A lurking variable, also known as a confounding variable, is a variable that is not included in a statistical analysis but can still affect the outcome of that analysis. Lurking variables can create problems by falsely identifying a strong relationship between variables or hiding the true relationship. They are extraneous variables that are intrinsic to a study and can have an important, significant effect on the variables of interest. Lurking variables earned their name because they often go undetected and hide beneath the surface of the variables researchers are interested in studying.
For example, a research scientist studies the effect of diet and exercise on a persons blood pressure. Lurking variables that also affect blood pressure are whether a person smokes and stress levels. If these variables are not accounted for in the analysis, they can lead to biased or misleading results.
To discover lurking variables, researchers must take the time to understand their data and the important variables that can affect a process. They can also create a plot of the data to look for non-linear trends that can identify the presence of lurking variables. For research results to be valid, lurking variables must be identified and then either eliminated, held constant, or included in the study.
