Side event at the 2018 APA Conference
IUSSP Two-Day Short Course
Bayesian Small Area Estimation using Complex Survey Data:
Methods and Applications
Shanghai, China, 10-11 July 2018, 9-5pm.
Shanghai University
This course is organized by the IUSSP as a side event at the 4th Asian Population Association Conference, taking place in Shanghai, China, 11-14 July 2018.
Organizing committee: Sam Clark (Department of Sociology, The Ohio State University), Zehang Li (Department of Statistics, University of Washington), Jon Wakefield (Departments of Statistics and Biostatistics, University of Washington).
Course Description:
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, space-time modeling, and Bayesian statistics and then bring these topics together to show how reliable SAE estimation can be performed. The course will end with a complex application: space-time smoothing of under-5 infant mortality using demographic and health survey (DHS) data. This application is part of an on-going collaboration that the instructors have with UNICEF. In this context, the use of both full and summary birth history data will be described. Throughout, hands-on experience will be gained through the use of the instructors’ SUMMER R package that carries out space-time smoothing of area-level complex survey data, based on methodology that has been published1 by the instructors.
1. Mercer, L., Wakefield, J., Pantazis, A., Lutambi, A., Masanja, H. and Clark, S. (2015). Small area estimation of child mortality in the absence of vital registration. The Annals of Applied Statistics, 9, 1889-1905.
Prerequisites:
None, although familiarity with R, Bayesian methods, and mortality measurement are helpful. Participants may want to bring their own laptop with R installed so that they can follow along and experiment with the data and code. Number of Participants: 20.
Registration: Please register online. Due to the limited number of places available, registration status will be confirmed by 2 April 2018. Participants registered to attend the APA Conference who have a communication on the programme will receive preference.
Travel Support: A small number of travel support awards will be provided to LDC participants; applicants should be IUSSP members in good standing who plan to participate in the APA Conference.