What does attrition bias refer to in experimental studies?

Attrition bias refers specifically to the impact that participant drop-out can have on the validity of an experimental study. When participants leave a long-term experiment, the remaining group may not be representative of the original population, which can skew the results and affect the study's conclusions. This issue can introduce systematic differences between those who complete the study and those who do not, potentially leading to an over- or underestimation of the effects being measured.

In long-term studies, if the remaining participants differ significantly in characteristics or outcomes from those who dropped out, the findings may not accurately reflect what would happen if all participants had remained. Therefore, it's crucial to account for and analyze attrition to mitigate its influence on study findings. Understanding this concept helps researchers design better studies and interpret results with appropriate caution, aiming for more reliable conclusions.