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Statistics in Transition New Series

An International Journal of the Polish Statistical Association

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics , Statistics & Probability

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ISSN: 1234-7655
eISSN: 2450-0291

DESCRIPTION

FEATURED ARTICLES

SUBJECTIVE AND COMMUNITY WELL-BEING INTERACTION IN A MULTILEVEL SPATIAL  MODELLING FRAMEWORK
LINEAR CHOLESKY DECOMPOSITION OF COVARIANCE MATRICES IN MIXED MODELS WITH CORRELATED RANDOM EFFECTS

VOLUME 16 , ISSUE 4 (December 2015) - List of articles

FROM THE EDITORS

Michael Hidiroglou/ Wlodzimierz Okrasa

DOI: 10.21307/stattrans-2015-027

FROM THE GUEST EDITORS (PART 1)

Raymond Chambers/ Malay Ghosh

DOI: 10.21307/stattrans-2015-028

INFERENTIAL ISSUES IN MODEL-BASED SMALL AREA ESTIMATION: SOME NEW DEVELOPMENTS

J. N. K. Rao

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 est(..)

DOI: 10.21307/stattrans-2015-029

Triple-goal estimation of unemployment rates for U.S. states using the U.S. Current Population Survey data

Daniel Bonnéry/ Yang Cheng/ Neung Soo Ha/ Partha Lahiri

In this paper, we first develop a triple-goal small area estimation methodology for simultaneous estimation of unemployment rates for U.S. states using the Current Population Survey (CPS) data and a two-level random sampling variance normal model. The main goal of this paper is to illustrate the utility of the triple-goal methodology in generating a single series of unemployment rate estimates for three separate purposes: developing estimates for individual small area means, producing empirical (..)

DOI: 10.21307/stattrans-2015-030

COVARIATE SELECTION FOR SMALL AREA ESTIMATION IN REPEATED SAMPLE SURVEYS

Jan A. van den Brakel/ Bart Buelens

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 statistic(..)

DOI: 10.21307/stattrans-2015-031

SMALL AREA ESTIMATION FOR SKEWED DATA IN THE PRESENCE OF ZEROES

Forough Karlberg

Skewed distributions with representative outliers pose a problem in many surveys. Various small area prediction approaches for skewed data based on transformation models have been proposed. However, in certain applications of those predictors, the fact that the survey data also contain a non-negligible number of zero-valued observations is sometimes dealt with rather crudely, for instance by arbitrarily adding a constant to each value (to allow zeroes to be considered as “positive observations, (..)

DOI: 10.21307/stattrans-2015-032

BORROWING INFORMATION OVER TIME IN BINOMIAL/LOGIT NORMAL MODELS FOR SMALL AREA ESTIMATION

Carolina Franco/ William R. Bell

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(..)

DOI: 10.21307/stattrans-2015-033

SMALL AREA ESTIMATES OF THE POPULATION DISTRIBUTION BY ETHNIC GROUP IN ENGLAND: A PROPOSAL USING STRUCTURE PRESERVING ESTIMATORS

Angela Luna/ Li-Chun Zhang/ Alison Whitworth/ Kirsten Piller

This paper addresses the problem of producing small area estimates of Ethnicity by Local Authority in England. A Structure Preserving approach is proposed, making use of the Generalized Structure Preserving Estimator. In order to identify the best way to use the available aggregate information, three fixed effects models with increasing levels of complexity were tested. Finite Population Mean Square Errors were estimated using a bootstrap approach. However, more complex models did not perform su(..)

DOI: 10.21307/stattrans-2015-034

SAE TEACHING USING SIMULATIONS

Jan Pablo Burgard/ Ralf Münnich

The increasing interest in applying small area estimation methods urges the needs for training in small area estimation. To better understand the behaviour of small area estimators in practice, simulations are a feasible way for evaluating and teaching properties of the estimators of interest. By designing such simulation studies, students gain a deeper understanding of small area estimation methods. Thus, we encourage to use appropriate simulations as an additional interactive tool in teaching (..)

DOI: 10.21307/stattrans-2015-035

SAE EDUCATION CHALLENGES TO ACADEMICS AND NSI

Elżbieta Gołata

The aim of the paper is to present some experiences in teaching Small Area Estimation (SAE). SAE education experiences and challenges are analysed from the academic side and from the NSI side. An attempt was undertaken to discuss SAE issues in a wider perspective of teaching statistics. In particular, the topics refer to Polish conditions, but they are presented against the background of selected international experiences and practices. Information comes from a special inquiry - a survey conduct(..)

DOI: 10.21307/stattrans-2015-036

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