"Maximizing Validity: Cluster-Random-Assignment in A/B Testing"

Cluster-Random-Assignment

Cluster-random-assignment is a method of assigning participants to different groups in a study or experiment. In this method, participants are grouped together based on certain characteristics, and then the groups are randomly assigned to different treatment conditions. This method is often used in large-scale studies where it is not feasible to assign individual participants to different groups.

Impact on A/B Testing on Web and in Mobile

Cluster-random-assignment can have a significant impact on A/B testing on web and in mobile. By grouping participants together based on certain characteristics, such as location or device type, researchers can ensure that the treatment conditions are evenly distributed across the different groups. This can help to reduce the impact of confounding variables and increase the validity of the results.

For example, if a researcher is conducting an A/B test on a mobile app, they may want to group participants based on the type of device they are using. This can help to ensure that the treatment conditions are evenly distributed across different types of devices, which can impact the user experience. By using cluster-random-assignment, the researcher can be confident that any differences in the results are due to the treatment conditions and not to differences in the devices being used.