A confounding variable, also known as a confounder, confounding factor, extraneous determinant, or lurking variable, is a variable that influences both the independent and dependent variables in a study, causing a spurious association. In other words, a confounding variable is an unmeasured third variable that affects the relationship between the supposed cause and effect. Confounding variables can introduce biases and distort the true relationship between variables, leading to incorrect interpretations of research results.
To be considered a confounder, a variable must meet two conditions:
- It must be correlated with the independent variable, which may or may not be a causal relationship.
- It must be causally related to the dependent variable.
Confounding variables can affect both variables that have a causal connection and those that do not. For example, if variables X and Y are associated and causally related, the association between them may be exaggerated by the influence of a third variable (Z) that affects both X and Y.
In research, it is important to identify and account for potential confounding variables to ensure the validity of the results. Failing to control for confounding variables can lead to spurious correlations and incorrect conclusions about causation.
