Randomized experiments are typically preferred over observational studies or experimental studies that lack randomization because they allow for more control. A common problem in studies without randomization is that there may be other variables influencing the results. These are known as confounding variables. A confounding variable is related to both the explanatory variable and the response variable.
- Confounding Variable
Characteristic that varies between cases and is related to both the explanatory and response variables; also known as a lurking variable or a third variable
Example: Ice Cream & Home Invasions Section
There is a positive relationship between ice cream sales and home invasions (i.e., as ice cream sales increase throughout the year so do home invasions). It is clear that increases in ice cream sales do not cause home invasions to increase, and home invasions do not cause an increase in ice cream sales. There is a third variable at play here: outdoor temperature. When the weather is warmer both ice cream sales and home invasions increase. In this case, outdoor temperature is a confounding variable because it is related to both ice cream sales and home invasions.
Example: Weight & Preferred Beverage Section
Research question: Do adults who prefer to drink beer, wine, and water differ in terms of their mean weights?
Data were collected from a sample of World Campus students to address the research question above. The researchers found that adults who preferred beer tended to weigh more than those who preferred wine.
A confounding variable in this study was gender identity. Those who identified as men were more likely to prefer beer and those who identified as women were more likely to prefer wine. In the sample, men weighed more than women on average.