choices? ›What is the major strength of the within-subjects design? It guarantees that the participants in the various conditions are equivalent at the start of the study.
What is simple within subjects design? ›In a within-subjects design, or a within-groups design, all participants take part in every condition. It's the opposite of a between-subjects design, where each participant experiences only one condition.
How do you analyze within subject design? ›Two statistical procedures that are used to analyze within-subjects designs are the paired samples test (also called the dependent t-test) and analysis of variance (ANOVA). A paired-samples test is used if you have only one independent variable and that variable only has two levels.
How many groups are in within subject design? ›Within-Subjects Designs with Two Levels
In the simplest within-subjects design, a within-subjects factor has two levels. A common example is an experiment measuring pretreatment and post-treatment scores from each subject.
Perhaps the most important advantage of within-subject designs is that they make it less likely that a real difference that exists between your conditions will stay undetected or be covered by random noise. Individual participants bring in to the test their own history, background knowledge, and context.
What is a within subjects design quizlet? ›In a within-subjects design, a procedure to minimize threats from order effects and time-related factors by changing the order in which treatment conditions are administered from one participant to another so that the treatment conditions are matched with respect to time.
What is a 2x2 within subjects design? ›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.
What is power within-subjects design? ›Within-subjects designs have greater statistical power than between-subjects designs, meaning that you need fewer participants in your study in order to find statistically significant effects. For example, the between-subjects version of a standard t-test requires a sample size of 128 to achieve a power of .
What is the problem with within-subjects design? ›
Disadvantages: Internal validity threats reduce the likelihood of establishing a direct relationship between variables. Time-related effects, such as growth, can influence the outcomes. Carryover effects mean that the specific order of different treatments affect the outcomes.
What is the defining characteristic of a within-subjects research design? ›what is the defining characteristic of a within subject experimental design. uses a single group of participants and tests or observes each individual in all of the different treatments being compared.
What are the different types of within group design? ›There are two common forms of within-group experimental design, time-series, and repeated measures. Under time series there are interrupted times series and equivalent time series. Under repeated-measure, there is only repeated measure design.
What is a 2x3 within-subjects design? ›A 2×3 factorial design is a type of experimental design that allows researchers to understand the effects of two independent variables on a single dependent variable. In this type of design, one independent variable has two levels and the other independent variable has three levels.
Is within-subjects design random? ›Thus, random assignment plays an important role in within-subjects designs just as in between-subjects designs. Here, instead of randomly assigning to conditions, they are randomly assigned to different orders of conditions.
What is one factor within-subjects design? ›In within-subjects experimental designs, each subject in the study is exposed to each level of the independent variable. Therefore, for each subject a score on the dependent variable is collected more than once (once for each level of the independent variable).
What requirements must be met to make within-subjects approach feasible? ›What requirements must be met to make the within-subjects approach feasible? Need to control for order, fatigue, and practice effects.
Can within-subjects design be experimental? ›Within-subjects design can be used for both experimental and non-experimental research. The goal of within-subjects design is to determine if one treatment condition is more effective than others.
Why is within subjects more powerful? ›Within-subjects designs are the most powerful type of research design because each participant serves as their own control. Multiple observations of the outcome can be taken as well to understand longitudinal effects. There is always a drastic decrease in the needed sample size when using within-subjects designs.
How many participants do you need between subject designs? ›In a between-subjects design, there is usually at least one control group and one experimental group, or multiple groups that differ on a variable (e.g., gender identity, ethnicity, test score, etc.)
Which of the following is an advantage of within subject designs? ›
Answer and Explanation: The correct answer is c) more power. Within-subjects design do not differ treatment in the groups.
Can a within subject design have a control group? ›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.
Which of the following is true of the within-subjects design? ›Which of the following is true of the within-subjects design? Fewer subjects are required than in an equivalent between-subjects design.
What is a 2x1 study design? ›Experimental Designs. • 2 x 1 is simplest possible design with one independent. • 2 x 1 is simplest possible design, with one independent. variable at two levels: Variable.
What does a 2x2x2 design mean? ›Let's take it up a notch and look at a 2x2x2 design. Here, there are three IVs with 2 levels each. There are three main effects, three two-way (2x2) interactions, and one 3-way (2x2x2) interaction.
Why is a pretest posttest design considered a within subjects design? ›The pretest-posttest design is much like a within-subjects experiment in which each participant is tested first under the control condition and then under the treatment condition.
What is a within subjects manipulation? ›A within-subjects variable is an independent variable that is manipulated by testing each subject at each level of the variable. Compare with a between-subjects variable in which different groups of subjects are used for each level of the variable.
What does 80% power in a study mean? ›Power is usually set at 80%. This means that if there are true effects to be found in 100 different studies with 80% power, only 80 out of 100 statistical tests will actually detect them. If you don't ensure sufficient power, your study may not be able to detect a true effect at all.
