In observational studies, researchers look for differences between exposed and unexposed groups, after people have already made their own lifestyle or treatment choices. In observational studies, researchers have no control over who’s in the exposed or unexposed groups at the start of the study. As a result, there are often fundamental differences between the two groups that can cloud the nature of the relationships under study. These differences, called confounders, can sometimes be identified and controlled with adjustments to gathered data. But sometimes important confounders exist that are never identified. This is why observational studies can’t prove cause-and-effect. They can only show associations on their own. Under certain criteria, however, a large body of evidence of observational studies can sometimes be used to draw conclusions about causation, such as the conclusion that smoking causes cancer.
For an example, see “Don’t fudge the facts on chocolate studies.”