Small area estimation using unmatched sampling and linking models

By Yong-Hwan You, J. Rao. 2002

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Small Area Estimation via Multivariate Fay–Herriot Models with Latent Spatial Dependence (2013, background): “ with σ2 i representing the sampling variance at location i. This survey variance is often assumed known (provided by the oﬃcial statistical agency) and the normality assumption may be relaxed (e.g., You and Rao, 2002). In the second model stage (2), auxiliary information, through the covariates x i”
Hierarchical Bayes Modeling of Survey-Weighted Small Area Proportions (2014, unknown): “However, a nonlinear linking model is often preferred for modeling proportions, leading to unmatched sampling and linking models, as in Model 2 (see, for example, You and Rao, 2002).”
On parametric bootstrap methods for small area prediction (2006, background): “You and Rao (2002) called this the ‘mismatched model’ and used it to estimate undercoverage in the 1991 Canadian census.”