### Sorry I missed you...

This is another post in a series on currently used survey design features that could be "relabeled" as adaptive. I think it is helpful to relabel for a couple of reasons. 1) It demonstrates a kind of feasibility of the approach, and 2) it would help us think more rigorously about these design options (for example, if we think about refusal conversions as a treatment within a sequence of treatments, we may design better experiments to test various ways of conducting conversions).

The design feature I'm thinking of today has to do with a card that interviewers leave behind sometimes when no one is home at a face-to-face contact attempt. The card says "Sorry I missed you..." and explains the study and that we will be trying to contact them.

Interviewers decide when to leave these cards. In team meetings with interviewers, I heard a lot of different strategies that interviewers use with these cards. For instance, one interviewer said she leaves them every time, even if they stack up. Others used them less frequently after several failed attempts. In any event, they have the decision rules in their heads. (They also have a lot of "data" about each housing unit and more or less experience with making contact with households.) These rules seem to vary.

I could (and did) imagine an adaptive rule that would say when these cards should be left behind. I fit a model that included a bunch of interactions with the SIMY card and other characteristics of the housing unit. The result was a prediction about when SIMY card helped and when it hurt. I then delivered recommendations to interviewers based on these model estimates. The adaptive rule could be stated as:

1) If the SIMY card increase probability of contact on the next attempt, then leave it.
2) If the SIMY card descreases or doesn't effect the probability of contact on the next attempt, then don't leave it.

Whether this rule works or not, I don't know. The interviewers didn't follow the model recommendations.

### "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…