Collaborative Research: Small-Area Estimation - A Growing Problem for the Next Millennium

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Large scale sample surveys are usually designed to produce reliable estimates of various characteristics of interest for large geographic areas. However, for effective planning of health, social, and other services, there is a growing demand to produce similar estimates for smaller geographic areas and subpopulations, commonly referred to as small-areas (or small-domains). The accuracy of small-area statistics is especially crucial when data are used to apportion government funds among various groups.This project focuses on development of new robust small-area estimation methods and the associated model diagnostics. The estimation methods will be developed under general multi-level models which will be useful in solving a variety of small-area estimation problems. To address an important and yet largely neglected aspect of model validation and model selection associated with multi-level models, a test using a sample splitting technique is proposed. Splitting the sample into an estimation set and a validation set can also be used for assessing the actual power of the model. This area of research will continue to grow as social scientists find the need to use complex multi-level models to solve their problems.The research is an outgrowth of the investigators' experiences with small-area estimation problems encountered by various federal, state, and private agencies. Importantly, this project will address a crucial practical problem underlying the work of many governmental and private institutions throughout the world. Further, this research on small-area estimation also will contribute significantly to the literature on survey sampling, generalized linear mixed models, empirical best prediction theory, linear empirical Bayes, variance component estimation, resampling methods, model diagnostics, higher order asymptotics, and statistical computing. Because of the interests of different types of researchers (e.g., survey samplers, main stream statisticians, social scientists), small-area estimation will remain one of the most intriguing problems in survey sampling as we advance into the next millennium.