Estimation of Randomisation Mean Square Error in Small Area Estimation

Danny Pfeffermann, Dano Ben-Hur*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)S31-S49
JournalInternational Statistical Review
Volume87
Issue numberS1
DOIs
StatePublished - May 2019

Bibliographical note

Publisher Copyright:
© 2018 The Authors. International Statistical Review © 2018 International Statistical Institute

Keywords

  • Area-level model
  • design MSE
  • mixed logistic model
  • model-based MSE

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