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Abstract:
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Design-based inference is being challenged due to declining response rates and rising costs, and the increasing availability of large non-probability samples. In the first part of this talk, I aim to present arguments for the continued relevance of this traditional survey paradigm, but also propose ways to make it more appropriate to today’s data collection environment. In the second part, I present some recent results on nonresponse adjusted estimators using constraints. The results will illustrate how traditional approaches continue to be competitive with more sophisticated ones.
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