Matched Pairs Design

The last experimental design you need to know about is matched pairs design. Let's first provide a matched pairs design definition and then have a look at an example.

In matched pairs design, participants are paired based on a specific characteristic or variable (e.g., age) and then divided into different conditions. Researchers assign one member to the control group and the other to the experimental group in each pair. The procedures are then the same as in the independent group design. Each group experiences only one level of IV. Researchers compare the average results of the groups after the experiment.

Pairs of people, Kindpng

Matched pairs design example

Suppose we conduct a research project to investigate whether StudySmarter helps A-level psychology students better than traditional textbooks and test participants’ learning outcomes using a post-test after graduation.

• We would pair participants based on their prior exam performance in psychology, as academic ability can be a confounding variable that affects post-test scores.
• Thus, we would pair the student with the best performance with the second-best, the third-best with the fourth-best, and so on.
• Then we would divide the pairs into two groups: the experimental group (high school graduates studying with StudySmarter) and the control group (high school graduates studying with traditional textbooks), following the same procedure as the independent group design.
• We would then compare the mean score of each group on the post-test.
• Most importantly, we would compare the mean score of the post-test between the two groups, which provides us with the results to interpret the research question.

What are the strengths and weaknesses of matched pairs design?

We will now discuss the strengths and weaknesses of matched pairs design.

Strengths of matched pairs design

In the following, we will present the strengths of the matched pairs design. We will discuss order effects, demand characteristics, and participant variables. The evaluation points are shown in PEEL format: Point/Evidence/Explanation/Link.

No order effects

P: An advantage of matched pairs over repeated measures is that there are no order effects. E: Order effects mean that the tasks completed in one condition may influence how the participant performs the task in the following condition. E: Since participants are only tested on matched pairs, there is no practise or boredom effect. L: Thus, by controlling the order effects, which can be a serious confounding variable, matched pairs improve the study’s validity.

Reduced demand characteristics

P: Another advantage of matched pairs is their reduced demand characteristics. E: Because we test all participants only once, participants are less likely to guess the experiment’s target. E: This may reduce the risk that participants will change some aspect of their behaviour in response to knowledge of the research hypothesis. L: Therefore, reducing demand characteristics may increase the validity of the research.

Control of participant variables

P: Participant variables can be controlled by selecting participants according to the experiment’s relevant variables. E: Participant variables are the external variables related to the individual characteristics of each participant and can affect their response. E: Extraneous variables in participants, such as individual differences, cannot be eliminated, but they can be reduced. L: By matching participants to relevant variables, we can reduce the confounding influence of participant variables to some extent, improving internal validity.

Weaknesses of matched pairs design

In the following, we will highlight the weaknesses of the matched pairs design. We will discuss the data needed, the number of participants required, the time required to find participants, and the elimination of participants.

More participants are needed

P: The matched pairs design has a lower economic benefit because it requires more participants. E: The matched pairs design requires twice as many participants as the repeated measures design. E: This is an economic disadvantage for researchers because they must spend more time and resources recruiting participants. L: Therefore, independent groups can be considered a less cost-effective and efficient experimental design than a repeated measures design.

Requires extra data

P: A matched pairs design has a lower economic benefit because it requires additional procedures. E: A matched pairs design requires data specifying each participant’s particular characteristic or variable. E: This is an economic disadvantage for researchers because more time and resources must be spent collecting additional data or conducting an additional pretest. L: Matched pairs can thus be considered a less cost-effective and efficient experimental design than repeated measures design and independent groups.

Disadvantage if one participant drops out

P: There is a disadvantage if a participant drops out of the study. E: Since participants are matched in pairs, the pair data would be useless if one dropped out. E: The data from two participants would be lost, which could set the study back and lead to the need to recruit replacement participants. L: For this reason, the matched pairs design may be less efficient.

Time-consuming

P: Finding pairs can be a time-consuming process. E: Participants need to be matched on certain variables. For example, if you want to match participants by age and weight, it might be difficult to find pairs of participants who are the same age and weight. E: This is a disadvantage because finding matching pairs could take a lot of time. L: This also leads to matched pairs perhaps being a less efficient design.