Signal and Noise in Feedback

Still on this theme of feedback. It would be nice if we got very clear signals from sampled units about why they don't want to do our surveys. However, this isn't usually the case. It seems that our best models still are pretty weakly predictive of when someone will respond.

Part of this could be that we don't have the 'right' data. We could improve our paradata and build better models.

Another part might never be captured. This is the situational part. Sampled persons might not be able to say why the refuse a survey on one day and agree to do another on another day. The decision is highly sensitive to small differences in the environment that we may never be able to capture in our data.

If that is the case, then the signal we can pick up for tailoring purposes is going to be weak. The good news is that it seems like we still haven't hit the limit of our ability to tailor. Onward!

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