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We obtain a second order approximation to the mean squared error (MSE), and its estimate, of the empirical or estimated best linear unbiased pre-dictor (EBLUP) of a mixed effect in a general mixed linear normal model. This covers many important small area models in the literature. Unlike previous research in this area, we provide a unified theory of(More)
When a Hierarchical Bayes area level model is used to produce estimates of proportions of units with a given characteristic for small areas, it is commonly assumed that the survey weighted proportion for each sampled small area has a normal distribution and that the sampling variance of this proportion is known. However, these assumptions are problematic(More)
Each month, the Bureau of Labor Statistics publishes estimates of employment for industrial supersectors at the metropolitan statistical area (MSA) level. The survey-weighted ratio estimator that is used to produce estimates for large domains is generally less reliable for MSA level estimation due to the unavailability of adequate sample from a given MSA.(More)
In a large scale survey, we are usually concerned with estimation of some characteristics of interest for a large area (e.g., a country). But we are frequently interested in estimating similar characteristics for a subpopulation using the same survey data. The direct survey estimator which utilizes data only from the small area of interest has been found to(More)
The National Health Interview Survey, conducted by the National Center for Health Statistics, is designed to provide reliable design-based estimates for a wide range of health-related variables for national and four major geographical regions of the USA. However, state-level or substate-level estimates are likely to be unreliable because they are based on(More)
In this paper, we consider an empirical Bayes method for combining multiple data sources in producing end-of-year estimates of crop harvested yield at the county level in the US. The method employs an area level model consisting of two separate submodels-one for the sampling error of direct survey estimates and the other relating true indications to a set(More)
In survey data analysis, there are two main approaches-design-based and model-based-for making inferences for different characteristics of the population. A design-based approach tends to produce unreliable estimates for small geographical regions or cross classified demographic regions due to the small sample sizes. Moreover, when there are no samples(More)
Consider interval estimation of m small area proportions P i (i = 1, · · · , m), where we assume a stratified random sampling design with equal number of observations n in each stratum, and where the domains of interest are the strata. A 100(1 − α)% confidence interval for P i that has appeared repeatedly in the literature and is used in application is(More)