This thread is for asking any questions that might seem obvious, tangential, silly or what-have-you. Don't be shy, everyone has holes in their knowledge, though the fewer and the smaller we can make them, the better.
Please be respectful of other people's admitting ignorance and don't mock them for it, as they're doing a noble thing.
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I don't really understand the problem. Yes, maybe you can't control them and get everyone onto the same method page. But I've already explained how you deal with that, given you the relevant keywords to search for like 'measurement error', and also given you example R code implementing several approaches.
They all take the basic approach of treating it as data/measurements which load on a latent variable for each method, and each method loads on the latent variable which is what you actually want; then you can infer whatever you need to. The first level of latent variables helps you estimate the biases of each category, some of which may be smaller than others, and then you collectively use them to estimate the final latent variable. Now you have a principled way to unify all your data from disparate methods which measure in similar but not identical way the variable you care about. If someone else comes up with a new method, it can be incorporated like the rest.
Right - sorry, melting brain. (Also, I had just thought that the assumed 10% difference between two measurers has not, in fact, been established rigorously, and that derailed the still-solid brain...)