Confounding variables

Confounding Variables

Confounding variables (pronunciation: /kənˈfaʊndɪŋ ˈvɛrɪəbəlz/) are factors that can cause or prevent the outcome of interest, are not intermediate variables, and are not associated with the factor(s) under investigation. They can also distort the apparent relationship between different variables.

Etymology

The term "confounding" is derived from the Old French word "confondre", which means "to mix up". In the context of research, it refers to the mixing up or confusion of effects that are due to the variable of interest and those that are due to other variables.

Definition

A confounding variable is an extraneous variable in a statistical model that correlates (positively or negatively) with both the dependent variable and the independent variable. A confounding variable, also known as a confounder or confounding factor, can lead to inaccurate results in research if not controlled for.

Related Terms

• Dependent Variable: The outcome that the researcher is interested in explaining or predicting.
• Independent Variable: The variable that is manipulated or controlled in a study to examine its impact on the dependent variable.
• Extraneous Variable: Any variable that is not intentionally studied in your experiment or test and can affect the results of your study.
• Control Variable: A variable that is kept constant to prevent its effects on the outcome and therefore, allow for clearer analysis of the relationship between the independent and dependent variables.

Examples

In a study examining the relationship between smoking and lung cancer, age could be a confounding variable. Older people are more likely to have been exposed to other risk factors for lung cancer, such as radon, asbestos, and air pollution. If not controlled for, age could confound the relationship between smoking and lung cancer.

Controlling for Confounding Variables

Researchers use several methods to control for confounding variables. These include randomization, matching, stratification, and statistical adjustment.

See Also

• Bias (statistics)
• Causal Inference
• Epidemiology
• Research Design
• Statistical Control

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