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2025

Preprint on the sae4health App Now Available!

We are pleased to share that a preprint introducing the sae4health app is now available on arXiv. The manuscript outlines the statistical framework and methodology underlying the app and includes a detailed case study on under-five stunting in Nigeria.

To cite SAE4Health in publications, please use

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:2505.01467. https://doi.org/10.48550/arXiv.2505.01467.

Advanced Option Feature Now Available!

The Advanced Options panel allows users to customize modeling choices by enabling a nested model, which mitigates oversmoothing when data are sparse, and by incorporating area-level covariates to improve prediction. Users can customize these features after completing the initial data sparsity check step.

Details about the nested model and covariate incorporation can be found in the Model Extension section.

R Shiny App for MICS Released!

We are excited to introduce the MICS version of our Shiny app! This version keeps the core functionalities of the DHS-based app but currently supports a limited set of countries and indicators due to restricted access to geographical data and the absence of standardized coding schemes for individual indicators. However, we plan to expand coverage over time.

The MICS version only has the web-based access, which host data internally on our secure server, eliminating the need for manual uploads.

R Shiny App v1.1.2 Released: Explore the Latest Features!

We are excited to share the following update on the R Shiny App:

  • Report Generation:
    This section section provides an automated way to compile results and visualizations into a comprehensive report. This feature allows users to easily document their analysis and share findings with stakeholders. The generated report includes relevant figures, tables, and summaries from the conducted analysis.