Group Design

When deciding how to structure a study that involves groups of people, researchers typically choose between two experimental designs: between-groups and repeated-measures or within-subjects.

Perhaps a researcher wants to compare how much readers empathize with the protagonist in a story—the dependent variable—when they read text that contains more emotional language versus more descriptive wording—the two levels of the independent variable.

She may decide to use a between-groups design—randomly assigning different individuals to each condition: the emotional language and descriptive language groups. As a result, each participant will only take part in one condition.

With random assignment, any potential confounds, such as how much people normally empathize with characters while reading, should be more equally distributed across both groups.

Alternatively, the researcher may decide to carry out the same study using a repeated-measures design—assigning the same participants to every level of the experimental conditions. Here, after taking part in one condition, each participant will also complete the second condition.

In this repeated-measures, or within-subjects design, potential confounds and the amount of error due to natural variance are automatically controlled for because the same participants are in each group.

For this reason, there is also the risk of order effects—participants performing differently in each condition because of the order they were presented. 

To avoid this issue affecting the results, counterbalancing—an approach that ensures all possible orders of the conditions occur—is used. For instance, half the participants could be asked to read the emotional text first, while the other half reads the descriptive text first.

In the end, both designs have their pros and cons when it comes to collecting and analyzing data, so plan accordingly!