When study statistics results are reported, what does it mean when authors say “results upon controlling for XYZ factors”?

Question

I don’t fully understand what controlling for a factor in a experiment means, especially when it comes to real world studies with large number of people in the trials. For e.g. ” Yogurt consumers had a higher DGAI score (ie, better diet quality) than nonconsumers. *Adjusted for demographic and lifestyle factors and DGAI*, yogurt consumers, compared with nonconsumers”
Looking for an intuitive way to understand what controlling for factors means.
Thank you in advance!

In: 3

Answer 1

Here is a very simple example. Suppose you conduct a survey and you find that taller people are more likely to have a certain opinion. But someone points out that, on average, men are taller than women, so maybe what’s really going on is that men are more likely to have that opinion, and height really has nothing to do with it. There are numerous different ways we might be able to check this. We can simply look through our results and see whether it is the case that men are more likely to have that opinion. If the answer is no, then that would seem to settle it. We could also look through our results to see whether taller men are more likely to hold the opinion than shorter men, and the same with women.

This can get much more complicated, because sometimes there are many plausible confounding factors, and sometimes only limited data are available on them.

> Adjusted for demographic and lifestyle factors

Vague language like this can sometimes be a bit of a smokescreen. Did they really control for *all* demographic and lifestyle factors, or even all the ones that are reasonably likely to be relevant? In most cases, this isn’t even feasible.

There can also be questions about whether it really makes sense to control for a certain factor, or whether it’s part of the effect you’re looking for. For example, suppose someone does a study demonstrating that people from rich families are more likely to be hired to a certain position. Someone might object that educational levels were not controlled for. But the study author might argue that educational levels are essentially a proxy for wealth, so it wouldn’t make sense to control for them.