In particular, one small area estimation method involving the combination of detailed survey and demographic data has been used relatively often to create estimates of health risks and behaviors. This tutorial aims at providing an updated version of the tutorial presented at user. The term small area in this context generally refers to a small geographical area such as a county. We introduce a command, fayherriot, that implements the fay herriot model fay and herriot, 1979, journal of the american statistical association 74. Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. Businesses survey of business owners survey of income and program participation sipp all surveys and programs media newsroom survey participants respondents partners educators and students. Improving estimates of district hiv prevalence and burden in. When the sample size is not enough to provide reliable estimates at a very particular level, the power of models and auxiliary. I would like to enquire about the existence of ado or code to perform small area estimation in stata. The course will begin with a history of small area estimation and different uses of small area statistics in both public and private sectors. For a comprehensive account of sae techniques, seerao2003.
This session focused on the topic of producing estimates in situations in which only a small amount of information is available or there are other limitations, such as physical, temporal, or conceptual boundaries that make direct estimation difficult. The fayherriot model improves the precision of arealevel direct estimates. Synthetic estimators for small area estimation method. We introduce a suite of small area estimation commands sae in stata that set the base for future work in this topic for the community of stata users. Most of the time, small area estimation approach is specifically tailored to a given application, depending on whether you have unit or area models, at what levels you have your auxiliary data, etc. The fayherriot command for estimating smallarea indicators.
Pushpal k mukhopadhyay and allen mcdowell, sas institute inc. Bayesian alternatives of both the nonspatial and spatial mixed e ects models for small area estimation have been proposed see, for example, datta and ghosh 1991. Comparison of estimation methods for creating small area. Small area estimation for survey data analysis using sas software pushpal k mukhopadhyay and allen mcdowell, sas institute inc. When the sample size is not enough to provide reliable. The paper presents the method of hierarchical bayes hb estimation under small area models with spatially correlated random effects and a spatial structure implied by the simultaneous. 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. It is now widely recognized that direct survey estimates for small areas are likely to yield unacceptably large.
Small area estimation of sparse disease counts using shared. Small area estimation sae has become a widely used technique in official statistics since the last decade of past century. Businesses survey of business owners survey of income and program. This paper presents a new family of stata functions devoted to small area estimation.
Attendants coming from nonuk academic institutions will be offered the same fees as those coming from uk academic institutions i. Mata functions and codes are open source and can be linked with new functions or methods by. This paper presents a new family of stata functions devoted to small. Smallarea estimation refers to methods for obtaining usable estimates for domains for which sample sizes are inadequate to produce adequately precise estimates using only data from within the domain. A stata package for unit level small area estimation english the. Major advantages include use of commonly available aggregated arealevel covariates, and relative ease of implementation using freely available software. Synthetic estimators for small area estimation method summary in surveys conducted by statistical offices one of the main problem is to have reliable estimates for domains for which the sample size is too small or even equal to zero. Experimental data products related sites software tables training and workshops. Statistical software components, s458495, boston college department of economics. Small area estimation sae of survey data down to small area level has become an increasingly widespread activity as scholars and policymakers have sought to gain ever more detailed spatial information to better target interventions or resources and to evaluate local policy impacts. Structure of the commands are intuitive for future. A small area procedure for estimating population counts.
Samuels 18 cantines island saugerties ny 12477 on nov 23, 20, at 8. Bayesian alternatives of both the nonspatial and spatial mixed e ects models for small area estimation have been proposed see, for example, datta and ghosh 1991, ghosh et al. Functional mixed effects model for small area estimation. Small area estimation of sparse disease counts using shared component modelsapplication to birth defect registry data in new south wales, australia. The small area estimation sae methods included in the r package sae have applications in many different. Small area estimation sae of survey data down to small area level has become an increasingly widespread activity as scholars and policymakers have sought to gain ever more detailed spatial. Beard a c geoff morgan a b douglas lincoln a richard summerhayes c deborah donoghue a therese dunn a b david muscatello d kerrie mengersen e.
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. The paper presents the method of hierarchical bayes hb estimation under small area models with spatially correlated random effects and a spatial structure implied by the simultaneous autoregressive sar process. The course will begin with a history of smallarea estimation and different uses of smallarea statistics in both public and private sectors. The r package sae is mainly designed for modelbased small area estimation. Introduction to small area estimation small area estimation in r application to mexican income data conclusion r packages for sae other packages i bayessae for arealevel models in bayesian context i. Structure of the commands are intuitive for future integration of the new methods or functions. This is accomplished by incorp orating information from outside sources. The paper was designed to appraise the excel toolkit designed by garenne and mccaa 2017 to implement the 4pocm in relation to schoumakers 20 stata software. Methods for indirect small area estimation parameters of interest. The basic arealevel fayherriot model is a viable choice for estimation of hiv prevalence and numbers of plhiv in small, unplanned survey domains. The client will always require more than is specified at the design stage fuller 1999. A common approach to small area estimation is to derive predictors under a. Pdf small area estimation of income under spatial sar model. Apr 16, 2017 small area estimation sae has become a widely used technique in official statistics since the last decade of past century.
