Contributing data without breaching anyone's privacy posts 31–60

Limitations of datasets: all community-collected data has limitations. The population is self-selected (people in this community are not representative of all people using these compounds). Reporting bias is real (remarkable outcomes get reported; mundane outcomes do not).

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.

On post #43 — agreed on the reasoning, with one qualification.

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.

Thank you for the correction. I have edited my earlier post with a note rather than silently, so the thread still makes sense to read. The error was mine and it was the kind that comes from remembering a figure instead of looking it up.

I read post #47 twice before replying, because I had assumed the opposite.

Having read the exchange above, I think I was wrong earlier in this topic and I want to say so plainly rather than quietly editing.

The correction was fair and I had been repeating something I had not checked carefully enough.

This follows post #47 rather than contradicting it.

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

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

On post #48 — agreed on the reasoning, with one qualification.

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.

Thank you for the correction. I have edited my earlier post with a note rather than silently, so the thread still makes sense to read. The error was mine and it was the kind that comes from remembering a figure instead of looking it up.

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.

post #54 is right about the mechanism and I think understates the practical bit.

Collection methods: ask how the data were collected. Longitudinal tracking over months is stronger than retrospective recall. Prospective measurement (done while experiencing something) is stronger than memory afterward.

Worth separating two things that post #52 runs together.

Limitations of datasets: all community-collected data has limitations. The population is self-selected (people in this community are not representative of all people using these compounds). Reporting bias is real (remarkable outcomes get reported; mundane outcomes do not).

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.

Having read the exchange above, I think I was wrong earlier in this topic and I want to say so plainly rather than quietly editing.

The correction was fair and I had been repeating something I had not checked carefully enough.

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

Two things before anyone answers the substance.

First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound.