Skip to main content

Sorry I missed you...

We've been using "Sorry I missed you" (SIMY) cards for many years in face-to-face surveys. We don't know that they work, but we keep using them anyway. I suspect that these cards are useful sometimes, not useful other times, and possibly harmful in some situations.

We haven't really collected data on the use of these cards, but interviewers do usually say something in their call notes about the use of SIMY. I've been working with data based on these notes. I'm trying to identify cases where the SIMY is useful and where it may be harmful.

We should be running some experiments with these cards in the near future. As with many of the experiments we've been running in face-to-face surveys, we have a double burden of proof.
  • First, will interviewers respond to recommendations delivered via our computerized sample management system.
  • Second, if they follow the recommendation, does it help.

Hopefully, we'll have some evidence on one or both of these questions soon.
Labels:

Comments

  1. AnonymousNovember 12, 2009 at 3:04 PM

    One on-going problem is that we don't seem to take the time to think about these issues theoretically. So why would SIMY cards work? Is it just an additional contact (occurring whenever the household member opens the door and notices a card), a social exchange, or something else. If it is an additional contact, then the location where the card is left may matter (I almost never go out my own front door). If it is a social exchange, as in Putnam's Bowling Alone, then it would matter that (a) the interviewer hand-writes a note, and (b) that the interviewer reveals something about him/herself (for example a phone number, best time to reach, etc.)

    ReplyDelete
  2. JamesNovember 13, 2009 at 3:34 PM

    One of my main interests with the SIMY card is to try and tailor its use to the specifics of the case. The first step is to see if that might be possible. My models (with messy data) indicate that there may be interactions between observable characteristics of the neighborhood and the effectiveness of the SIMY card in promoting contact.

    If we can establish that much, then it may be possible to experiment with other aspects of the SIMY card (e.g. hand-written notes).

    ReplyDelete

Post a Comment

Popular posts from this blog

Tailoring vs. Targeting

One of the chapters in a recent book on surveying hard-to-reach populations looks at "targeting and tailoring" survey designs. The chapter references this paper on the use of the terms among those who design health communication. I thought the article was an interesting one. They start by saying that "one way to classify message strategies like tailoring is by the level of specificity with which characteristics of the target audience are reflected in the the communication." That made sense. There is likely a continuum of specificity ranging from complete non-differentiation across units to nearly individualized. But then the authors break that continuum and try to define a "fundamental" difference between tailoring and targeting. They say targeting is for some subgroup while tailoring is to the characteristics of the individual. That sounds good, but at least for surveys, I'm not sure the distinction holds. In survey design, what would constitute
36 comments
Read more

What is Data Quality, and How to Enhance it in Research

  We often talk about “data quality” or “data integrity” when we are discussing the collection or analysis of one type of data or another. Yet, the definition of these terms might be unclear, or they may vary across different contexts. In any event, the terms are somewhat abstract -- which can make it difficult, in practice, to improve. That is, we need to know what we are describing with those terms, before we can improve them. Over the last two years, we have been developing a course on   Total Data Quality , soon to be available on Coursera. We start from an error classification scheme adopted by survey methodology many years ago. Known as the “Total Survey Error” perspective, it focuses on the classification of errors into measurement and representation dimensions. One goal of our course is to expand this classification scheme from survey data to other types of data. The figure shows the classification scheme as we have modified it to include both survey data and organic forms of d
Post a Comment
Read more

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 assu
4 comments
Read more