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  • Statistics In Transition


Article | 06-July-2017


This article considers a robust hierarchical Bayesian approach to deal with random effects of small area means when some of these effects assume extreme values, resulting in outliers. In the presence of outliers, the standard Fay-Herriot model, used for modeling area-level data, under normality assumptions of random effects may overestimate the random effects variance, thus providing less than ideal shrinkage towards the synthetic regression predictions and inhibiting the borrowing of

Adrijo Chakraborty, Gauri Sankar Datta, Abhyuday Mandal

Statistics in Transition New Series, Volume 17 , ISSUE 1, 67–90

Article | 18-March-2020

Robust estimation of wages in small enterprises:  the application to Poland’s districts

The paper presents an empirical study designed to test a small area estimation method. The aim of the study is to apply a robust version of the Fay-Herriot model to the estimation of average wages in the small business sector. Unlike the classical Fay-Herriot model, its robust version makes it possible to meet the assumption of normality of random effects under the presence of outliers. Moreover, the use of this version of the Fay-Herriot model helps to improve the precision of estimates

Grażyna Dehnel, Łukasz Wawrowski

Statistics in Transition New Series, Volume 21 , ISSUE 1, 137–157

Article | 15-September-2020

Effective transformation-based variable selection under two-fold subarea models in small area estimation

estimate an information criterion based on the transformed linking model and use the estimated information criterion for variable selection. The proposed method is motivated by the variable selection method of Lahiri and Suntornchost (2015) for the Fay-Herriot model and the variable selection method of Li and Lahiri (2019) for the unit-level nested-error regression model. Simulation results show that the proposed variable selection method performs significantly better than some naive competitors

Song Cai, J. N. K. Rao, Laura Dumitrescu, Golshid Chatrchi

Statistics in Transition New Series, Volume 21 , ISSUE 4, 68–83

Article | 27-May-2019


all. In order to correct the errors at the area level in our next census, we investigate the use of the following three-step procedure: A- Draw a sample from an enhanced register to obtain initial direct sample estimates for the number of persons residing in each area on “census day”, B- Fit the Fay-Herriot model to the direct estimates in an attempt to improve their accuracy, C- Compute a final census estimate for each statistical area as a linear combination of the estimate obtained

Danny Pfeffermann, Dano Ben-Hur, Olivia Blum

Statistics in Transition New Series, Volume 20 , ISSUE 1, 7–19

Research paper | 01-November-2017


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

Carolina Franco, William R. Bell

Statistics in Transition New Series, Volume 16 , ISSUE 4, 563–584

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