Confounding: Difference between revisions
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== Confounding == | |||
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Latest revision as of 02:06, 17 February 2025
Confounding is a concept in epidemiology that refers to a situation where the effect or association between an exposure and an outcome is distorted by the presence of another variable. The variable that causes this distortion is referred to as a confounding variable or a confounder.
Definition[edit]
Confounding occurs when the causal effect of one variable on the outcome is mixed with the effect of another variable on the outcome. The confounding variable is associated with both the exposure and the outcome, but is not on the causal pathway between the exposure and the outcome.
Types of Confounding[edit]
There are three main types of confounding:
- Positive confounding occurs when the observed association is biased away from the null.
- Negative confounding occurs when the observed association is biased towards the null.
- Partial confounding occurs when the observed association is biased, but not as much as in positive or negative confounding.
Control of Confounding[edit]
There are several methods to control for confounding, including:
- Randomization in the design of the study
- Stratification or matching in the analysis of the study
- Statistical adjustment in the analysis of the study
Examples[edit]
An example of confounding occurs in a study of the association between smoking and lung cancer. If age is also associated with lung cancer (older people are more likely to get lung cancer), and age is associated with smoking (older people are more likely to smoke), then age is a confounder in the study. If not controlled for, the effect of smoking on lung cancer may be overestimated.



