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Response Rates as a Reward Function

I recently saw a presentation by Melanie Calinescu and Barry Schouten on adaptive survey design. They have been using optimization techniques to design mixed-mode surveys. In the optimization problems, they seek to maximize a measure of sample balance (the R-Indicator) for a fixed cost by using different allocation to the modes for different subgroups in the population (for example, <35 years of age and 35+).  The modes in their example are web and face-to-face. In their example, the older group is more responsive in both modes, so they get allocated at higher rates to web. You can read their paper here to see the very interesting setup and results.

In the presentation, they showed what happens when you use the response rate as the thing that you are seeking to maximize. In some of the lower budgets, the optimal allocation was to simply ignore the younger group. You could not get a higher response rate by doing anything other than using all your resources on the older group. Once you had taken all of the relatively easy interviews with the older group, you might try to get some easy interviews with the younger group.

I thought that was an interesting result. It showed that allowing the response rate to guide data collection can be harmful. Fortunately, it seems that no one would actually carry out such a design. Still, it does make me wonder what harmful effects the response rate may have on data collection practices.
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