Categories → Causal Wizard Concept , Causal Inference , Study Design
A Cohort is a group of subjects, participants or sample-units who have the same Treatment status (Control or Treated)
In the context of experimental design and causal inference, a cohort is a group of subjects or participants who share some common characteristics or experiences. Typically, cohorts are used in experimental studies to compare the outcomes of different treatments or interventions.
In many experimental studies, and in Causal Wizard, there are two Cohorts: the "control" cohort and the "treated" cohort. The control cohort is the group of participants who do not receive the treatment or intervention being tested. The treated group, on the other hand, is the group of participants who receive the treatment, intervention or exposure.
The purpose of having a control group is to provide a baseline against which the effects of the treatment can be compared. By comparing the outcomes of the treated group with those of the control group, researchers can determine whether the treatment has any causal effect on the outcomes being measured.
For example, suppose a researcher wants to test the effectiveness of a new drug in reducing blood pressure. The researcher might recruit two cohorts of participants: one cohort would be the control group, who receive a placebo (a sugar pill that looks identical to the real drug) and the other cohort would be the treated group, who receive the actual drug. The researcher would then measure the blood pressure of both cohorts at regular intervals and compare the outcomes between the two groups.
While in a randomized controlled trial (RCT), assignment to control and treated cohorts is delibarately randomized, these cohorts can still be identified retrospectively in observational studies.
The key difference between the control and treated cohorts is that the control cohort does not receive the treatment being tested, while the treated cohort does receive the treatment. This difference allows researchers to isolate the effect of the treatment on the outcome of interest and assess whether it causes any change.