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Does anyone have a good reference from a statistician’s perspective on analyzing data from N-of-1 experiments? I’ve been hearing excitement about them, and id like to understand whether the hype is deserved? Feels like you need strong, time series-like assumptions?
@lihua_lei_stat Although, as they note, there may not be a known, limited inter-temporal interference pattern that can be exploited, i.e. interference even between clusters
@lihua_lei_stat Haha yeah it’s weird but the N refers to times and 1 refers to a single unit—the idea is you have “N observations of a single unit,” a statement which obscures the trickiness of those observations coming from a time series :)
@lihua_lei_stat Apparently a biostatistics term for a switchback/crossover experiment, described in e.g. https://t.co/Tmg0m43srj, https://t.co/T5SjvRSnny, and https://t.co/jqSSRBrKtp
@Apoorva__Lal@UnibusPluram Yeah i think that’s right; I didn’t know about those other terms for the same design but after looking them up, of course, Stefan Wager has a paper on it: https://t.co/Tmg0m43srj
@Apoorva__Lal@UnibusPluram Yeah i think that’s right; I didn’t know about those other terms for the same design but after looking them up, of course, Stefan Wager has a paper on it: https://t.co/Tmg0m43srj
@UnibusPluram Gotcha, although seems like you’d need more assumptions w/ N-of-1 data than a standard RCT (although w/ things like rare diseases, I guess not tiny N is a suspect assumption anyway)