Unfortunately, there’s prob no way to know if 5 or 6 is better!
Why? Here’s a #tweetorial on estimating causal effects for nutrition. Grab a 🥗 & get comfy!
You need to make 2 decisions: how often should I eat any fries; and how many fries should I eat in a serving?
•what is the best frequency of French fry consumption to prevent heart attacks?
•what is the best serving size of French fries to prevent heart attacks?
So, the first step of our #targettrial (inclusion criteria) is sorted: we’ll enroll a bunch of 40 year olds.
What about those who have never eaten fries? That depends on our causal question...
The first question is easier to answer and let’s us include the never eaters.
We want joint interventions on the frequency & amount of fries:
•Eat fries only Z times per month & only X fries at once sitting.
We can specify ranges, say X = 1 to 100 & Z = 1 to 30.
But 100*30 = 3000 trial arms. That’s a lot of people! 😬
Our participants are 40 at baseline, but the average age at 1st heart attack for men is ~66 & for women, ~70. So maybe we should follow for ~30 years?
Good thing we have those unlimited resources!
So, the intention-to-eat effect isn’t going to be very useful.
That’s more complicated, & we need people to record their actual fry eating behavior for 30 years, but in theory it can be done!
1️⃣ we absolutely require info on predictors or fry eating & heart attack over time (& same for ghosting)
2️⃣we must use g-methods if past fry-eating predicts future fry-eating (& ditto ghosting).
Who wants to fund my 3000-arm trial w/ 30 years of follow-up & daily fry consumption diaries, plus regular measurement of confounders?
Okay, don’t panic, we may still be able to answer our question: let’s do an observational study! We can use our #targettrial to design it, and we probably don’t even need to change much!
First, we need to worry about baseline randomization! But that’s hardly a big deal—we were already dealing with 30 years of counfounders, so what’s one more time point?
We wanted 3000 trial arms to cover all the possible combos of fry eating frequency and amount, and that was too many for our trial to be reasonable.
But our #obsdata will *also* only work if there are people who eat every freq/amount combo.
Plus we need something called positivity: we need everyone in our study to have had a chance of following every fry-eating strategy.
•eat fries whenever, but only ever X at once.
That’s a bit weird, but cuts our # of interventions down to 100 from 3000 👍🏼👍🏼
At least some people must always eat X=1 to 100 fries every time they eat fries for 30 years.
And everyone has a chance of always eating X=1 to 100 fries every time they eat fries for 30 years (positivity)
(PS: even if we switch to container size, we aren’t saved b/c size can vary widely!)
Compared to that, using g-methods to control for time-varying exposure-confounding feedback is a piece of cake!