The package introduces new mata functions and a plugin used. This study assesses the capabilities of the 4parameters own children method 4pocm approach in the estimation of fertility rates of small areas using schoumakers 20 poisson regressionbased personperiod approach ppa. A stata package for unit level small area estimation english. Stata that set the base for future work in this topic for the community of stata. We present a new stata package for small area estimations of poverty and inequality implementing methodologies from elbers, lanjouw, and. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for. Small area estimationpoverty map in stata ideasrepec. Introduction to small area estimation small area estimation in r application to mexican income data conclusion small area estimation in r with application to mexican income data annkristin kreutzmann1, s oren pannier1 natalia rojasperilla1, timo schmid1 matthias templ2 nikos tzavidis3 1 freie universit at berlin. Small area estimation using esds government surveys. Synthetic estimators for small area estimation method summary in surveys conducted by statistical offices one of the main problem is to have reliable estimates for domains for which the sample size is.
Try googling small area estimation stata and mcmc stata steve steven j. Small area estimation deals with the problem of providing estimates of. An overview aapor 2014 25 28 referencesii datta, g. Small area estimation and microsimulation modeling is the first practical handbook that comprehensively presents modern statistical sae methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. The brfss sae method uses 4 data sets the brfss, the american community survey public use microdata sample, nielsen claritas population totals, and the missouri census. In particular, bayesian small area spatial modelling has already been successful in. The package introduces new mata functions and a plugin used to circumvent memory limitations that inevitably arise when working with larger datasets. 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. Evaluations and improvements in small area estimation. Domain estimates, reliability, and smallarea estimation.
Improving estimates of district hiv prevalence and burden. The modelbased approach to small area estimation offers several advantages including. Analysis of poverty data by small area estimation wiley. Statistical smallarea estimation approaches can sometimes be used to develop usable domain estimates in scenarios 2 and 3 above. This paper presents a new family of stata functions devoted to. 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. Small area or small domain, local area, subdomain, small subgroup, minor domain, etc. In particular, one small area estimation method involving the combination of detailed survey and demographic data has been used relatively often to create estimates of health risks and behaviors such as smoking, hypertension, or physical activity twigg et al. 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.
Stata module to provide commands and mata functions. Stata module to fit an area level fayherriot model. A methodological approach to small area estimation for the. Small area estimation of sparse disease counts using shared component modelsapplication to birth defect registry data in new south wales, australia author links open overlay panel arul earnest a john r. This course will provide an introduction to the main concepts and issues in small estimation and describes various approaches for estimating different small area parameters. Small area estimation of sparse disease counts using. Inform national and subnational policies and programs. This session focused on the topic of producing estimates in situations in which. Smallarea estimation refers to methods for obtaining usable. We present a new family of stata functions devoted to small area estimation, sae. Small area estimation in r with application to mexican income.
Jul 14, 2016 the aims of this study were to 1 describe a new brfss small area estimation sae method and 2 investigate the internal and external validity of the brfss saes it produced. 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. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for specific areassubpopulations. 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. This is accomplished by incorporating information from outside sources. Introduction to small area estimation small area estimation in r application to mexican income data conclusion r packages for sae other packages i bayessae for area level models in bayesian context i saerobust for robust area level models i saery and sae2 for area level models with time e ects i sae for a wide variety of sae methods including area level and unitlevel models for the mean as. Traditional demographic sample surveys designed for national estimates do not provide large enough samples to produce reliable direct estimates for. Small area estimation and microsimulation modeling is the first practical handbook that comprehensively presents modern statistical sae methods in the framework of ultramodern spatial microsimulation. I have used gllamm in my applications with binary outcomes, although of course the speed has been killing me. This course will provide an introduction to the main concepts and. An r package for small area estimation by isabel molina and yolanda marhuenda abstract we describe the r package sae for small area estimation. We present a new stata package for small area estimations of poverty and inequality implementing methodologies from elbers, lanjouw, and lanjouw econometrica, 2003. A common approach to small area estimation is to derive predictors under a speci ed mixed model for the direct estimators. Oct 12, 2016 furthermore, there is a shortage of training materials on small area estimation with r.
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