​Bayes, buttressed by design-based ideas, is the best

This seminar will cover conceptual arguments and examples suggesting that the Bayesian approach to survey inference can address the varied challenges of survey analysis.   The speaker will discuss how Bayesian models that incorporate features of the complex design can yield inferences that are relevant to the specific data set obtained, but also have good repeated-sampling properties. Examples will focus on the role of auxiliary variables and sampling weights and methods for handling nonresponse.  

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