Responsive design and sampling variability

At the Joint Statistical Meetings, I went to a session on responsive and adaptive design. One of the speakers, Barry Schouten, contrasted responsive and adaptive designs. One of the contrasts was that responsive design was concerned with controlling short-term fluctuations in outcomes such as response rates.

This got me thinking. I think the idea is that responsive design will respond to the current data, which includes some sampling error. In fact, it's possible that sampling error could be the sole driver of responsive design interventions in some cases. I don't think this is usually the case, but it certainly is part of what responsive designs might do.

At first, this seemed like a bad feature. One could imagine that all responsive design interventions should include a feature that accounts for sampling error. For instance, decision rules that attain a level of statistical significance. We've implemented some like that.

On the other hand, sometimes controlling sampling error is a goal of survey data collection. For instance, we may have a budget. The overall budget doesn't include sampling error that would take us over that budget. In that case, controlling the sampling error is a requirement.

An interesting problem for responsive designs is determining whether control of the sampling error is necessary, or are we after other sources of error.

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