←back to thread

817 points dynm | 2 comments | | HN request time: 0.42s | source
Show context
mg ◴[] No.43307263[source]
This is great. The author defines their own metrics, is doing their own A/B tests and publishes their interpretation plus the raw data. Imagine a world where all health blogging was like that.

Personally, I have not published any results yet, but I have been doing this type of experiments for 4 years now. And collected 48874 data points so far. I built a simple system to do it in Vim:

https://www.gibney.org/a_syntax_for_self-tracking

I also built a bunch of tooling to analyze the data.

I think that mankind could greatly benefit from more people doing randomized studies on their own. Especially if we find a way to collectively interpret the data.

So I really applaud the author for conducting this and especially for providing the raw data.

Reading through the article and the comments here on HN, I wish there was more focus on the interpretation of the experiment. Pretty much all comments here seem to be anecdotal.

Let's look at the author's interpretation. Personally, I find that part a bit short.

They calculated 4 p-values and write:

    Technically, I did find two significant results.
I wonder what "Technically" means here. Are there "significant results" that are "better" than just "technically significant results"?

Then they continue:

    Of course, I don’t think this
    means I’ve proven theanine is harmful.
So what does it mean? What was the goal of collecting the data? What would the interpretation have been if the data would show a significant positive effect of Theanine?

It's great that they offer the raw data. I look forward to taking a look at it later today.

replies(14): >>43307304 #>>43307775 #>>43307806 #>>43307937 #>>43308201 #>>43308318 #>>43308320 #>>43308521 #>>43308854 #>>43309271 #>>43310099 #>>43320433 #>>43333903 #>>43380374 #
matthewdgreen ◴[] No.43308318[source]
This is an N=1 trial. Dressing your N=1 trial up with lots of pseudo controls and pseudo blinding and data collection does not make it better. In fact: putting this much effort into any medication trial makes it much more likely that you’re going to be incentivized to find effects that don’t exist. I think it’s nice that the author admits that they found nothing, but statistically, worthless drugs show effects in much better-designed trials than this one: it’s basically a coin toss.
replies(12): >>43308423 #>>43308440 #>>43309081 #>>43309263 #>>43309513 #>>43309704 #>>43309722 #>>43309838 #>>43311651 #>>43313233 #>>43315219 #>>43322581 #
1. azeirah ◴[] No.43311651[source]
Any experiment you perform on yourself has N=1. Self-science isn't as robust as gold standard double blind blablabla PhD trials, but come on.

How else are you going to find out whether a particular diet or medication works for you specifically? It's ALWAYS N=1.

replies(1): >>43311770 #
2. hartator ◴[] No.43311770[source]
And a honest n=1 is better than a double blind n=1000 but outcome-interested study. It’s so easy to make data tell the story you want.