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CSSS 20th: Short course: Bayesian Small Area Estimation using Complex Survey Data
WhenThursday, May 23, 2019, 9 a.m. – 12:30 p.m.
Campus locationIntellectual House (INT)
Campus room4249
Event typesWorkshops
Event sponsorsCenter for Statistics and the Social Sciences

Instructor: Jon Wakefield, Professor of Statistics and Biostatistics, University of Washington

Bayesian Small Area Estimation using Complex Survey Data: Methods and Applications.

Small area estimation (SAE) is an important endeavor in global health, epidemiology, and increasingly, in demography. SAE is often based on data obtained from complex surveys, and one must acknowledge the survey design when statistical analysis is performed so that measures of uncertainty incorporate sampling variability and bias is avoided. Often data in particular areas are sparse (perhaps non-existent) and so spatial smoothing is advantageous to ‘borrow strength’ from neighboring areas. We will begin with introductions to complex survey data, SAE, spatial modeling, and Bayesian statistics and then bring these topics together to show how reliable SAE estimation can be performed. The SUMMER R package will be used to illustrate ideas.

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