About the Datasets category

Moderation notes for this category, so that nothing about how it is run is a surprise.

Topics get moved into and out of here regularly. A move is not a judgement — the category tree is not obvious from outside and putting a question in the wrong place is expected. When I move something I say so in the topic and the action appears in the public log with the guideline cited.

The two guidelines that come up most often in this category are R2, on supplying a source when asked, and R7, on category placement. Neither is used punitively.

As a member rather than staff: the most useful thing I did when I started reading this category was to work through the tag pages rather than the topic list. The topic list shows you what is recent. The tags show you what is settled.

Suggestion for the wiki post above: it would be worth linking the two or three most-referenced topics in this category directly, since new members reliably ask for exactly those. Happy to make the edit myself if nobody objects, with a revision note.

Bias toward positive outcomes: datasets collected by members are biased toward people who found the compounds useful. People who did not respond do not return. People who had bad outcomes might have left the community.

I read post #4 twice before replying, because I had assumed the opposite.

Combining data from different sources: datasets from this site are not directly comparable to published trials because the populations are different. They are worth reading separately, not merged together.

Temporal bias: older data in a dataset might reflect conditions (supplier, formulation, context) that have changed. Newer data is more current.

How to contribute: if you have longitudinal data you want to add, the format is simple: date, measurement, context. Contact the maintainer of the specific dataset.

Privacy: if contributing data, only share data you are comfortable making permanent and public. Once posted, data is persistent.

Practical note that does not fit anywhere else. Whatever you conclude from this topic, write down what you did and when. The single most useful thing in your own records is not any individual result; it is that they are dated and consecutive.

post #10 answers the question as asked. The question underneath it is different.

Using data in discussions: datasets are useful as reference points when someone claims something unusual. "I have not seen that reported in the data" is different from "that is impossible", but data gives you something to say.

Community-collected datasets: some members have compiled datasets from their own experience and shared them. They are self-reported, unblinded, and therefore limited as evidence. But they show real patterns that people experience.