In this way, all confounding variables, known and unknown, should be distributed randomly and, in general, equally between the study and control groups. Randomization thereby enhances the comparability of the two groups and provides a more valid basis for inferring that the intervention caused the observed outcomes. A cohort study differs from a clinical trial in that the investigators do not determine at the outset which persons receive the intervention or exposure. Rather, persons who have already been exposed to the risk factor or intervention and controls who have not been exposed are selected by the investigators to be followed longitudinally over time in an effort to observe differences in outcome. The Framingham Heart Study, for example, is a large ongoing cohort study providing longitudinal data on cardiovascular disease in residents of a Massachusetts community in whom potential cardiovascular risk factors were first measured nearly 50 years ago.
Cohort studies are therefore observational, whereas clinical trials are experimental.
For example, increased mortality among persons with low body weight can be due to the confounding variable of underlying illness. Unlike randomized controlled trials, a shortcoming of cohort studies is that one can correct only for known confounding variables. Failure to demonstrate a significant effect in such studies may be the result of statistical properties of the study design rather than a true reflection of poor clinical effectiveness. The design is therefore retrospective, with the health outcome already known at the outset. Other types of study designs, such as ecologic or cross-national studies, uncontrolled cohort studies, and case reports, can provide useful data but do not generally provide strong evidence for or against effectiveness.