An Applied Comparison of Area-Level Linear Mixed Models in Small Area Estimation

作者：Pereira Luis Nobre^*; Coelho Pedro Simoes

来源：Communications in Statistics - Simulation and Computation, 2013, 42(3): 671-685.

DOI：10.1080/03610918.2011.654029

• Empirical best linear unbiased prediction
• Linear mixed model
• Small area estimation
• Spatial correlation
• Temporal autocorrelation

This article reviews four area-level linear mixed models that borrow strength by exploiting the possible correlation among the neighboring areas or/and past time periods. Its main goal is to study if there are efficiency gains when a spatial dependence or/and a temporal autocorrelation among random-area effects are included into the models. The Fay-Herriot estimator is used as benchmark. A design-based simulation study based on real data collected from a longitudinal survey conducted by a statistical office is presented. Our results show that models that explore both spatial and chronological association considerably improve the efficiency of small area estimates.

• 出版日期2013