### Identifying all the active components of the design...

I've been reading papers on email prenotification and reminders. They are very interesting. There are usually several important features for these emails: how many are sent, the lag between messages, the subject line, the content of the email (length etc.), the placement of the URL, etc.

A full factorial design with all these factors is nearly impossible. So folks do the best they can and focus on a few of these features. I've been looking at papers on how many messages were sent, but I find that the lag time between message also varies a lot. It's hard to know which of these dimensions is the "active" component. It could be either, both, and may even be synergies (aka "interactions") between the two (and between other dimensions of the design as well).

Linda Collins and colleagues talk about methods for identifying the "active components" of the treatments in these complex situations. Given the complexity of these designs, with a large number of design features,  the fractional factorial designs she describes may be helpful. Further, it might be useful to think of each experiment as a link in a long chain of experimentation (see here). The trick is to design each "link" such that we explore each of the potential design features and any possible interactions with other design features.

1. Hi James, I saw some recent experiments Nancy Bates and colleagues did at the Census Bureau at the nonresponse workshop. She found that none of the things she tested (subject line, content of message) affected response. I think there was one condition were people were more likely to view the survey, but it did not result in more complete responses. We need more experiments on e-mail invitations, as web surveys rely on them. Also, I think that e-mail invitations don't work the same as paper ones. E-mail is much shorter and faster.

2. I'm reviewing this literature because I am writing up the results of an experiment with email reminders. We didn't do anything with the time between reminders. Missed an opportunity. I'm trying to do something on the time between reminders for a study we are beginning next month.

I agree, email is different.

### "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…