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Showing posts from June, 2015

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'

Personalized Survey Design

In my last post, I talked about personalized medicine. I found out this week that in personalized medicine, there is a distinction between targeted and tailored treatments. Targeted treatments are aimed at specified subgroups of the population, while tailored protocols are individual-specific treatments that may be based in a targeted treatment, but use within-patient variation to "tune" treatments over time. I wonder if the kind of tailored protocols suggested by this kind of tailoring are possible for surveys? Panel surveys are one area where this may be possible. But it seems that the panel would have to have many waves or repetitions. There might not be enough measurement of variation with only a few waves. What's a few? Let's say fewer than 10 or 20. It seems like these methods might have an application in surveys that use frequent measurement and/or a relatively long period of time. For example, imagine a survey that collected data weekly for 2 or 3 years. O