Small-area Estimation Training Materials

Subnational Estimates of Child Mortality using Complex Survey Data


Over the past several years a group of statisticians and demographers at the University of Washington and The Ohio State University have developed a method to produce subnational estimates of child mortality using complex survey data. Open source code to implement the method is publicly available for the R statistical computing environment as the SUMMER package. 

 

  • The training materials available on this page provide additional background, instruction, worked examples, and example code.  

 

The production of these training materials was supported by a grant from the William and Flora Hewlett Foundation to the IUSSP to support innovative demographic methodologies and knowledge sharing for sustainable development.

1. Bayesian Subnational Estimation using Complex Survey Data: Overview, Motivation and Survey Sampling

by Jon Wakefield

 

2. Bayesian Subnational Estimation using Complex Survey Data: Bayesian Inference and Smoothing Models

by Jon Wakefield

 

3. Bayesian Subnational Estimation using Complex Survey Data: Spatial Models for Survey Data
by Jon Wakefield

 

4. Bayesian Subnational Estimation using Complex Survey Data: Introduction to R
by Zehang Richard LI

 

 

5. Bayesian Subnational Estimation using Complex Survey Data: Space‑time Smoothing in R
by Zehang Richard Li

 

 

 

6. Bayesian Subnational Estimation using Complex Survey Data: Case Study (Kenya 2014 DHS)
by Zehang Richard Li

 

    

For more information, contact:

Jon Wakefield 
Richard Li 
Samuel Clark


Related published material:

Changes in the Spatial Distribution of the Under-Five Mortality Rate: Small-area Analysis of 122 DHS Surveys in 262 Subregions of 35 Countries in Africa

 

Estimating Under-Five Mortality in Space and Time in a Developing World Context

 

Space-time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality