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Estimation of Small Area Proportions Based on Logistic Mixed Model
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 Title & Authors
Estimation of Small Area Proportions Based on Logistic Mixed Model
Jeong, Kwang-Mo; Son, Jung-Hyun;
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We consider a logistic model with random effects as the superpopulation for estimating the small area pro-portions. The best linear unbiased predictor under linear mired model is popular in small area estimation. We use this type of estimator under logistic mixed motel for the small area proportions, on which the estimation of mean squared error is also discussed. Two kinds of estimation methods, the parametric bootstrap and the linear approximation will be compared through a Monte Carlo study in the respects of the normality assumption on the random effects distribution and also the magnitude of sample sizes on the approximation.
Best linear unbiased predictor;small area;logistic mixed model;mean squared error;parametric bootstrap;
 Cited by
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