Estimating the prevalence of anemia rates among children under five in Peruvian districts with a small sample size

Anna Sikov () and José Cerda-Hernandez ()
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Anna Sikov: National Engineering University
José Cerda-Hernandez: National Engineering University

Statistical Methods & Applications, 2023, vol. 32, issue 5, No 14, 1779-1804

Abstract: Abstract In this paper we attempt to answer the following question: “Is it possible to obtain reliable estimates for the prevalence of anemia rates in children under five years in the districts of Peru?” Specifically, the objective of the present paper is to understand to which extent employing the basic and the spatial Fay–Herriot models can compensate for inadequate sample size in most of the sampled districts, and whether the way of choosing the spatial neighbors has an impact on the resulting inference. Furthermore, we explore the question of how to choose an optimal way to define the neighbors. As such, our research focuses on studying the prediction accuracy of the aforementioned models, and on the sensitivity of the results to the definition of “neighbor”. We use the data from the Demographic and Family Health Survey of the year 2019, and the National Census carried out in 2017.

Keywords: Direct estimate; Spatial autocorrelation; Fay–Herriot model; Mean square error; Bootstrap (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10260-023-00698-x

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