How can you generalize an n-of-1 trial’s results to another person?
I repeatedly get this question from colleagues. And it’s important — foundational, in fact!
The real question they’re asking is:
Why would we use anything other than a randomized controlled trial (RCT)* to find real effects that generalize beyond our study sample?
It’s akin to asking how one would generalize the results (i.e., average treatment effects or ATEs) from an RCT to non-participants. The non-participants would have to resemble the participants in the RCT by meeting the same eligibility criteria as the RCT’s target population. If they do, the effects might transport (i.e., generalize) to these non-participants.
The person is the population.
Similarly, the next would-be n-of-1 trial** participant would have to “be a target population” resembling the original n-of-1 trial participant. That is, their own full set of multivariate time series*** needs to be similar enough to the original participant’s such that they “meet the same eligibility criteria” — characteristics known (or reasonably assumed) to meaningfully modify the treatment effects (i.e., effect modifiers).
In this way, the n-of-1 trial participant is a “population-of-one” (Daza, 2018). That is, the participant’s own…
