An overview aapor 2014 25 28 referencesii datta, g. Structure of the commands are intuitive for future integration of the new methods or functions. Small area estimation in r with application to mexican. 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. We present a new stata package for small area estimations of poverty and inequality implementing methodologies from elbers, lanjouw, and. Small area estimation in r with application to mexican income. The course will begin with a history of small area estimation and different uses of small area statistics in both public and private sectors. Pushpal k mukhopadhyay and allen mcdowell, sas institute inc. 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.
The small area estimation sae methods included in the r package sae have applications in many different. Major advantages include use of commonly available aggregated arealevel covariates, and relative ease of implementation using freely available software. Oct 12, 2016 furthermore, there is a shortage of training materials on small area estimation with r. 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. When the sample size is not enough to provide reliable. 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.
Functional mixed effects model for small area estimation. The fayherriot command for estimating smallarea indicators. 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. A methodological approach to small area estimation for the. Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. Methods for indirect small area estimation parameters of interest. I would like to enquire about the existence of ado or code to perform small area estimation in stata. Domain estimates, reliability, and smallarea estimation. 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. 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. 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.
Synthetic estimators for small area estimation method. 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. Statistical smallarea estimation approaches can sometimes be used to develop usable domain estimates in scenarios 2 and 3 above. In particular, bayesian small area spatial modelling has already been successful in. The term small area in this context generally refers to a small geographical area such as a county. 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. Stata module to fit an area level fayherriot model. Samuels 18 cantines island saugerties ny 12477 on nov 23, 20, at 8. An r package for small area estimation by isabel molina and yolanda marhuenda abstract we describe the r package sae for small area estimation. The fayherriot model improves the precision of arealevel direct estimates. 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.
Comparison of estimation methods for creating small area. 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. Stata that set the base for future work in this topic for the community of stata. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for. When the sample size is not enough to provide reliable estimates at a very particular level, the power of models and auxiliary. Small area estimation of sparse disease counts using shared. Inform national and subnational policies and programs. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for specific areassubpopulations. The r package sae is mainly designed for modelbased small area estimation. This is accomplished by incorp orating information from outside sources. 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. 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. Smallarea estimation refers to methods for obtaining usable. 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.
It is now widely recognized that direct survey estimates for small areas are likely to yield unacceptably large. 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. Small area estimation of sparse disease counts using shared component modelsapplication to birth defect registry data in new south wales, australia. This paper presents a new family of stata functions devoted to. Experimental data products related sites software tables training and workshops. Attendants coming from nonuk academic institutions will be offered the same fees as those coming from uk academic institutions i. 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. Evaluations and improvements in small area estimation. Small area estimation for survey data analysis using sas software pushpal k mukhopadhyay and allen mcdowell, sas institute inc. Small area estimationpoverty map in stata ideasrepec. 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. 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. Stata module to provide commands and mata functions.
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. This paper presents a new family of stata functions devoted to small. This paper presents a new family of stata functions devoted to small area estimation. Analysis of poverty data by small area estimation wiley. Improving estimates of district hiv prevalence and burden in.
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. A stata package for unit level small area estimation english. We introduce a command, fayherriot, that implements the fay herriot model fay and herriot, 1979, journal of the american statistical association 74. 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. This tutorial aims at providing an updated version of the tutorial presented at user. 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 basic arealevel fayherriot model is a viable choice for estimation of hiv prevalence and numbers of plhiv in small, unplanned survey domains. Try googling small area estimation stata and mcmc stata steve steven j. 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. The package introduces new mata functions and a plugin used to circumvent memory limitations that inevitably arise when working with larger datasets. This session focused on the topic of producing estimates in situations in which. Small area estimation of sparse disease counts using. Traditional demographic sample surveys designed for national estimates do not provide large enough samples to produce reliable direct estimates for.
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. 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. 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. Businesses survey of business owners survey of income and program. 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. The package introduces new mata functions and a plugin used. 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. We present a new family of stata functions devoted to small area estimation, sae. Apr 16, 2017 small area estimation sae has become a widely used technique in official statistics since the last decade of past century.
For a comprehensive account of sae techniques, seerao2003. Small area estimation sae has become a widely used technique in official statistics since the last decade of past century. A common approach to small area estimation is to derive predictors under a. The course will begin with a history of smallarea estimation and different uses of smallarea statistics in both public and private sectors. 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. 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. This course will provide an introduction to the main concepts and.
Structure of the commands are intuitive for future. Mata functions and codes are open source and can be linked with new functions or methods by. A small area procedure for estimating population counts. A common approach to small area estimation is to derive predictors under a speci ed mixed model for the direct estimators. The modelbased approach to small area estimation offers several advantages including. This is accomplished by incorporating information from outside sources.
Small area or small domain, local area, subdomain, small subgroup, minor domain, etc. Small area estimation deals with the problem of providing estimates of. 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. 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. 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. I have used gllamm in my applications with binary outcomes, although of course the speed has been killing me.
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