A Design-Based Approach to Small Area Estimation Using a Semiparametric Generalized Linear Mixed Model

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.