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Methodological Updates

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.