### Attrition in Designs that use Frequent Measurement

I saw this paper recently that talked about how to measure and evaluate nonresponse to surveys that use short, frequently-administered instruments ("measurement-burst survey").

I've been working on a problem with data like these for a while. A complication was that the questionnaire changed based upon the intervals between measurements. For example, questions might begin, "Since you last completed this survey..." or "in the last two weeks..." depending upon the situation. Plus, panel members could choose to respond at different intervals, even though they were asked to respond at a specified interval.

This made for a complex pattern of missing data. I ended up defining attrition in several ways.  The most useful was to lay out a grid over time. The survey was designed to be taken weekly, so I looked at each week over the time period to see if any reporting occured. This allowed me to how many cells in the grid were missing.

But even that wasn't very satisfying. In this study, it's reasonable to assume that someone who responds every other week gives you more information than someone who responds for the first half of the data collection period. Now I'm looking at imputation as a way to measure the relative information content across different patterns of missing data. This uses all the observed data an looks at how much information was "lost" for each pattern.

1. That's good to see this post.

### "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…