Have you heard of a confounding variable? Let’s go over it!
When you are looking at the relationship between two things there is an independent variable and a dependent variable.
Independent: the variable you are adjusting or controlling in the study. This variable presumably has an effect on the dependent variable and you want to explore this.
Dependent: the variable you are measuring or observing in the study. This variable is presumably affected by the independent variable.
But how often is a study performed in which everything is controlled? Almost never!!! There is certainly almost always something that can’t be kept constant between groups or even something that you don’t realize is present and interfering with your measurements.
This is known as a confounding variable! A confounder is something in a study that impacts the dependent variable (and sometimes even the independent variable) therefore making it difficult (or impossible) to get a good understanding of the relationship in question.
If you don’t realize a confounding variable is present you risk drawing completely incorrect conclusions!
I hope that this post helps you to understand what a confounding variable is, how you can look for them, and why it’s important you consider them when looking at data.
I make a reference to a previous post I did on the hierarchy of evidence. I think it’s important to point out that as you go up in evidence quality, the data is usually filled with fewer confounders because the studies were designed to control for them. Anecdotal remarks or case studies are difficult to draw conclusions from in particular because of how confounded they are.
Where have you seen an example of a confounder recently??