sae4health-package {sae4health}R Documentation

R Shiny App for Small Area Estimation of Health and Demographic Indicators

Description

The sae4health package powers an R Shiny app designed for small area estimation (SAE) of health and demographic indicators in low- and middle-income countries (LMICs). It enables subnational estimation and prevalence mapping for more than 150 binary indicators derived from Demographic and Health Surveys (DHS), providing an intuitive interface for public health analysts, policymakers, and researchers.

Details

Built on the surveyPrev package, sae4health ensures methodological rigor in SAE analysis. It offers guided model selection, automated model fitting, and interactive visualization, making advanced statistical methods accessible to non-experts.

For comprehensive documentation on the sae4health project and web-based app access, visit: https://sae4health.stat.uw.edu/

The latest development version of the package is maintained at: https://github.com/wu-thomas/sae4health

Citation: Wu, Y., Dong, Q., Xu, J., Li, Z. R., & Wakefield, J. (2025). sae4health: An R Shiny Application for Small Area Estimation in Low- and Middle-Income Countries. doi:10.48550/arXiv.2505.01467.

Author(s)

References

Wu, Y., Dong, Q., Xu, J., Li, Z. R., & Wakefield, J. (2025). sae4health: An R Shiny Application for Small Area Estimation in Low- and Middle-Income Countries. arXiv preprint.doi:10.48550/arXiv.2505.01467

See Also

Getting Started:

https://sae4health.stat.uw.edu/overview/project_overview/

Demo and Instruction Video:

https://sae4health.stat.uw.edu/overview/youtube_app_demo/

Statistical Methods:

https://sae4health.stat.uw.edu/method/approach_overview/

Visualization Gallery:

https://sae4health.stat.uw.edu/gallery/visual_overview/

Recent Updates and News:

https://sae4health.stat.uw.edu/blog/


[Package sae4health version 1.2.3 Index]