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 language | English |
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Pages (from-to) | S31-S49 |
Journal | International Statistical Review |
Volume | 87 |
Issue number | S1 |
DOIs | |
State | Published - 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