### Messy Experiments

I have this feeling that survey experiments are often very messy. Maybe it's just in comparison to the ideal type -- a laboratory with a completely controlled environment where only one variable is altered between two randomly assigned groups.

But still, surveys have a very complicated structure. We often call this the "essential survey conditions." But that glib phrase might hide some important details. My concern is that when we focus on a single feature of a survey design, e.g. incentives, we might come to the wrong conclusion if we don't consider how that feature interacts with other design features.

This matters when we attempt to generalize from published research to another situation. If we only focus on a single feature, we might come to the wrong conclusion. Take the well-known result -- incentives work! Except that the impact of incentives seems to be different for interviewer-administered surveys than for self-administered surveys. The other features of the design are also important and may mediate the expected results of the feature under consideration.

Every time I start to write a literature review, this issue comes up in my mind as I try to reconcile the inevitably conflicting results. Of course, there are other problems, such as the normal noise associated with published research results. But, there is this other potential reason out there that should be kept in mind.

The other side of the issues comes up when I'm writing up the methods used. Then I have to remind myself to be as detailed as possible in describing the survey design features so that the context of the results will be clear.

### "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…