Estimation of Randomisation Mean Square Error in Small Area Estimation. (27th September 2018)

• Record Type: Journal Article
• Authors: Pfeffermann, Danny; Ben‐Hur, Dano
• Other Names: Chen Jiahua guestEditor.; Wu Changbao guestEditor.
• Is Part Of: International statistical review. Volume 87(2019)Supplement 1
• Page Start: S31
• Page End: S49
• Publication Date: 2018-09-27
• Subjects: Area‐level model -- design MSE -- mixed logistic model -- model‐based MSE; Statistics -- Periodicals; Statistics -- Bibliography -- Periodicals; Statistics -- Bibliography; Statistics -- Periodicals; Statistique; Statistique -- Périodiques; Statistique -- Bibliographie -- Périodiques; Statistique -- Étude et enseignement -- Périodiques; Statistique -- Étude et enseignement -- Bibliographie -- Périodiques; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 519.2
• DOI: 10.1111/insr.12289
• Languages: English
• ISSNs: 0306-7734

Abstract

Summary: In this article, we propose a new method for estimating the randomisation (design‐based) mean squared error (DMSE) of model‐dependent small area predictors. Analogously to classical survey sampling theory, the DMSE considers the finite population values as fixed numbers and accounts for the MSE of small area predictors over all possible sample selections. The proposed method models the true DMSE as computed for synthetic populations and samples drawn from them, as a function of known statistics and then applies the model to the original sample. Several simulation studies for the linear area‐level model and the unit‐level mixed logistic model illustrate the performance of the proposed method and compare it with the performance of other DMSE estimators proposed in the literature.