### Adaptive Design and Panel Surveys

I read this very interesting blog post by Peter Lugtig yesterday. The slides from the talk he describes are also linked to the post. He builds on an analysis of classes of nonresponders. Several distinct patterns of nonresponse are identified. The characteristics of persons in each class are then described. For example, some drop out early, some "lurk" around the survey, some stay more or less permanently.

He suggests that it might be smart to identify design features that are effective for each of the groups and then tailor these features to the subgroups in an adaptive design. This makes a lot of sense. And panel studies are an attractive place to start doing this kind of work. In the panel setting, there is a lot more data available on cases. This can help in identifying subgroups. And, with repeated trials of the protocol, it may be possible to improve outcomes (response) over time.

I think the hard part is creating the groups. This reminds me of a problem that I read about years ago in determining a policy for catalog mailings. The groupings need to be homogenous with respect to the impact of the feature we intend to use. For example, if we decide to mail an off-wave newsletter, we want that feature to improve the probability of response for everyone in the group and not anyone outside the group. Or as nearly so as possible.

We have the additional problem that we also want the ones we recruit to help us improve the quality of estimates. Of course, they reduce sampling error. It would be nice if they might also reduce the bias of adjusted estimates. It's a bit harder to judge when that happens.

### "Responsive Design" and "Adaptive Design"

My dissertation was entitled "Adaptive Survey Design to Reduce Nonresponse Bias." I had been working for several years on "responsive designs" before that. As I was preparing my dissertation, I really saw "adaptive" design as a subset of responsive design.

Since then, I've seen both terms used in different places. As both terms are relatively new, there is likely to be confusion about the meanings. I thought I might offer my understanding of the terms, for what it's worth.

The term "responsive design" was developed by Groves and Heeringa (2006). They coined the term, so I think their definition is the one that should be used. They defined "responsive design" in the following way:

1. Preidentify a set of design features that affect cost and error tradeoffs.
2. Identify indicators for these costs and errors. Monitor these during data collection.
3. Alter the design features based on pre-identified decision rules based on the indi…

### An Experimental Adaptive Contact Strategy

I'm running an experiment on contact methods in a telephone survey. I'm going to present the results of the experiment at the FCSM conference in November. Here's the basic idea.

Multi-level models are fit daily with the household being a grouping factor. The models provide household-specific estimates of the probability of contact for each of four call windows. The predictor variables in this model are the geographic context variables available for an RDD sample.

Let $\mathbf{X_{ij}}$ denote a $k_j \times 1$ vector of demographic variables for the $i^{th}$ person and $j^{th}$ call. The data records are calls. There may be zero, one, or multiple calls to household in each window. The outcome variable is an indicator for whether contact was achieved on the call. This contact indicator is denoted $R_{ijl}$ for the $i^{th}$ person on the $j^{th}$ call to the $l^{th}$ window. Then for each of the four call windows denoted $l$, a separate model is fit where each household is assum…

### Future of Responsive and Adaptive Design

A special issue of the Journal of Official Statistics on responsive and adaptive design recently appeared. I was an associate editor for the issue and helped draft an editorial that raised issues for future research in this area. The last chapter of our book on Adaptive Survey Design also defines a set of questions that may be of issue.

I think one of the more important areas of research is to identify targeted design strategies. This differs from current procedures that often sequence the same protocol across all cases. For example, everyone gets web, then those who haven't responded to  web get mail. The targeted approach, on the other hand, would find a subgroup amenable to web and another amenable to mail.

This is a difficult task as most design features have been explored with respect to the entire population, but we know less about subgroups. Further, we often have very little information with which to define these groups. We may not even have basic household or person chara…