The U.S. Census Bureau’s SAIPE (Small Area Income and Poverty Estimates) program estimates poverty for various age groups for states, counties, and school districts of the U.S. We focus here on poverty estimates of school-aged (5-17) children for counties. The corresponding SAIPE production model applies to log transformed direct survey estimates for each county of the number of 5-17 year-olds ...

This paper considers small-area estimation with proportion data, and discusses the choice of upper-level model for the variation over areas. Inference about the random effects for the areas may depend strongly on the choice of this model, but this choice is not a straightforward matter. We show that posterior distributions of the deviances for the competing models provide a valuable tool for th...

............................................................................................................................................... 3 Introduction .......................................................................................................................................... 4 Overview of the main methodological approaches to SAE ..............................................

The Census Bureau is considering the replacement of the decennial census long form for the collection of the sample data with a continuous survey. The Continuous Measurement Survey (CMS) is designed to provide yearly estimates for large areas and multiyear averages for small areas. This will provide timely estimates for large areas that are currently produced only every ten years from the decen...

The objective of small area estimation (SAE) methods is to use survey data for estimating some characteristics, such as means, totals, quantiles of items of interest, in areas or domains where the sample size is not large enough to obtain reliable direct estimates. In the last years SAE methods have received a growing interest, since their use in the formulation of new policies and programs, po...

In public health management there is a need to produce subnational estimates of health outcomes. Often, however, funds are not available to collect samples large enough to produce traditional survey sample estimates for each subnational area. Although parametric hierarchical methods have been successfully used to derive estimates from small samples, there is a concern that the geographic divers...

The effective use of spatial information, that is the geographic locations of population units, in a regression model-based approach to small area estimation is an important practical issue. One approach for incorporating such spatial information in a small area regression model is via Geographically Weighted Regression (GWR). In GWR the relationship between the outcome variable and the covaria...

Abstract We describe the R package sae for small area estimation. This package can be used to obtain model-based estimates for small areas based on a variety of models at the area and unit levels, along with basic direct and indirect estimates. Mean squared errors are estimated by analytical approximations in simple models and applying bootstrap procedures in more complex models. We describe th...

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fi...