Effective Transformation-Based Variable Selection Under Two-Fold Subarea Models in Small Area Estimation

• Autorzy: Song Cai , J. N. K. Rao , Laura Dumitrescu , Golshid Chatrchi
• Języki publikacji: EN

Abstrakty

EN

We present a simple yet effective variable selection method for the two-fold nested subarea model, which generalizes the widely-used Fay-Herriot area model. The twofold subarea model consists of a sampling model and a linking model, which has a nested-error model structure but with unobserved responses. To select variables under the two-fold subarea model, we first transform the linking model into a model with the structure of a regular regression model and unobserved responses. We then 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, especially when the variance of the area-level random effect in the linking model is large. (original abstract)

Słowa kluczowe

EN

Small area estimates; Variables selection; Statistical models

PL

Statystyka małych obszarów; Dobór zmiennych; Modele statystyczne

• Czasopismo: Statistics in Transition
• Rocznik: 2020
• Tom: 21
• Numer: nr 4 Special Issue
• Strony: 68--83

Twórcy

autor

Song Cai

• Carleton University, Ottawa, ON, Canada

autor

J. N. K. Rao

• Carleton University, Ottawa, ON, Canada

autor

Laura Dumitrescu

• Victoria University of Wellington, Wellington, New Zealand

autor

Golshid Chatrchi

• Statistics Canada, Ottawa, Ontario, Canada

Bibliografia

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• LAHIRI, P., SUNTORNCHOST, J., (2015). Variable selection for linear mixed models with applications in small area estimation. Sankhy¯a B, 77(2), pp. 312-320.
• LI, Y., LAHIRI, P., (2019). A simple adaptation of variable selection software for regression models to select variables in nested error regression models. Sankhy¯a B, 81(2), pp. 302-371.
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• RAO, J. N. K., MOLINA, I., (2015). Small Area Estimation, 2nd Edition. Hoboken: Wiley.
• TORABI, M., RAO, J. N. K., (2014). On small area estimation under a sub-area level model. Journal of Multivariate Analysis, 127, pp. 36-55.
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Identyfikatory

DOI

10.21307/stattrans-2020-031