Registration for this module closes June 30. 

Schedule notice: This module consists of two sessions on July 7 - 8:30 a.m. to noon and 1-4:30 p.m. Pacific (11:30 a.m. to 3 p.m. and 4 p.m. to 7:30 p.m. Eastern). The registration rates for this course are the same as for a two-day module, which also consists of two sessions.

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.