Talk:Curation Policy

From BugSigDB

Edit flowchart here: https://docs.google.com/document/d/19pLGtBgFKxtY7k4-LwYb2Y1NyJqPyMQA/edit#heading=h.gjdgxs

Thanks User:ChiomaBlessing! Note about Laboratory studies - I wouldn't call "They're not randomized here because they’re all living in a controlled setting and in the same condition(s)." a defining feature (there might still be randomization). A defining feature is that the researcher controls the contrast of interest, rather than just observing it, under controlled laboratory conditions. Note, randomization in laboratory experiments is still probably good practice to avoid accidental bias: Festing MFW. The "completely randomised" and the "randomised block" are the only experimental designs suitable for widespread use in pre-clinical research. Sci Rep. 2020 Oct 16;10(1):17577. doi: 10.1038/s41598-020-74538-3. PMID: 33067494; PMCID: PMC7567855.

Got it! Thanks Levi @ User:Lwaldron. Also, please check cross-sectional description,as an additional description, I added the New York population-based study which you mentioned during the office-hour discussion on study-designs some months ago.

Minor edits, and I think it's ready! --User:Lwaldron

Under time series, the description "the analysis over time or before and after event attribute distinguishes this from the Prospective Cohort design". However, the description for prospective cohort design indicates that participants are followed up over time. Hmmm, could there be maybe a more specific description for prospective cohort so that it is not confused with time series? --User:ChiomaBlessing

Good point. It is possible to do either a cross-sectional or a time series analysis from a prospective cohort. But in a cross-sectional (case-control or not), you would be comparing some people to others, whereas in the longitudinal / time-series you are first comparing participants to themselves at other points in time - even if you also compare those time trends between participants. Can you try to clarify? --User:Lwaldron