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New Objective Functions...

I've argued in previous posts that the response rate has functioned like an objective function that has been used to design "optimal" data collections. The process has been implicitly defined this way. And it is probably the case that the designs are less than optimal for maximizing the response rate. Still, data collection strategies have been shaped by this objective function.

Switching to new functions may be difficult for a number of reasons. First, we need other objective functions. These are difficult to define as there is always uncertainty with respect to nonresponse bias. Which function may be the most useful? R-Indicators? Functions of the relationships between observed Y's and sampling frame data?

There are theoretical considerations, but we also need empirical tests. What happens empirically when data collection has a different goal? We haven't systematically tested these other options and their impact on the quality of the data. That should be high on our "to do" list.

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