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Showing posts from September, 2011

Adaptive and Responsive Design

I've raised this topic a couple of times here. Several years ago, Groves and Heeringa (2006) proposed an approach to survey data collection that they called "Responsive Design." The design was rolled out in phases with information from prior phases being used to tailor the design in later phases.

In my dissertation, I wrote about "Adaptive Survey Design." For me, the main point of using the term "adaptive" was to link to the research on adaptive treatment regimes, especially as proposed by Susan Murphy and her colleagues.

I hadn't thought much about the relationship between the two. At the time, I saw what I was doing as a subset of responsive designs.

Since then, Barry Schouten and Melania Calinescu at Statistics Netherlands have defined "adaptive static" and "adaptive dynamic" designs. Adaptive static designs tailor the protocol to information on the sampling frame. For example, determining the mode of contact for each case …

Mode Switching Algorithms

After running an experiment using sequences of modes (for contacting sampled households), I've been thinking about how to decide when to switch modes. In our experiment, we had a specified time when the switch would occur (after 5 weeks of the first mode, switch to the second mode).

It seems like better "switching" rules should be possible. Ideally, we would want to identify some best mode as quickly as possible. The amount of time it might take to determine this would vary across sampled cases.

The hard part is that we generally have very little feedback. We don't get a lot of information back from failed attempts. For example, a letter doesn't generally generate much feedback other than an interview occurred, it didn't occur, or the letter was returned. It might be that interviewer-administered modes are more promising for this kind of tailoring, since they do generally obtain more feedback.