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Repeated Measures Design

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Repeated Measures Design

What's the repeated measures design in psychology? Let's look at the definition first.

In a repeated measures design, all participants experience all levels of the independent variables (IVs). In other words, participants are one group and participate in all study conditions. Typically, researchers compare the average results of the conditions after the experiment.

All clear? If not, a repeated measures design example will help you get a better understanding of how it operates. Subsequently, we will also examine the pros and cons of repeated measures design.

Repeated Measures Design Design procedure StudySmarterRepeated measures design diagram, Erika Hae - StudySmarter Originals

Repeated measures design example in psychology

Suppose the study investigates whether StudySmarter helps A-level psychology students better than traditional textbooks, assessing learning with tests. If the researchers conduct a repeated measures experiment, all participants will use StudySmarter and standard textbooks. This process differs from an independent group design, where researchers divide participants into two groups, one using StudySmarter and the other using traditional textbooks.

What are the pros and cons of repeated measures design?

As always, one of the important aspects to consider are the pros and cons of repeated measures design.

Repeated measures design advantages

Assessment items are presented in the format PEEL: Point/Evidence/Explanation/Link. Below we will present the advantages of the repeated measures design. We will focus on the participant variables and the economic benefits.

Control of participants variables

P: Participant variables are controlled because the same participants participate in both conditions. E: Participant variables are extraneous variables related to the individual characteristics of each participant and may influence their response. E: In a repeated measures design, the same participants participate in each condition, so extraneous participant variables such as individual differences can be eliminated. L: By reducing the influence of participant variables, the repeated measures design has good internal validity.

Fewer participants are needed

P: Repeated measures design has a tremendous economic advantage because it requires fewer participants. E: Repeated measures designs require only half the participants in independent groups and matched pairs designs. E: This is a tremendous economic advantage for researchers because they spend less time and resources recruiting participants. L: Repeated measures can thus be considered a more cost-effective and efficient experimental design than independent groups and matched pairs.

Repeated measures design disadvantages

In the following, we will present the disadvantages of the experimental design with repeated measurements. These are order effects and demand characteristics.

Order effect

P: One of the major limitations of repeated measures is order effects. E: Order effects mean that tasks completed in one condition may affect task performance in another. E: For example, participants may perform better in the second condition either because of the practise effect or worse because of boredom or fatigue. L: Thus, if all participants complete the tasks in the same order, order effects are a serious problem that affects the study's validity.

Demand characteristics

P: Another limitation in repeated measures is demand characteristics. E: The first test could induce demand characteristics because it allows participants to guess the survey's target when it is repeated in the second test. E: There is a risk that participants will change some aspect of their behaviour in response to knowing the research hypothesis. L: In this way, demand characteristics may reduce research validity.

How can we deal with the limitations of repeated measures design?

Below we present ways to deal with the limitations of repeated measures design. These involve counterbalancing techniques to deal with order effects and cover stories to deal with demand characteristics.

Dealing with order effects (counterbalancing)

P: Counterbalancing is an experimental technique used to overcome order effects. E: Counterbalancing ensures each condition is tested equally first or second. E: For example, participants are divided in half, with one half completing the two conditions in one order and the other half completing the conditions in reverse order. L: In this way, a researcher can control the order of the conditions and ensure better validity.

Dealing with demand characteristics (cover story)

P: A cover story about the test's purpose can prevent participants from guessing the research hypothesis. E: The cover story should be plausible but false. Researchers communicate this statement to participants to prevent the true hypothesis from being revealed. E: Such deception can be practised when the knowledge of the experiment's true purpose can influence the participant's behaviour in the study. L: In this way, deception can allow the researcher to control demand characteristics and ensure better validity.

Repeated Measures Design - Key takeaways

  • In the repeated measures design, all participants experience all levels of IVs.
  • Participant variables are controlled because the same participants participate in both conditions.
  • The repeated measures design has significant economic advantages because it requires fewer participants.
  • Order effects mean the tasks completed in one condition may impact the performance task in another condition.
  • Demand characteristics can occur. Researchers can use cover stories to deal with demand characteristics.

Frequently Asked Questions about Repeated Measures Design

In a repeated measures design, the participants are one group and participate in all study conditions (independent variables).

Repeated measure designs are cheaper as you need fewer participants, participant variables can be controlled, and participant results can be measured over time, which is helpful for longitudinal studies.

Suppose you came up with a new crisp flavour and want to know if people would like it more than already existing flavours. So you get three different flavours of crisps, including your new flavour, have the same participants try all three flavours and then rate which one they liked the best.

The advantages are control of participant variables and fewer participants needed. The disadvantages are order effects and demand characteristics.

A repeated measure design could be planned as an observational study, but they are typically controlled experiments.

Final Repeated Measures Design Quiz

Question

What is a repeated measures design?

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Answer

In the repeated measures, all participants experience all levels of IVs.

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Question

Why are repeated measures criticised for having order effects?

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Answer

One of the major limitations of repeated measures is order effects. Order effects mean that tasks completed in one condition may have an effect on task performance in another condition.

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Question

Why are repeated measures praised as cost-effective?

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Answer

Repeated measures design has great economic benefits as this design only requires half the number of participants with independent groups and matched pairs design. This is a tremendous economic benefit to the researchers as they will spend less time and resources to recruit participants.

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Question

Why are repeated measures praised for having high validity?

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Answer

Participant variables are controlled because the same participants take part in both conditions. Participant variables are extraneous variables related to the individual characteristics of each participant and may influence their response. The same participants participate in each condition in a repeated measures design, so extraneous participant variables such as individual differences can be eliminated.

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Question

Why are repeated measures criticised for having demand characteristics?

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Answer

The first test could induce demand characteristics because it allows participants to guess the target of the survey when it is repeated in the second test. There is a risk that participants will change some aspect of their behaviour in response to knowing the research hypothesis.

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Question

How can research deal with the order effects?

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Answer

Counterbalancing is an experimental technique used to overcome order effects. Counterbalancing ensures each condition is tested equally first or second.

Show question

Question

How can research deal with the demand characteristics?

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Answer

A cover story about the purpose of the test can prevent participants from guessing the research hypothesis. The cover story should be plausible but false. Researchers communicate this statement to participants to prevent the true hypothesis from being revealed. Such deception can be practised when the knowledge of the experiment's true purpose can influence the participant's behaviour in the study. In this way, deception can allow the researcher to control demand characteristics and ensure better validity.

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