is clear that the estimates are far enough out of line, but Bell and his team are not correcting for statistical errors.

Little referred back to Fay and Raghunathan’s points about the skills needed to conduct these types of analysis, arguing that it does not help to think about survey sampling as a field separate from the general statistical community in which models are being taught. Zaslavsky added that if the general feeling is that there are not enough people who can do this type of analysis, then it is important to think about the implications for new directions in training.

Fay said that this debate has been going on for many years, and the concern about model-based estimation has always been that data users cannot understand the complex techniques and are suspicious of what is going on “behind the curtain.” But if data users really understood what is involved with design-based estimation, for example, postsurvey adjustment and variance estimation, they would be concerned about that as well.

He thinks it would be useful for researchers to continue to pursue this research and talk to the data users in contexts similar to that described by Raghunathan. To the extent that researchers are able to communicate their methods and demonstrate a commitment to accuracy, it is likely that data users will embrace these techniques, in the same way they accepted the classical estimators that they do not fully understand.



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