This tutorial will introduce confounding variables by:
The word “confounding” is when two variables get mixed up with one another and you can't tell the effect of one variable from the effect of the other variable. The confounding variable is the one not accounted for in a study.
Suppose that a researcher wants to know whether a high protein diet will help lab rats gain more weight than a low protein diet. The researcher has 26 lab rats and she selects 13 of the smallest rats to receive the low protein diet and 13 of the largest to receive the high protein diet.
At the end of the study, she weighs the rats to determine their weight gain and finds that the rats on the high protein diet gained more weight.
Can you think of anything that she did wrong in this study?
The answer involves the occurrence of confounding. Remember, confounding is when two variables get mixed up and you can't tell the effect of one variable from the effect of the other variable. So, what does that mean in this case?
The effects of the diets-- whether or not the high protein diet caused the rats to gain more weight-- was confounded by the fact that the heaviest rats were put on the high protein diet.
It’s not clear if the high protein diets were effective at gaining weight. Something else may have caused the weight gain since they were heavy already.
So, these are the two variables of interest in the study. The high protein diet was supposed to be the explanatory variable. The weight gain was supposed to be the response variable. The researcher was going to try to figure out a link between the two. But because of the way she assigned the rats, only a limited conclusion could be drawn. She wasn't able to draw the direct conclusion that she was hoping for. And that's confounding. Confounding should be limited in experiments when possible.
A high school math teacher, hoping to have his students do well on the final, offers an optional review session. And he says, “No one who's ever attended the review session has ever scored less than a B”.
What is the teacher trying to imply?
Why isn’t his implication correct?
What you should have come up with is that he's trying to imply that the review sessions will cause the students to do better. That may be true, however, there may be a few confounding variables. Maybe only his best and brightest students attend the optional review and these are students that may have done well on the final exam anyway.
The effects, if any, are confounded by the intrinsic motivation of students to show up to the session.
Confounding occurs when there is a variable that is chosen as an explanatory variable in an experiment, but because another variable got in the way, it cannot be determine to explain a cause.
You saw confounding variables in action and you now understand how it limits the conclusions that can be drawn, from the supposed explanatory variable. So, the variable, the confounding variable, inhibits a cause and effect conclusion. And often, it's one that we didn't think to measure, which is problematic.
Source: This work is adapted from Sophia author Jonathan Osters.
Confounding occurs when the effects, if any, of the treatments are indistinguishable from the potential effects of some other variable which was unaccounted for.
A variable which was not accounted for in a study, which limits the conclusions that the study can draw.