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Mixed-Effects Models and Small Area Estimation
This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both...
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Three-fold Fay–Herriot model for small area estimation and its diagnostics
This paper introduces a three-fold Fay–Herriot model with random effects at three hierarchical levels. Small area best linear unbiased predictors of...
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Basic Mixed-Effects Models for Small Area Estimation
Statistical inference in the general linear mixed models is explained in the previous chapters. As basic models used in small area estimation, in...
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Small area estimation of health insurance coverage for Kenyan counties
Health insurance is important in disease management, access to quality health care and attaining Universal Health Care. National and regional data on...
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mind, A methodology for multivariate small area estimation with multiple random effects
This paper describes a small area estimator based on a multivariate linear mixed model implemented in the R Package mind . The method is a...
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Hierarchical Bayes small area estimation for county-level health prevalence to having a personal doctor
The complexity of survey data and the availability of data from auxiliary sources motivate researchers to explore estimation methods that extend...
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Small area estimation of average compositions under multivariate nested error regression models
This paper investigates the small area estimation of population averages of unit-level compositional data. The new methodology transforms the...
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Bayesian hierarchical spatial model for small-area estimation with non-ignorable nonresponses and its application to the NHANES dental caries data
The National Health and Nutrition Examination Survey (NHANES) is a major program of the National Center for Health Statistics, designed to assess the...
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The impact of local cost-of-living differences on relative poverty incidence: an application using retail scanner data and small area estimation models
Estimating economic poverty indicators at the local level is essential for well-targeted data-driven welfare policies. However, Italy is a country...
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Advanced Theory of Basic Small Area Models
In Chap. 4, we introduced two famous small area models, Fay–Herriot and nested error regression models, and provided basic theory of parameter...
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Small Area Estimation
This chapter gives some introductory comments about small area estimation and mixed models. As the book illustrates the statistical methodology with...
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Small Area Estimation and Develo** Small Domain Statistics
On drawing a sample suitably from a survey population so as to estimate its total, mean or any other parameters, sometimes, in addition, it may be of...
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A Course on Small Area Estimation and Mixed Models Methods, Theory and Applications in R
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on...
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Extensions of Basic Small Area Models
The flexibility of the two basic small area models described in Chap. 4 can be limited for practical...
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Models to Support Forest Inventory and Small Area Estimation Using Sparsely Sampled LiDAR: A Case Study Involving G-LiHT LiDAR in Tanana, Alaska
A two-stage hierarchical Bayesian model is developed and implemented to estimate forest biomass density and total given sparsely sampled LiDAR and...
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Small area prediction of proportions and counts under a spatial Poisson mixed model
This paper introduces an area-level Poisson mixed model with SAR(1) spatially correlated random effects. Small area predictors of proportions and...
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Small area estimation of socioeconomic indicators for sampled and unsampled domains
Socioeconomic indicators play a crucial role in monitoring political actions over time and across regions. Income-based indicators such as the median...
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Addressing Covariate Lack in Unit-Level Small Area Models Using GAMLSS
The primary goal of this study is to estimate the Theil index using a unit-level Small Area Estimation (SAE) model. This has lead two primary...
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Bias Calibration for Robust Estimation in Small Areas
It is well known that the existence of outliers in a sample can significantly affect the estimation of population parameters. Intuition suggests that...