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!
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Sometimes you know that a group has a certain advantage, so you can correct for that to “get it out of the way”.
**Dumb example: God decides to bless Alabama by letting everyone in the state live five years longer.** (I’m using numbers from [https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_life_expectancy](https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_life_expectancy) for this.) Alabama’s life expectancy jumps to 80.5.
New Jersey’s life expectancy is also 80.5. An AL person says to a NJ person, “looks like our health care’s just as good as yours”. Can you see what the NJ person’s going to say?
(Quick pause for all the New Jersey jokes.) Probably something like “without those extra 5 years God gave you, you’d be at 75.5, so no, your health care is nowhere near as good”. Subtracting those 5 years off would be called “controlling for God’s favor”, and it means we know God favors you, but we want to look at factors other than that.
This is important for stuff like (totally making up the numbers here) if you know that a minority usually does 6% worse on some academic test, and you find a district where they only do 2% worse. If we “control for their minority-ness”, we’d say “wow, that’s 4% better than we’d expect to see, we should check out what that district is doing”.
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