The method that researchers use to identify or correct for attrition are:
- A.) follow up with the participants who left the study at a later date and replace their missing data with the new data
- B.) find other participants with similar scores and replace the missing ones
- D.) determine whether those who dropped out of the study had a different pattern of scores than those who stayed in the study.
What does Attrition mean in research session?
Attrition, also known as "dropout" or "loss to follow-up," refers to the loss of participants from a study over time. Researchers use several methods to identify or correct for attrition, including:
- Tracking: Researchers can track participants throughout the study and document any missing data or dropouts. This allows them to identify and understand the reasons for attrition and to estimate the potential impact of dropouts on the study results.
- Follow-up: Researchers can conduct follow-up assessments to try to contact and re-enroll participants who have dropped out of the study. This can help to reduce the potential bias caused by attrition.
- Data imputation: Researchers can use statistical techniques, such as multiple imputation, to estimate missing data and fill in the gaps caused by attrition. This can help to minimize the impact of dropouts on the study results, but it is important to note that this is not always an optimal solution as it does not account for bias that may happen as a result of missing data.