Survey Methods Musings

A recent article by Brick and Tourangeau re-examines the data from a paper by Groves and Peytcheva (2008). The original analyses from Groves and Peytcheva were based upon 959 estimates with known variables measured on 59 surveys with varying response rates. They found very little correlation between the response rate and the bias on those 959 estimates. Brick and Tourangeau view the problem as a multi-level problem of 59 clusters (i.e. surveys) of the 959 estimates. They created for each survey a composite score based on all the bias estimates from each survey. Their results were somewhat sensitive to how the composite score was created. They do present several different ways of doing this -- simple mean, mean weighted by sample size, mean weighted by the number of estimates. Each of these study-level composite bias scores is more correlated with the response rate. They conclude: "This strongly suggests that nonresponse bias is partly a function of study-level characteristics; ...

Following up yet again, on posts about how people choose modes. In particular, it does seem that different subgroups are likely to respond to different modes at different rates. Of course, with the caveat that it's obviously not just the mode, but also how you get there that matters. We do have some evidence about subgroups that are likely to choose a mode. Haan, Ongena, and Aarts examine an experiment where respondents to a survey are given a choice of modes. They found that full-time workers and young adults were more likely to choose web over face-to-face. The situation is an experimental one that might not be very similar to many surveys: Face-to-face and telephone recruitment to the choice of face-to-face or web survey. But at least the design allows them to look at who might make different choices. It would be good to have more data on persons making the choice in order to better understand the choice. For example, information about how much they use the internet might ...