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Shiferaw Y, Galpin J. Corrected Confidence Intervals for a Small Area Parameter through the Weighted Estimator under the Basic Area Level Model. JIRSS. 2018; 17 (2)
URL: http://jirss.irstat.ir/article-1-440-en.html
Abstract:   (76 Views)

Area level linear mixed models can be generally applied to produce small area indirect estimators when only aggregated data such as sample means are available‎. ‎This paper tries to fill an important research gap in small area estimation literature‎, ‎the problem of constructing confidence intervals (CIs) when the estimated variance of the random effect as well as the estimated mean squared error (MSE) are negative‎. ‎More precisely‎, ‎the coverage accuracy of the proposed CI is of the order O-3/2‎, ‎where $m$ is the number of sampled areas‎. ‎The performance of the proposed method is illustrated with respect to coverage probability (CP) and average length (AL) using a simulation experiment‎. ‎Simulation results demonstrate the superiority of the proposed method over existing naive CIs‎. ‎In addition‎, ‎the proposed CI based on the weighted estimator is comparable with the existing corrected CIs based on empirical best linear unbiased predictor (EBLUP) in the literature‎.

Type of Study: Original Paper | Subject: 62Dxx: Sampling theory, sample surveys
Received: 2017/07/10 | Accepted: 2018/04/23 | Published: 2018/04/23

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