A Design-Based Approach to Small Area Estimation Using a Semiparametric Generalized Linear Mixed Model
研究了半参数广义线性混合模型在样本稀少或无样本区域生成一致估计的能力，采用基于设计的刀切法计算方差，对统计和计量经济学研究者有用。
Summary In small area estimation, non-parametric models with penalized spline regression have been demonstrated to be a useful tool in creating granular area estimates to provide supplemental information where samples are few or non-existent. This study further examines the ability of a semiparametric generalized linear mixed model to produce conforming estimates for multiple area levels. A mosaic analogy is used to describe this process. A design-based jackknife method is employed for variance calculation.