Comparison of unit level and area level small area estimators

被引:0
|
作者
Hidiroglou, Michael A. [1 ]
You, Yong [2 ]
机构
[1] STAT Canada, Business Survey Methods Div, Ottawa, ON K1A 0T6, Canada
[2] STAT Canada, Int Cooperat & Corp Stat Methods Div, Ottawa, ON K1A 0T6, Canada
关键词
Confidence interval; Design consistency; Fay-Herriot model; Informative sampling; Model misspecification; Nested error regression model; Relative root mean squared error (RRMSE); Survey weight; MEAN SQUARED ERROR; SURVEY WEIGHTS; PREDICTION;
D O I
暂无
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
In this paper, we compare the EBLUP and pseudo-EBLUP estimators for small area estimation under the nested error regression model and three area level model-based estimators using the Fay-Herriot model. We conduct a design-based simulation study to compare the model-based estimators for unit level and area level models under informative and non-informative sampling. In particular, we are interested in the confidence interval coverage rate of the unit level and area level estimators. We also compare the estimators if the model has been misspecified. Our simulation results show that estimators based on the unit level model perform better than those based on the area level. The pseudo-EBLUP estimator is the best among unit level and area level estimators.
引用
收藏
页码:41 / 61
页数:21
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