The modelbased approach to small area estimation offers several advantages including. Small area demography refers to demographic applications and analyses executed at local and regional scales smith and morrison, 2005. An r package for small area estimation by isabel molina and yolanda marhuenda abstract we describe the r package sae for small area estimation. New important developments in small area estimation. The term small area in this context generally refers to a small geographical area such as a county. Conference on small area estimation conference center, u. Small area estimation wiley series in survey methodology. A methodological approach to small area estimation for the. This package can be used to obtain modelbased estimates for small areas based on a variety of models at the area and unit levels, along with basic direct and indirect estimates. The global strategy is an initiative endorsed in 2010 by the united nations statistical. Aug 29, 2019 because standalone surveys may not support reliable estimation at these lower geographic levels, modelbased small area estimates saes that combine information from multiple sources could be an effective alternative approach. While no universally accepted definition exists for what constitutes a small area for population estimation and projection purposes, it commonly involves administrative units below the national and state level. Carlin bayesian methods have been used quite extensively in recent years for solving small area estimation problems.
In the presentationthe comparison of estimation results for spatial and spatiotemporal small area model is presented. Bureau of the census, suitland, maryland revised program presenters of talks are listed in boldface. Small area estimation of cancer risk factors and screening. Generalized maximum likelihood method in linear mixed models. Pdf over the last three decades, mixed models have been frequently used in a wide range of small area applications. This article argues that an interdisciplinary approach, combining the body of statistical research in small area estimation with the body of research in social data mining based on big data, can provide novel means to tackle this problem successfully. Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics from both public and private sectors. Multilevel regression and poststratification for smallarea estimation of population health outcomes. Multilevel regression and poststratification for small area estimation of population health outcomes. The problem of small area estimation sae is how to produce reliable estimates of characteristics of interest such as means, counts, quantiles, etc. Abstract we describe the r package sae for small area estimation.
Mean squared errors are estimated by analytical approximations in simple models and applying bootstrap procedures in more complex models. Small area estimation an overview sciencedirect topics. Small area estimation wiley online books wiley online library. Lahiri and huilin li university of maryland, college park, and national cancer institute abstract.
Mixed models with an application in small area estimation p. Furthermore, small area estimation problems can confound attempts to accurately downscale predictions from the city or district to individual buildings. Section 4 provides four examples that reflect the diverse uses of small area estimations at statistics canada 2. As an example, the us current population survey cps provides accurate statistics about income and poverty for the nation as a whole.
As a consequence, the eblup estimate of a small area mean reduces to a. Introduction to small area estimation bias project. Written by two experts in the field, small area estimation, second edition provides a comprehensive and uptodate account of the methods and theory of small area estimation sae, particularly indirect estimation based on explicit small area linking models. Popular techniques for small area estimation use implicit or. Bayesian statistics for small area estimation bias project. Small area estimation tackles the problem of providing reliable estimates of one or several variables of interest in areas where the information available on those variables is, on its own, not su.
Small area modelbased estimators using big data sources in. Small area estimation is important in light of a continual demand by data users for finer geographic detail of published statistics and for various subpopulations. An accessible introduction to indirect estimation methods, both traditional and modelbased. Small area estimation methodologies are beneficial for business organisations, policy. The second edition is also an ideal textbook for graduatelevel courses in sae and reliable small area statistics.
I believe that it has the potential to turn small area to a larger area of importance to both researchers and practitioners. Section 3 defines the notation, provides a number of typical direct estimators, and indirect estimators used in small area estimation. Survey domain analytical population subgroups for which equally reliable estimates are desired e. Small area estimation using esds government surveys.
Traditionally, small area is a small geographic area within a larger geographic area or a small demographic group within a larger demographic group. Application to mexican income data conclusion why using small area estimation population of interest or target population. In the presentation the method of small area estimation under spatial simultaneous autoregressive sar model is presented. Traditional demographic sample surveys designed for national estimates do not provide large enough samples to produce reliable direct estimates for. An overview aapor 2014 25 28 referencesii datta, g. Pushpal k mukhopadhyay and allen mcdowell, sas institute inc. Pdf mixed model prediction and small area estimation. The estimation was conducted using both spatial eblup and hierarchical bayes method with sar random effects that depend on. Bayesian statistics for small area estimation 3 area and another one which re ects likely correlation between neighbouring regions. The sample size in the domain of interest is too small to use a standard estimator. Solutions and perspectives was prepared within the framework of the global strategy to improve agricultural and rural statistics.
Pdf small area estimation of income using spatiotemporal. New important developments in small area estimation 3 ss1. Jul 14, 2016 zhang x, holt jb, lu h, wheaton ag, ford es, greenlund kj, et al. The problem of small area estimation sae is how to pro duce reliable. Small area estimation in r with application to mexican income.
Pdf small area estimation under spatial sar model jan. Aug 14, 2015 small area estimation, second edition is an excellent reference for practicing statisticians and survey methodologists as well as practitioners interested in learning sae methods. Spatial disaggregation and smallarea estimation methods for. Apr 16, 2017 small area estimation sae has become a widely used technique in official statistics since the last decade of past century. The analysis was conducted for incomerelated variables coming from the polish household budget survey and explanatory variables. Small area estimates have been produced using administrative files or surveys enhanced with administrative.
For surveys of governments, small area refers to their state by function or itemcode. Functional mixed effects model for small area estimation. Jan 09, 2003 this pioneering work, in which rao provides a comprehensive and uptodate treatment of small area estimation, will become a classic. It is now widely recognized that direct survey estimates for small areas are likely to yield unacceptably large standard errors due to the smallness of sample sizes in the areas. New important developments in small area estimation arxiv. Part of the challenge emerges from data constraints, as few sanitation agencies collect and make available granular waste collection data.
Standard methods frequently produce zero estimates of dispersion parameters in the underlying linear mixed model. Note that disease mapping applications are based on data available on disease status for all individuals in every area, whilst small area estimation. A typical income consumption or living standards survey collects detailed information that can be used for estimation of our statistic of interest. Guidelines on small area estimation for city statistics and other. This technical report on spatial disaggregation and smallarea estimation methods for agricultural surveys. In small area estimation, a model is used to estimate the response in subpopulations with few or no sample observations. Pdf small area estimation sae was first studied at statistics canada in the seventies. Small area estimation is any of several statistical techniques involving the estimation of parameters for small subpopulations, generally used when the subpopulation of interest is included in a larger survey. Uses a basic area level linear model to illustrate the methods. Using machine learning and small area estimation to predict. Rao carleton university, ottawa, canada paper presented at the ntts 20 conference, brussels. Small area estimation techniques combine multiple data sources to capitalize on each data sources strengths. Donald malec, national center for health statistics, cdc joint roundtable on health data needs for community. When the sample size is not enough to provide reliable estimates at a very particular level, the power of models and auxiliary.
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