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Estimation of Randomisation Mean Square Error in Small Area Estimation

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  • Danny Pfeffermann
  • Dano Ben‐Hur

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.

Suggested Citation

  • Danny Pfeffermann & Dano Ben‐Hur, 2019. "Estimation of Randomisation Mean Square Error in Small Area Estimation," International Statistical Review, International Statistical Institute, vol. 87(S1), pages 31-49, May.
    • Handle: RePEc:bla:istatr:v:87:y:2019:i:s1:p:s31-s49
    DOI: 10.1111/insr.12289
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    Cited by:

    1. Isabel Molina & Paul Corral & Minh Nguyen, 2022. "Estimation of poverty and inequality in small areas: review and discussion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1143-1166, December.

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