Criteria for Confounding: An Example

Studies often focus on the association between two variables; for instance, between a risk factor and a disease. However, reality is usually complex and there are many other variables that may influence this association. Sometimes, the presence of a third variable can either exaggerate the association between the two variables we study or mask an underlying true association. This is called confounding and is any researcher’s nightmare. In this module, you will learn multiple methods to detect confounding in a study, so that you can prepare to deal with it. By the end of the module, you will be able to apply these methods to actual data and conclude whether there is confounding.

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