What are the pros and cons of a between-subjects design? ›While a between-subjects design has fewer threats to internal validity, it also requires more participants for high statistical power than a within-subjects design. Advantages: Prevents carryover effects of learning and fatigue. Shorter study duration.
Are within-subjects designs more sensitive? ›Sample Size and Power: Within-subjects studies have increased sensitivity due to participants acting as their own controls, which has the practical effect of requiring substantially fewer participants to get the same level of precision as an otherwise identical between-subjects experiment.
Which do you think is better between subjects designs or within-subjects designs? ›
Compared to within-subjects studies, between-subjects studies have shorter testing sessions. Test participants who are assigned one website to test will be able to complete the usability test faster than those who need to test two (or more) websites, making the between-studies approach ideal for remote usability tests.
What are the threats to internal validity in within-subjects design? ›What are threats to internal validity? There are eight threats to internal validity: history, maturation, instrumentation, testing, selection bias, regression to the mean, social interaction and attrition.
What is a within subject experiment? ›In a “within-subject” designed experiment, each individual is exposed to more than one of the treatments being tested, whether it be playing a game with two different parameter values, being treated and untreated, answering multiple questions, or performing tasks under more than one external stimulus.
What is one reason researchers use within group designs? ›A within-group design helps to eliminate confounds found in a between-groups research design by: using the same participants for each level of the independent variable. A researcher plans to study how participants' attitudes are influenced by the type of celebrity used in commercials.
What does a 3x3 design mean? ›This is a design that consists of three factors, each at three levels. It can be expressed as a 3 x 3 x 3 = 33 design.
What does a 2x2 study mean? ›an experimental design in which there are two independent variables each having two levels. When this design is depicted as a matrix, two rows represent one of the independent variables and two columns represent the other independent variable. Also called two-by-two design; two-way factorial design.
How many conditions are needed for a 2x3 study? ›It's a 2x3 design, so it should have 6 conditions. As you can see there are now 6 cells to measure the DV.
What are examples of within subject design? ›Another common example of a within-subjects design is medical testing, where researchers try to establish whether a drug is effective or whether a placebo effect is in order. The researchers, in the crudest form of the test, will give all of the participants the placebo, for a time, and monitor the results.
What are examples of between-subjects design? ›For example, in a between-subjects design investigating the efficacy of three different drugs for treating depression, one group of depressed individuals would receive one of the drugs, a different group would receive another one of the drugs, and yet another group would receive the remaining drug.
What is inter subject design? ›Between-subjects design, also known as independent groups design, is a type of experimental design in which different groups of participants are tested under different conditions or at different time points.
What is an in between-subjects design? ›
In a between-subjects design, also called a between-groups design, every participant experiences only one condition, and you compare group differences between participants in various conditions. It's the opposite of a within-subjects design, where every participant experiences every condition.
Why use a within-subjects design? ›Perhaps the most important advantage of within-subject designs is that they make it less likely that a real difference that exists between your conditions will stay undetected or be covered by random noise. Individual participants bring in to the test their own history, background knowledge, and context.
What are two advantages of a within-subject design? ›Advantages: Only requires small samples. Statistically powerful. Removes the effects of individual differences on the outcomes.
Why are within-subject designs good? ›It's easier to recruit a sample for a within-subjects design than a between-subjects design because you need fewer participants. Every participant provides repeated measures, making the study more cost effective.
What is an example of a between subject experiments? ›In a between-subjects experiment , each participant is tested in only one condition. For example, a researcher with a sample of 100university students might assign half of them to write about a traumatic event and the other half write about a neutral event.
What is an example of between subject factors? ›In a study examining weight loss, for example, the different amounts of daily exercise under investigation would be a between-subjects factor if each was undertaken by a different set of people. Also called between-subjects variable.
When should you not use a within subjects design? ›If the researcher is interested in treatment effects under minimum practice, the within-subjects design is inappropriate because subjects are providing data for two of the three treatments (more generally, k - 1 of k treatments) under more than minimum practice.
What is a 2x2 between participants design? ›A 2X2 factorial design shows that the experiment includes two independent variables each having two levels. This design would yield four experimental conditions. As the experiment is a between-subject experimental design, each participant in the experiment undergoes only one experimental condition.
What is research methods within-subjects design? ›A within-subjects design, or a within-groups design, is a research design method of assigning participants to treatment groups. This type of design is also known as a repeated measures design. In this design method, all participants are exposed to every condition of the independent variable.
Why is within-subjects more powerful? ›Within-subjects designs are the most powerful type of research design because each participant serves as their own control. Multiple observations of the outcome can be taken as well to understand longitudinal effects. There is always a drastic decrease in the needed sample size when using within-subjects designs.