If you’re manually collecting data, how do you set yourself up to reduce the amount of time spent cleaning/tidying it afterwards?
Sometimes I find it difficult to imagine what my data would look like in it’s tidy state, e.g. I’ll have a ID variable, then anything between 10-50 variables where each variable has between 1-10 observations per ID. The manual input feels incredibly messy and error prone in itself. Add a few extra collaborators and you’ve got the recipe for disaster. Do you collect data in whatever way seems most natural for your current project, or do you keep it tidy from the beginning? How?
Google spreadsheets and Excel are “good” options - but not very safe in my opinion (I’m still living in a world where Excel files and article feedback gets emailed around with _namedate). I could use google and the googlesheets package to have some level of version control, but I’d prefer something like RedCap. RedCap, however, seems to require a lot of resources and I’m not sure if we’ll be able to use it. Are there any other options that works well with R? Like a lightweight/easier to use version of RedCap with an R API…?