Weighting expanding on my earlier response. Now examine the curve. Now examine the effect of weighting on the error and r values. Possibly to an unusable point. Then you know what fraction of the overall intraindividual variability is due to the assay, for example.
Many people simply assume that assay error is a small fraction of the overall error.
Below is an earlier version of this discussion as well. Then find the remaining noise in the intraindividual variability. It really boosts comfidence in a study if you find a low gamma, for instance, showing that the remaining error beyond the assay is relatively small. The converse is also useful to know. The problem is that the coefficient of variation is hardly ever constant, and the SD needs to be known over its entire working range.