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    Wyświetlanie 1-5 z 5
    Tytuł:
    A Comparison of Small Area and Calibration Estimators via Simulation
    Autorzy:
    Hidiroglou, Michael A.
    Estevao, Victor M.
    Powiązania:
    https://bibliotekanauki.pl/articles/465930.pdf
    Data publikacji:
    2016
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    area level
    unit level
    calibration estimates
    small area estimates
    simulation
    Opis:
    Domain estimates are typically obtained using calibration estimators that are direct or modified direct. They are direct if they strictly use data within the domain of interest. They are modified direct if they use both data within and outside the domain of interest. An alternative way of producing these estimates is through small area procedures. In this article, we compare the performance of these two approaches via a simulation. The population is generated using a hierarchical model that includes both area effects and unit level random errors. The population is made up of mutually exclusive domains of different sizes, ranging from a small number of units to a large number of units. We select many independent simple random samples of fixed size from the population and compute various estimates for each sample using the available auxiliary information. The estimates computed for the simulation included the Horvitz-Thompson estimator, the synthetic estimator (indirect estimate), calibration estimators, and unit level based estimators (small area estimate). The performance of these estimators is summarized based on their design- based properties
    Źródło:
    Statistics in Transition new series; 2016, 17, 1; 133-154
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Covariate Selection for Small Area Estimation in Repeated Sample Surveys
    Autorzy:
    van den Brakel, Jan A.
    Buelens, Bart
    Powiązania:
    https://bibliotekanauki.pl/articles/465973.pdf
    Data publikacji:
    2015
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    area level models
    cAIC
    Hierachical Bayesian predictors
    Opis:
    If the implementation of small area estimation methods to multiple editions of a repeated sample survey is considered, then the question arises which covariates to use in the models. Applying standard model selection procedures independently to the different editions of the survey may identify different sets of covariates for each edition. If the small area predictions are sensitive to the different models, this is undesirable in official statistics since monitoring change over time of statistical quantities is of utmost importance. Therefore, potential confounding of true change and methodological alterations should be avoided. An approach to model selection is proposed resulting in a single set of covariates for multiple survey editions. This is achieved through conducting covariate selection simultaneously for all editions, minimizing the average of the edition-specific conditional Akaike Information Criteria. Consecutive editions of the Dutch crime victimization survey are used as a case study. Municipal estimates of three survey variables are obtained using area level models. The proposed averaging strategy is compared to the standard method of considering each edition separately, and to an elementary approach using covariates selected in the first edition. Resulting models, point estimates and MSE estimates are analyzed, indicating no substantial adverse effects of the conceptually attractive averaging strategy.
    Źródło:
    Statistics in Transition new series; 2015, 16, 4; 523-540
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Borrowing Information over time in Binomial/Logit Normal Models for Small Area Estimation
    Autorzy:
    Franco, Carolina
    Bell, William R.
    Powiązania:
    https://bibliotekanauki.pl/articles/465889.pdf
    Data publikacji:
    2015
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    area level model
    complex surveys
    American Community Survey
    bivariate
    model
    SAIPE
    Opis:
    Linear area level models for small area estimation, such as the Fay-Herriot model, face challenges when applied to discrete survey data. Such data commonly arise as direct survey estimates of the number of persons possessing some characteristic, such as the number of persons in poverty. For such applications, we examine a binomial/logit normal (BLN) model that assumes a binomial distribution for rescaled survey estimates and a normal distribution with a linear regression mean function for logits of the true proportions. Effective sample sizes are defined so variances given the true proportions equal corresponding sampling variances of the direct survey estimates. We extend the BLN model to bivariate and time series (first order autoregressive) versions to permit borrowing information from past survey estimates, then apply these models to data used by the U.S. Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) program to predict county poverty for school-age children. We compare prediction results from the alternative models to see how much the bivariate and time series models reduce prediction error variances from those of the univariate BLN model. Standard conditional variance calculations for corresponding linear Gaussian models that suggest how much variance reduction will be achieved from borrowing information over time with linear models agree generally with the BLN empirical results.
    Źródło:
    Statistics in Transition new series; 2015, 16, 4; 563-584
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Inferential Issues in Model-Based Small Area Estimation: Some New Developments
    Autorzy:
    Rao, J. N. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/465725.pdf
    Data publikacji:
    2015
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    area level models
    complex parameters
    informative sampling
    model misspecification
    robust estimation
    unit level models
    Opis:
    Small area estimation (SAE) has seen a rapid growth over the past 10 years or so. Earlier work is covered in the author's book (Rao 2003). The main purpose of this paper is to highlight some new developments in model-based SAE since the publication of the author's book. A large part of the new theory addressed practical issues associated with the model-based approach, and we present some of those methods for area level and unit level models. We also briefly mention some new work on synthetic estimation of area means or totals based on implicit models.
    Źródło:
    Statistics in Transition new series; 2015, 16, 4; 491-510
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Comparison of Small Area Estimation Methods for Poverty Mapping
    Autorzy:
    Guadarrama, María
    Molina, Isabel
    Rao, J. N. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/465671.pdf
    Data publikacji:
    2016
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    area level model
    non-linear parameters
    empirical best estimator
    hierarchical Bayes
    poverty mapping
    unit level models
    Opis:
    We review main small area estimation methods for the estimation of general nonlinear parameters focusing on FGT family of poverty indicators introduced by Foster, Greer and Thorbecke (1984). In particular, we consider direct estimation, the Fay-Herriot area level model (Fay and Herriot, 1979), the method of Elbers, Lanjouw and Lanjouw (2003) used by the World Bank, the empirical Best/Bayes (EB) method of Molina and Rao (2010) and its extension, the Census EB, and finally the hierarchical Bayes proposal of Molina, Nandram and Rao (2014). We put ourselves in the point of view of a practitioner and discuss, as objectively as possible, the benefits and drawbacks of each method, illustrating some of them through simulation studies.
    Źródło:
    Statistics in Transition new series; 2016, 17, 1; 41-66
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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