That’s what I was trying to get at in my post, but I wasn’t being very clear.
However, if you randomize over multi-day blocks your data points go down. Once you’re randomizing whole weeks and looking at parameters with a high standard deviation, it might take impractically long to collect meaningful data.
I’m starting to think that long several week blocks are absolutely necessary for drug or lifestyle self-experimentation, because the effects once tolerance is developed are usually different from naive effects. For a drug or lifestyle change that’s intended to improve quality of life or performance, the effect of long term steady use is usually what you’re interested in.
However, if you randomize over multi-day blocks your data points go down. Once you’re randomizing whole weeks and looking at parameters with a high standard deviation, it might take impractically long to collect meaningful data.
Que? If I’m randomizing week-blocks and I’m measuring my sleep data each night, and I have 7*4 nights on and 7*4 nights off, don’t I have as many datapoints as if I randomized 56 individual nights on and off? I’m not testing solely at the beginning or end of each block. Even if it takes a full 6 days to reach steady-state, I still get signal from day 7.
The data doesn’t become representative of what you’re trying to test (long term use), until after it’s stabilized or tolerance is developed.
For example, imagine you’re testing a stimulant which keeps you from sleeping the first few days, but eventually helps you focus better and sleep normal. You can’t use the sleep deprived data from the beginning of the cycle if your goal is to identify the effects of using it long term.
I guess it’s obvious, but I was just pointing out that it takes longer to do a self experiment on something that has effects which change gradually over time vs something that can be assumed to stabilize quickly.
That’s what I was trying to get at in my post, but I wasn’t being very clear.
However, if you randomize over multi-day blocks your data points go down. Once you’re randomizing whole weeks and looking at parameters with a high standard deviation, it might take impractically long to collect meaningful data.
I’m starting to think that long several week blocks are absolutely necessary for drug or lifestyle self-experimentation, because the effects once tolerance is developed are usually different from naive effects. For a drug or lifestyle change that’s intended to improve quality of life or performance, the effect of long term steady use is usually what you’re interested in.
Que? If I’m randomizing week-blocks and I’m measuring my sleep data each night, and I have 7*4 nights on and 7*4 nights off, don’t I have as many datapoints as if I randomized 56 individual nights on and off? I’m not testing solely at the beginning or end of each block. Even if it takes a full 6 days to reach steady-state, I still get signal from day 7.
The data doesn’t become representative of what you’re trying to test (long term use), until after it’s stabilized or tolerance is developed.
For example, imagine you’re testing a stimulant which keeps you from sleeping the first few days, but eventually helps you focus better and sleep normal. You can’t use the sleep deprived data from the beginning of the cycle if your goal is to identify the effects of using it long term.
I guess it’s obvious, but I was just pointing out that it takes longer to do a self experiment on something that has effects which change gradually over time vs something that can be assumed to stabilize quickly.